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Jan 12, 1997 - on Independent Component Analysis and blind Signal Separation, ICA2003, ... and analytical solution to the differential source separation problem,â ... âUsing wold decomposition principle in blind separation of joint stationary ..... [83] R. Balan, A. Jourjine, and J. Rosca, âAR processes and sources can be ...

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References in Blind Separtion & Identification, and Control Theory. Ali Mansour ENSIETA, 29806 Brest, France Email: [email protected], http://ali.mansour.free.fr April 25, 2005

References [1] S. Abdallah and M. Plumbley, “Geometric ICA using nonlinear correlation and MDS,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 161–166. [2] K. Abed Meraim, Ph. Loubaton, and E. Moulines, “Déconvolution autodidacte mono-source/multi-capteurs: Techniques au second ordre,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 189–192. [3] K. Abed Meraim, Y. Hua, and A. Belouchrani, “A linear prediction-like algorithm for passive localization of nearfield sources,” in Fourth International Symposium on Signal Processing and its Applications (ISSPA’96), Gold Coast, Australia, August 25-30 1996, pp. 626–629. [4] K. Abed Meraim, A. Belouchrani, A. Mansour, and Y. Hua, “Parameter estimation of exponentially damped sinusoids using second order statistics,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 2025–2028, Elsevier. [5] K. Abed Meraim and Y. Hua, “Blind identification of multi-input multi-output system using minimum noise subspace,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 254–258, January 1997. [6] K. Abed Meraim, J. F. Cardoso, A. Gorokhov, Ph. Loubaton, and E. Moulines, “On subspace methods for blind identification of single-input multiple-output FIR systems,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 42–55, January 1997. [7] K. Abed Meraim, Ph. Loubaton, and E. Moulines, “A subspace algorithm for certain blind identification problems,” IEEE Trans. on Information Theory, vol. 43, no. 3, pp. 499–511, March 1997. [8] K. Abed Meraim, Ph. Loubaton, and E. Moulines, “Prediction error method for second-order blind identification,” IEEE Trans. on Information Theory, vol. 45, no. 3, pp. 694–705, March 1997. [9] K. Abed Meraim, Y. Hua, Ph. Loubaton, and E. Moulines, “Subspace method for blind identification of multichannel FIR systems in noise field with unknownspatial covariance,” IEEE Signal Processing Letters, vol. 4, no. 5, pp. 135–137, May 1997. [10] K. Abed Meraim, W. Qiu, and Y. Hua, “Blind system identification,” Proceedings of the IEEE, vol. 85, no. 8, pp. 1310–1322, 1997. [11] K. Abed Meraim, Y. Xiang, J. H. Manton, and Y Hua, “Blind source separation using second order cyclostationary statistics,” IEEE Trans. on Signal Processing, vol. 49, no. 4, pp. 694–701, April 2001. [12] F. Abrard, Y. Deville, and M. Benali, “Numerical and analytical solution to the differential source separation problem,” in Signal Processing VII, Theories and Applications (EUSIPCO’2000), Tamper, Finland, September 2000, pp. 4–8, Elsevier. [13] F. Abrard and Y. Deville, “Blind source separation in convolutive mixtures: a hybrid approach for colored sources,” in International work-conference on Artificial and Natural Networks, IWANN’2001, Menorca, Balearic Islands, Spain, 13-15 June 2001. [14] F. Abrard, Y. Deville, and P. R. White, “A new source separation approach for instantaneous mixtures based on time-frequency analysis,” in Proceedings of ECMS, Toulouse, France, May-June 2001, pp. 259–267. [15] A. I. Abu-el Haija, “Detecting the amplitude and frequency of noisy sinsusoidal signals,” INT. J. Electronics, vol. 69, no. 6, pp. 747–765, 1990. [16] S. Achard, D.-T. Pham, and C. Jutten, “Blind source separation in post nonlinear mixtures,” in Third International Workshop on Independent Component Analysis and signal Separation (ICA2001), San Diego, California, U.S.A, 9-12 December 2001, pp. 295–300. [17] S. Achard, D.-T. Pham, and C. Jutten, “Quadratic dependence measure for nonlinear blind sources separation,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 263–268. [18] D. Achavar, Séparation de sources: Généralisation ` a un modèle convolutif, Ph.D. thesis, Université de Montpellier II, Decembre 1993.

[19] A. Adib, E. Moreau, and D. Aboutajdine, “Blind sources separation by simultaneous generalized referenced contrasts diagonalization,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003. [20] A. Adib, E. Moreau, and D. Aboutajdine, “Sources separation contrasts using a reference signal,” IEEE Signal Processing Letters, vol. 11, no. 3, pp. 312–315, March 2004. [21] A. Ahmed, C. Andrieu, A. Doucet, and P. Rayner, “A multi-user kurtosis algorithm for blind source separation,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3148–3151. [22] M. R. Aghabozorgi and A. M. Doost-Hoseini, “Using wold decomposition principle in blind separation of joint stationary correlated sources,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 397–402. [23] W. Akmouche, E. Kerherve, and A. Quinquis, “Ofdm spectral characterization: Estimation of the bandwidth and the number of sub-carriers,” in 10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, Pocono Manor Inn, Pennsylvania, USA, 14 - 16 August 2000, pp. 48–52. [24] W. Akmouche, Etude et caractrisation des modulations multiporteuses OFDM, Ph.D. thesis, UBO, Brest, 12-Octobre 2000. [25] L. Albera, A. Ferreol, P. Comon, and P. Chevalier, “Sixth order blind identification of nderdetermined mixtures (BIRTH) of sources,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 909–914. [26] A. Albert, Regression and the moore-penrose pseudoinverse, Academic Press, New York and London, 1972. [27] L. I. Alfredsson, VLSI architectures and arithmetic operations with application to the Fermat number transform, Ph.D. thesis, Linkoping University, Sweden, 1996. [28] G. Aliftiras, Receiver implementations for a CDMA cellular system., Ph.D. thesis, Virginia Polytechnic Institute, USA, July 1996. [29] M.J. Al-Kindi and J. J. Dunlop, “Improved adaptive noise cancellation in the presence of signal leakage on the noise reference channel,” Signal Processing, vol. 17, pp. 241–250, 1989. [30] L. B. Almeida, “Faster training in nonlinear ICA using MISEP,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 113–118. [31] L. B. Almeida, “Linear and nonlinear ica based on mutual information– the misep method,” Signal Processing, vol. 84, pp. 231–245, 2004. [32] M. J. T. Alphey, D. I. Laurenson, and A. F. Murray, “Improvements in the on-line performance of informationmaximization-based blind signal separation,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 49–54. [33] J. Altuna and B. Mulgrew, “A comparison of cyclostationary blind equalization techniques,” in IEE Colloquium on Multipath Countermeasures, London, UK, 23-May 1996. [34] J. Altuna and B. Mulgrew, “A comparison of cyclostationary blind equalization algorithms in the mobile radio environment,” International Journal of adptive Control and Signal Processing, vol. John Wiley & Sons LTD, 1998. [35] A. Alwan, S. Narayanan, B. Strope, and A. Shen, “Speech production and perception models and their applications to synthesis, recognition, and coding,” in Speech Processing, revognition and Artificial Neural Networks, G. et al. Chollet, Ed., Springer, 1998, pp. 139–160. [36] S. I. Amari, K. Kurata, and H. Nagaoka, “Information geometry of Boltzmann machines,” IEEE Trans. on Neural Networks, vol. 3, no. 2, pp. 260–271, March 1992. [37] S. I. Amari, A. Cichocki, and H. H. Yang, “A new learning algorithm for blind signal separation,” in Neural Information Processing System 8, Eds. D.S. Toureyzky et. al., 1995, pp. 757–763. [38] S. I. Amari, “Geometry of semiparametric models and applications,” in ISI’96, 1996. [39] S. I. Amari, “Information geometry of neural networks -new Bayesian theory,” in International Conference on Neural Information Processing (ICONIP’96), Hong-Kong, September 1996, pp. 24–27. [40] S. I. Amari, “Gradient learning in structured parameter spaces: Adaptive blind separation of signal sources,” in The 1996 world congress on neural networks, San Diego, California, USA, 15-20 September 1996. [41] S. I. Amari, “Neural learning in structured parameter spaces: Natural Riemannian Gradient,” in Neural Information Processing System-Natural and Synthetic, San Diego, Colorado, USA, 2-7 December 1996. [42] S. I. Amari, , and N. Murata, “Statistical analysis of regularization constant - from bayes, MDL and NIC points of view,” in International work-conference on Artificial and Natural Networks, IWANN’97, Canary Islands, Spain, 4-6 June 1997, pp. 284–293. [43] S. I. Amari, S. Douglas, A. Cichocki, and H. Yang, “Novel on-line adaptive learning algorithms for blind deconvolution using the natural gradient approach,” in 11th IFAC Symposium on Systems Identification, Kitakyushu, Japan, July 1997.

[44] S. I. Amari, T. P. Chen, and A. Cichocki, “Stability analysis of adaptive blind source separation,” Neural Networks, vol. 10, no. 8, pp. 1345–1351, 1997. [45] S. I. Amari, S. C. Douglas, A. Cichocki, and H. H. Yang, “Multichannel blind deconvolution and equalization using the natural gradient,” in IEEE International workshop on wireless communication, Paris, France, 1997, pp. 101–104. [46] S. I. Amari and J. F. Cardoso, “Blind source separation-semiparametric statistical approach,” IEEE Trans. on Signal Processing, vol. 45, no. 11, pp. 2692–2700, November 1997. [47] S. I. Amari, “Natural gradient works efficiently in learning,” Neural Computation, vol. 10, no. 4, pp. 251–276, 1998. [48] S. I. Amari and A. Cichocki, “Adaptive blind signal processing-neural network appraches,” Proceedings of the IEEE, vol. 86, no. 10, pp. 2026–2048, 1998. [49] S. I. Amari, “ICA of temporally correlated signals - learning algorithm,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 13–18. [50] S.I. Amari, “Superefficiency in blind source separation,” IEEE Trans. on Signal Processing, vol. 47, no. 4, pp. 936–944, April 1999. [51] S.I. Amari, H. Park, and K. Fukumizu, “Adaptive method of realizing natural gradient learning for multilayer perceptrons,” Neural Computation, vol. 12, no. 6, pp. 1399–1409, 2000. [52] S.I. Amari, T. P. Chen, and A. Cichocki, “Nonholonomic orthogonal learning algorithms for blind sources separation,” Neural Computation, vol. 12, no. 6, pp. 1463–1484, 2000. [53] S.I. Amari, “Independent component analysis (ICA) and method of estimating functions,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E85-A, no. 3, pp. 570–547, 2002. [54] P. O. Amblard and J. L. Lacoume, “Statistiques d’ordre superieur des signaux complexes stationnaires et nonstationnaires,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, Septmber 1993, pp. 121–124. [55] P. O. Amblard, J. M. Brossier, and N. Charkani, “New adptative estimation of the fourth-order cumulant: Application to transient detection, blind deconvolution and timing recovery in communication,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 466–469, Elsevier. [56] P. O. Amblard and J. M. Brossier, “Adaptative estimation of the fourth-order cumulant of an i.i.d. stochastic process,” Signal Processing, vol. 42, pp. 37–43, February 1995. [57] M. G. Amin, A. Belouchrani, and Y. Zhang, “The spatial ambiguity functions and its applications,” IEEE Signal Processing Letters, vol. 7, no. 6, pp. 138–140, June 2000. [58] M. G. Amin and Y. Zhang, “Direction finding based on spatial time-frequency distribution matrices,” Digital Signal Processing, vol. 10, pp. 325–339, 2000. [59] K. Amleh and H. Li, “An algebraic approach to blind carrier offset and code timing estimation for ds-cdma systems,” IEEE Signal Processing Letters, vol. 10, no. 2, pp. 32–34, February 2003. [60] W. P. Ang and B. Farhang-Boroujeny, “A new class of gradient adaptive step-size LMS algorithms,” IEEE Trans. on Signal Processing, vol. 49, no. 4, pp. 805–810, April 2001. [61] A. ANGOT, Compléments de mathématiques, MASSON, 1972. [62] B. Ans, J. C. Gilhodes, and J. Hérault, “Simulation de réseaux neuronaux (sirene). II. hypothèse de décodage du message de mouvement porté par les afférences fusoriales IA et II par un mécanisme de plasticité synaptique,” C. R. Acad; Sci. Paris, vol. série III, pp. 419–422, 1983. [63] B. Ans, J. Hérault, and C. Jutten, “Adaptive neural architectures: Detection of primitives,” in Proceedings of COGNITIVA’85, Paris, France, 4-7 June 1985, pp. 593–597. [64] N. Arad and N. Dyn, “Almost cardinal spline interpolation,” Journal Approximation Theory, vol. 64, no. 1, pp. 133–144, july 1990. [65] S. Araki, S. Makino, and R. Mukai, “Equivalence between frequency-domain blind source separation and frequency domain adaptive beamformaing,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2002, ICASSP 2002, Orlando, Florida, U.S.A, 13-17 May 2002. [66] R. W. Ashby, Design for a brain, John Wiley and Sons, New York, 1952. [67] R. W. Ashby, An introduction to cybernetics, John Wiley and Sons, New York, 1952. [68] M. Athans, “The matrix minimum principle,” Information and Control, vol. 11, pp. 592–606, 1968. [69] H. Attias and C. E. Schreiner, “Blind source separation and deconvolution: The dynamic componenet analysis algorithm,” Neural Computation, vol. 10, pp. 1373–1424, 1998. [70] F. Auger, P. Flandrin, P. Gon¸calvès, and O. Lemoine, “Time-frequency toolbox: For use with matlab,” 1996. [71] C. Aviles-Cruz and A. Guérin-Dugué, “Textures discriminattion enhancement by fusion with second and fourth order statistics,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, Elsevier. [72] E. E. Azzouz and A. K. Nandi, Automatic modulation recognition of communication signals, Kluwer Academic Publishers, 1996.

[73] M. Babaie-Zadeh, C. Jutten, and K. Nayebi, “Mutual information minimization for separating the convolutive mixtures,” in International work-conference on Artificial and Natural Networks, IWANN’2001, Menorca, Balearic Islands, Spain, 13-15 June 2001. [74] M. Babaie-Zadeh, C. Jutten, and K. Nayebi, “Applying multi dimensional score functions to separating post non-linear mixtures,” in Proceedings of ICA’2001, USA, 2001. [75] M. Babaie-Zadeh, On blind source separation in convolutive and nonlinear mixtures, Ph.D. thesis, INPG Grenoble, 20-Septembre 2002. [76] M. Babaie-Zadeh, C. Jutten, and K. Nayebi, “Differential of mutual information function,” IEEE Signal Processing Letters, 2002. [77] M. Babaie-Zadeh, A. Mansour, C. Jutten, and F. Marvasti, “A geometrical approach for separating several speech signals,” in International Workshop on Independent Component Analysis and signal Separation (ICA2004), Granada, Spain, 22-24 September 2004, pp. 798–806. [78] F. R. Bach and M. I. Jordan, “Finding clusters in independent component analysis,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 891–896. [79] A. D. Back and A. Cichocki, “Blind source separation and deconvolution of fast sampled signals,” in Progress in Connectionist-Based Information Systems, Eds. N. Kasabov,(ICONIP-97), New Zealand, November 1997, pp. 637–641. [80] U. M. Bae, H. M. Park, and S. Y. Lee, “Top-down attention to complement independent component analysis for blind signal separation,” NeuroComputing, , no. 49, pp. 315–327, 2002. [81] E. Bai and M. Fu, “Blind system identification and channel equalization of IIR systems without statistical information,” IEEE Trans. on Signal Processing, vol. 47, no. 7, pp. 1910–1921, July 1999. [82] T. S. Bakir and R. M. Mersereau, “Blind adaptive derevebreation of speech signals using a microphone array,” in 13th Annual Workshop on Adaptive Sensor Array Processing, Lexington, USA, June 7-8 2003. [83] R. Balan, A. Jourjine, and J. Rosca, “AR processes and sources can be reconstructed from degenerate mixtures,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 467–472. [84] R. Balan, J. Rosca, S. Rickard, and J. O’Ruanaidh, “The influence of windowing on time delay estimates,” in Proceedings of the 2000 CISS, Princeton, NJ, USA, March 2000, pp. 15–17. [85] R. Balan, J. Rosca, and S. Rickard, “Robustness of parametric source demixing in echoic environments,” in Third International Workshop on Independent Component Analysis and signal Separation (ICA2001), San Diego, California, U.S.A, 9-12 December 2001, pp. 144–149. [86] R. Balan, J. Rosca, and S. Rickard, “Non-square blind source separation under coherent noise by beamforming and timefrequency masking,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 313–318. [87] M. Balin, “Idea-interactive deinterleaver for elint analysis,” in International Conference on Signal Processing, Applications & Technology, ICSPAT’96, 1996, pp. 852–856. [88] B. Barkat and B. Boashash, “Instantaneous frequency estimation of polynomial fm signals using the peak of the pwvd: statisitical performance in the presence of additive gaussian noise,” IEEE Trans. on Signal Processing, vol. 47, no. 9, pp. 2480–2490, September 1999. [89] B. Barkat and B. Boashash, “Design of higher order polynomial wigner ville distributions,” IEEE Trans. on Signal Processing, vol. 47, no. 9, pp. 2608–2611, September 1999. [90] R. G. Baraniuk and D. L. Jones, “Unitary equivalence: A new twist on signal processing,” IEEE Trans. Signal Processing, vol. 43, no. 10, pp. 2269–2282, Octobre 1995. [91] S. Barbarossa, A. Scaglione, and G. Giannakis, “Product high-order ambiguity function for multicomponent polynomialphase signal modeling,” IEEE Trans. on Signal Processing, vol. 46, no. 3, pp. 691–708, 1998. [92] C. B. Barber, D. P. Dobkin, and H. Huhdanpaa, “The quickhull algorithm for convex hulls,” ACM Trans. on Mathematical Software, vol. 22, no. 4, pp. 469–483, December 1996. [93] H.B. Barlow, “Possible principles underlying the transformation of sensory messages,” in Sensory Communication, W. Rosenblith, Ed. 1961, p. 217, MIT Press. [94] Y. Barness, J. Carlin, and M. Steinberger, “Bootstrapping adaptive cross pol cancelers for satellite communications,” in International Conference on Communication, Philadelphia, Pennsylvania, June 1982. [95] J.W. Barness, Y. Carlin and M.L. Steinberger, “Bootstrapping adaptative interference cancelers: some practical limitations,” in Proc. The Globecom. Conference, 1982, pp. 1251–1255. [96] J. Basak and S. I. Amari, “Blind separation of uniformly distributed signals: a general approach,” IEEE Trans. on Neural Networks, vol. 10, no. 5, pp. 1173–1185, September 1999. [97] M. Basseville, “Distance measures for signal processing and pattern recognition,” Signal Processing, vol. 18, no. 4, pp. 349–369, December 1989. [98] E. Bayer-Fluckiger, F. Oggier, and E. Viterbo, “New algebraic constructions of rotated z n -lattice constellations for the rayleigh fading channel,” IEEE Trans. on Information Theory, vol. 50, no. 4, pp. 702–714, April 2004.

[99] C. Beck and F. Schl¨ ogl, Thermodynamics of chaotic systems, Cambridge Nonlinear Science Series 4, Cambridge University Press, 1993. [100] M. Bellanger, Les filtres impulsionnels finis RIF, Traitement numérique du signal, Edition Cnet-Paris, 1972. [101] A. J. Bell and T. J. Sejnowski, “An information-maximization approach to blind separation and blind deconvolution,” Neural Computation, vol. 7, no. 6, pp. 1129–1159, November 1995. [102] T. Bell and T. Sejnowski, “The ’independent components’ of natural scenes are edge filters,” Vision Research, vol. 37, no. 23, pp. 3327–3338, 1997. [103] A. Belouchrani, K. Abed-Meraim, J. F. Cardoso, and E. Moulines, “Second-order blind separation of correlated sources,” in Int. Conf. on Digital Sig., Nicosia, Cyprus, july 1993, pp. 346–351. [104] A. Belouchrani and K. Abed-Meraim, “Séparation aveugle au second ordre de sources corrélées,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 309–312. [105] A. Belouchrani and J. F. Cardoso, “Maximum likelihood source separation for discrete sources,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 768–771, Elsevier. [106] A. Belouchrani and K. Abed Meraim, “Estimation du propagateur au quatrième ordre,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 189–192. [107] A. Belouchrani and J.-F. Cardoso, “Maximum likelihood source separation by the expectation-maximization technique,” in NOLTA 95, Las Vegas, USA, 1995. [108] A. Belouchrani, Séparation autodidacte de sources: Algoritmes, performances et application ` a des signaux expérimentaux, Ph.D. thesis, ENST Paris, 1995. [109] A. Belouchrani, K. Abed-Meraim, J. F. Cardoso, and E. Moulines, “A blind separation technique using second-order statistics,” IEEE Trans. on Signal Processing, vol. 45, no. 2, pp. 434–444, 1997. [110] A. Belouchrani and M. G. Amin, “Blind source separation based on time-frequency signal representations,” IEEE Trans. on Signal Processing, vol. 46, no. 11, pp. 2888–2897, 1998. [111] A. Belouchrani and M. G. Amin, “Time-frequency MUSIC,” IEEE Signal Processing Letters, vol. 6, no. 5, pp. 109–110, May 1999. [112] A. Belouchrani and M. G. Amin, “A two-sensor array blind beamformer for direct sequence spread spectrum communications,” IEEE Trans. on Signal Processing, vol. 47, no. 8, pp. 2191–2199, 1999. [113] A. Belouchrani and A. Cichocki, “Robust whitening procedure in blind separation context,” Electronics Letters, vol. 36, no. 24, pp. 2050–2051, 2000. [114] A. Belouchrani and M. G. Amin, “Jammer mitigation in spread spectrum communications using blind sources separation,” Signal Processing, vol. 80, pp. 723–729, 2000. [115] A. Belouchrani, K. Abed-meraim, M. Amin, and A. Zoubir, “Joint anti-diagonalization for blind source separation,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [116] Y. Bensadoun and E. Navakov, “Multi-dimensional adaptative method for cancelling EMG signal from the ECG signal,” in Proceedings of IEEE engineering in medicine and biology conference (CMBEC’95), 1995, pp. 173–174. [117] A. Benvéniste, M. Goursat, and G. Ruget, “Robust identification of a nonminimum phase system: blind adjustment of a linear equalizer in data communications.,” IEEE Trans. on Automatic Control, vol. AC-25, no. 3, pp. 385–399, June 1980. [118] A. Benvéniste, M. Métivier, and P. Priouret, Adaptive algorithms and stochastic approximations., Spring-Verlag, 1990. [119] J. F. Bercher, “Un algorithme de factorisation bispectrale,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 117–120. [120] A. Berthon, “Fonctions d’ambigu¨ıté, groupes de transformations et opérateurs de déplacement temps-fréquence. partie i,” Traitement du signal, vol. 19, no. 3, pp. 205–215, 2002. [121] G. Bienvenu and L. Kopp, “Optimality of high-resolution array processing using the eigensystem approach,” IEEE Trans. on ASSP, vol. 31, no. 5, pp. 1235–1248, 1983. [122] J. A. Bilmes, “A gentle tutorial of the EM algorithm and its application to parameter estimation for gaussian mixture and hidden markov models,” Tech. Rep., International Computer Science Institute, Berkely, USA, April 1998, TR-97-021. [123] R. Bitmead, S. Kung, B. D. O. Anderson, and T. Kailath, “Greatest common division via generalized Sylvester and Bezout matrices,” IEEE Trans. on Automatic Control, vol. 23, no. 6, pp. 1043–1047, December 1978. [124] Y. Blanco and S. Zazo, “New guanssianity measures based on order statistics: application to ica,” NeuroComputing, , no. 51, pp. 303–320, 2003. [125] H. A. P. Blom and Y. Bar-Shalom, “The interleaving multiple model algorithm for systems with markovian switching coefficients,” IEEE Trans. on Automatic Control, vol. 33, no. 8, pp. 780–783, August 1988. [126] B. Boashash, “Estimating and interpreting the instantaneous frequency of a signal part 1: Fundamental,” Proceedings of the IEEE, vol. 80, no. 4, pp. 520–537, Avril 1992.

[127] B. Boashash, “Estimating and interpreting the instantaneous frequency of a signal part 2: Algorithms and applications,” Proceedings of the IEEE, vol. 80, no. 4, pp. 540–568, Avril 1992. [128] B. Boashash and B. Ristich, “Polynomial wigner ville distributions and time varying higher order spectra,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 1992, ICASSP 1992, San Francisco, USA, March 1992. [129] B. Boashash and P. O’Shea, “Polynomial wigner-ville distributions and their relationship to time-varying higher order spectra,” IEEE Trans. on Sgnal Processing, vol. 42, no. 1, pp. 216–223, January 1994. [130] B. Boashash and B. Ristich, “Polynomial time-frequency distributions and time varying higher order spectra : application to the analysis of multicomponent fm signals and to the treatment of multiplicative noise,” Sgnal Processing, vol. 67, no. 1, pp. 1–23, January 1994. [131] P. Bofill and M. Zibulevsky, “Blind separation of more sources than mixtures using sparsity of their short-time fourier transform,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 87–92. [132] P. Bofill and M. Zibulevsky, “Underdetermined blind source separation using sparse representations,” Signal Processing, vol. 81, pp. 2353–2363, 2001. [133] P. Bofill, “Undetermined blind separation of delayed sound sources in the frequency domain,” NeuroComputing, p. To appear, 2002. [134] S. F. Boll, “Suppression of acoustic noise in speech using spectral subtraction,” IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. ASSP-27, no. 2, pp. 113–120, April 1979. [135] P. Bondoan, M. Benidir, and B. Picinbono, “Sur l’inversibilité de la matrice de corrélation d’un vecteur aléatoire ` a composantes polynomiales,” in Actes du XIIIème colloque GRETSI, Juan-Les-Pins, France, September 1991, pp. 13–16. [136] S. Bonnifay, K. Yao, and C. Jutten, “Underwater acoustic signal separation based on prior estimation of the channel impulse response,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3156–3159. [137] S. Bonnifay, Séparation de sources appliquée aux communications sous-marines, Ph.D. thesis, Université de Bretagne Occidentale, Octobre 2001. [138] A. Borovkov, Statistique mathématique, Mir, Moscou, 1987. [139] D. Boss and K. D. Kammeyer, “Statistical analysis of cumulant estimation errors with regard to an efficient blind ARMA identification,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [140] D. Boss and K. D. Kammeyer, “Blind estimation of ARMA systems,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 1105–1108, Elsevier. [141] D. Boss and K. D. Kammeyer, “Blind estimation of ARMA systems,” in IEEE International Conference on Communications, Montreal, Canada, June 1997, pp. 46–50. [142] C. Bouder, G. Burel, and S. Azou, “Dtermination automatique des paramtres dune transmission numrique,” in RTCLF (Runion des Thoriciens des Circuits de Langue Franaise), Brest, France, Octobre 1998. [143] M. Boumahdi, “Nouvel algorithme d’identification aveugle de systèmes linéaires perturbés en sortie par un bruit gaussien,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 85–88. [144] H. Boumaraf, Ch. Servière, and D.-T. Pham, “Extraction de signaux de parole dans un environnement acoustique par la sèparation aveugle de sources,” in Actes du 19ème colloque GRETSI, Paris, France, 8-11 September 2003. [145] M. Bouvet and S. C. Schwartz, “Underwater noises: Statistical modeling, detection, and normalization,” Journal of Acoustic Society of America, vol. 83, no. 3, pp. 1023–1033, March 1988. [146] A. Bouvier, M. George, and F. Le Lionnais, Dictionnaire des mathématiques, Presses Universitaires De France, 1993. [147] M. Bouzaien and A. Mansour, “HOS criteria & ICA algorithms applied to radar detection,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003. [148] A. H. Bowker and G. J. Lieberman, Méthodes statistiques de l’ingénieur, Dunod, Paris, 1965. [149] I. Bradaric, A. P. Petropulu, and K. Diamantaras, “Blind nxn MIMO system estimation using second order statistics,” in 34th Annual Conference on Information Sciences and Systems (CISS-2000), Princeton University, March 2000. [150] I. Bradaric, A. P. Petropulu, and K. Diamantaras, “On blind identification of FIR-MIMO systems with cyclostationary inputs using second order statistics,” IEEE Trans. on Signal Processing, vol. 51, no. 2, pp. 434–441, February 2003. [151] Paul S. Bradley and Usama M. Fayyad, “Refining initial points for K-Means clustering,” in Proc. 15th International Conf. on Machine Learning. 1998, pp. 91–99, Morgan Kaufmann, San Francisco, CA. [152] V. Braitenberg, VEHICLES, experiments in synthetic psychology, Academic Press, New York and London, 1972. [153] W. R. Braun, “PN acquisition and tracking performance in DS/CDMA systems with symbol-length spreading sequences,” IEEE Trans. on Communications, vol. 45, no. 12, pp. 1595–1601, December 1997. [154] D. R. Brillinger, Time series data analysis and theory, Holden Day, 1981. [155] L. Brillouin, Les tenseurs en mécanique et en élasticité, Jacques Gabay, 1987.

[156] C. Brolly, G. Alengrin, J. M. Lopez, and P. Perez, “Multi-hypothesis method in pulses deinterleaving,” in In SPIE Conference on Advanced Algorithms and Architectures for Signal Processing, San Diego (CA), USA, July 19-24 1998, pp. 273–282. [157] V. Buchoux, O. Cappé, E Moulines, and A. Gorokhov, “On the performance of semi-blind subspace-based channel estimation,” IEEE Trans. on Signal Processing, vol. 48, no. 6, pp. 1750–1759, 2000. [158] G. Burel, Reseaux de neurones en traitement d’images: Des modèls th´ eoriques aux applications industrielles, Ph.D. thesis, Université de Bretagne occidentale, 1991. [159] G. Burel, “Blind separation of sources: A nonlinear neural algorithme.,” Neural Networks, vol. 5, pp. 937–947, 1992. [160] G. BUREL, S. AZOU, and A. QUINQUIS, “Interception and furtivity of digital transmissions,” Communications 2002, Bucharest, Romania, 5-7 December 2002.

in In IEEE-

[161] V. Buzenac, R. Settineri, and M. Najim, “Non causal ARMA modelling: an adaptive gradient-based apprioach,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [162] G. Calot, Cours de statistique descriptive, dunod, Paris, 1971. [163] X. R. Cao and R. W. Liu, “General approch to blind source separation,” IEEE Trans. on Signal Processing, vol. 44, no. 3, pp. 562–571, March 1996. [164] V. Capdevielle, “Séparation de sources sinusoidales de frequences proches,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 337–340. [165] V. Capdevielle, C. Seviére, and J. L. Lacoume, “Separation of wide band sources,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 66–70. [166] V. Capdevielle, Séparation de sources large bande a l’aide des moments d’ordre supérieur, Ph.D. thesis, INP Grenoble, 1995. [167] V. Capdevielle, C. Seviére, and J. L. Lacoume, “Blind separation of wide-band sources: Application to rotating machine signals,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 2085– 2088, Elsevier. [168] J. F. Cardoso, “Blind identification of independent signals,” in Workshop on Higher-Order Spectral Analysis, Vail (CO), USA, June 1989. [169] J. F. Cardoso, “Source separation using higher order moments,” in Proceedings of International Conference on Speech and Signal Processing 1989, ICASSP 1989, Glasgow, Scotland, May 1989, pp. 2109–2212. [170] J. F. Cardoso, “Eigen-structure of the fourth-order cumulant tensor with application to the blind source separation problem,” in Proceedings of International Conference on Speech and Signal Processing 1990, ICASSP 1990, Albuquerque, USA, April 3-6 1990, pp. 2655–2658. [171] J. F. Cardoso and P. Comon, “Tensor-based independent component analysis,” in Signal Processing V, Theories and Applications (EUSIPCO’90), L. Torres, E. Masgrau, and M. A. Lagunas, Eds., Barcelona, Espain, 1990, pp. 673–676, Elsevier. [172] J. F. Cardoso, “Localisation et identification par la quadricovariance,” Traitement du signal, vol. 7, no. 5, pp. 397–406, December 1990. [173] J. F. Cardoso, “Super-symetric decomposition of the fourth-order cumulant tensor. blind identification of more sources than sensors.,” in Proceedings of International Conference on Speech and Signal Processing 1991, ICASSP’91, TorontoCanada, May 1991, pp. 3109–3112. [174] J.-F. Cardoso, “Higher-order narrow-band array processing,” in Proc. IEEE Signal Processing Workshop on Higher-Order Statistics, Chamrousse, France, June 1991, pp. 121–130. [175] J. F. Cardoso and B. Laheld, “Adaptive blind source separation for channel spatial equalization,” in Proc. cost229, Bordeaux, France, 1992, pp. 19–26. [176] J. F. Cardoso, “Iterative techniques for blind source separation using only fourth-order cumulants,” in Signal Processing VI, Theories and Applications (EUSIPCO’92), J. Vandewalle, R. Boite, M. Moonen, and A. Oosterlinck, Eds., Brussels, Belgium, August 1992, pp. 739–742, Elsevier. [177] J.-F. Cardoso and A. Souloumiac, “An efficient technique for blind separation of complex sources,” in Proc. IEEE Signal Processing Workshop on Higher-Order Statistics, South Lac Tahoe, USA (CA), June 1993, pp. 275–279. [178] J. F. Cardoso and A. Soulamic, “Blind beamforming for non-gaussian signals,” IEE Proceedings-F, vol. 140, no. 6, pp. 362, December 1993. [179] J. F. Cardoso, A. Belouchrani, and B. Laheld, “A new composite criterion for adaptive and iterative blind source separation,” in Proceedings of International Conference on Speech and Signal Processing 1994, ICASSP 1994, Adelaide, Australia, April 18-22 1994, pp. 273–276. [180] J. F. Cardoso, “On the performance of orthogonal source separation algorithm,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 776–779, Elsevier. [181] J. F. Cardoso and E Moulines, “A robustness property of doa estimators based on covariance,” IEEE Trans. Signal Processing, vol. 42, no. 11, pp. 3285–3287, November 1994.

[182] J. F. Cardoso and E Moulines, “Asymptotic performance analysis of direction-finding algorithms based on fourth-order cumulants,” IEEE Trans. Signal Processing, vol. 43, no. 1, pp. 214–224, January 1995. [183] J. F. Cardoso, S. Bose, and B. Friedlander, “Output cumulant matching for source separation,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 44–48. [184] J. F. Cardoso, “Séparation adaptative de sources dans l’espace signal,” in Actes du XVème colloque GRETSI, JuanLes-Pins, France, 18-21 September 1995, pp. 277–280. [185] J. F. Cardoso and P. Comon, “Independent component analysis, a survey of some algebraic methods,” in Proc. ISCAS Conference, Atlanta, USA, May 1996, vol. 2, pp. 93–96. [186] J. F. Cardoso and A. Soulamic, “Jacobi angles for simultaneous diagonalization,” SIAM, vol. 17, no. 1, pp. 161–164, 1996. [187] J. F. Cardoso and B. Laheld, “Equivariant adaptive source separation,” IEEE Trans. on Signal Processing, vol. 44, no. 12, pp. 3017–3030, December 1996. [188] J.-F. Cardoso, “Infomax and maximum likelihood for source separation,” IEEE Signal Processing Letters, vol. 4, pp. 112–114, 1997. [189] J. F. Cardoso, “Blind signal separation: statistical principles,” Proceedings of IEEE, pp. 2009–2025, October 1998. [190] J. F. Cardoso, C. Jutten, and Ph. Loubaton, “Preface of the ICA proceedings,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), Aussois, France, 11-15 January 1999. [191] J.-F. Cardoso, “High order contrasts for for independent component analysis,” Neural Computation, vol. 11, pp. 157–192, 1999. [192] J. F. Cardoso and D. L. Donoho, “Some experiments on independent component analysis of non-gaussian process,” in IEEE SP Int Workshop on High Order Statistics, HOS 99, Caeserea, Israel, 12-14 June 1999, pp. 74–77. [193] J.-F. Cardoso, J. Delabrouille, and G. Patanchon, “Independent component analysis of the cosmic microwave background,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 1111–1116. [194] A. Carini and E. Mumolo, “Fast squarre-root RLS adaptive filtering algorithms,” Signal Processing, vol. 57, pp. 233–250, 1997. [195] F. Castanie, “Modèles paramétriques non stationnaires,” in Traitement du signal-Développements Récents, Les Houches, France, August-September 1993. [196] L. Castedo, C. J. Escudero, and A. Dapena, “A blind signal separation method for multiuser communications,” IEEE Trans. on Signal Processing, vol. 45, no. 5, pp. 1343–1348, May 1997. [197] R. Caulcutt, Statistics in research and development, Chapman & Hall, London, New York, Tokyo, 1991. [198] D. C. B. Chan, S. J. Godsill, and P. J. W. Rayner, “Blind signal separation by output decorrelation,” in Proceedings of International Conference on Speech and Signal Processing 1996, ICASSP 1996, Atlanta, Georgia, May 1996. [199] D. Charles, “Constrained pca techniques for the identification of common factors in data,” NeuroComputating, vol. 22, pp. 145–156, 1998. [200] N. Charkani and J. Hérault, “On the performances of the fourth-order cross cumulants in blind separation of sources,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 86–90. [201] N. Charkani, Séparation auto-adaptative de sources pour les mélanges convolutifs. Application ` a la téléphonie mains-libres dans les voitures, Ph.D. thesis, INP Grenoble, November 1996. [202] N. Charkani and Y. Deville, “Self-adaptive separation of convolutively mixed signals with a recursive stricture. part I: Staility analysis and optimization of asymptotic behaviour,” Signal Processing, vol. 73, pp. 225–254, 1999. [203] N. Charkani and Y. Deville, “Self-adaptive separation of convolutively mixed signals with a recursive stricture. part II: Theoretical extensions and application to synthetic and real signals,” Signal Processing, vol. 75, pp. 117–140, 1999. [204] E. Chaumette, P. Comon, and D. Muller, “Application of ICA to airport surveillance,” in HOS 93, South Lake TahoeCalifornia, 7-9 June 1993, pp. 210–214. [205] E. Chaumette, P. Comon, and D. Muller, “An ICA-based technique for radiating sources estimation; application to airport surveillance,” IEE Proceedings - Part F, vol. 140, no. 6, pp. 395–401, december 1993. [206] E. Chaumette and D. Muller, “Séparation de sources aux ordres supérieurs : application au garbling en radar secondaire,” in Actes du l’Ecole des technique avancées en signal, image et parole, Grenoble, France, septembre 1996, pp. 245–253. [207] B. Chen, A. P. Petropulu, and K. I. Diamantaras, “Error analysis of SOS-based MIMO system identification algorithm,” in 33th Annual Asilomar Conference on Signals, Systems, and Comupters, Pacific Grove, Canada, September 1999. [208] B. Chen and A. P. Petropulu, “Multiple-input-multiple-output blind system identification based on cross-polyspectra,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 584–587. [209] B. Chen and A. P. Petropulu, “Frequency domain blind MIMO system identification based on second- and higher order statistics,” IEEE Trans. on Signal Processing, vol. 49, no. 8, pp. 1677–1688, August 2001. [210] H. Chen, T. K. Sarkar, S. A. Dianat, and J. D. Brule, “Adaptive spectral estimation by the conjugate gradient method,” IEEE Trans. on Acoustics, Speech and Signal Processing, vol. ASSP-34, no. 2, pp. 272–284, April 1986.

[211] J. F. Chen and W. ser, “Speech detection using microphone array.,” Electronics Letters, vol. 36, no. 1, pp. 181–182, January 2000. [212] W. Chen, U. Mitra, and P. Schniter, “On the equivalence of the three reduced rank linear estimators with applications to DS-CDMA,” IEEE Trans. on Information Theory, vol. 48, no. 9, pp. 2609–2614, September 2002. [213] W. Chen, J. P. Reilly, and K. M. Wong, “Detection of the number of signals in noise with banded covariance matrices,” IEE Proceedings- Radar, sonar and Navogation, vol. 143, no. 5, pp. 289–294, Ovtober 1996. [214] Y. F. Chen, M. D. Zoltowski, J. ramos, C. Chatterjee, and V. P. Roychowdhury, “Reduced-dimension blind space time 2-d rake receivers for DS-CDMA communication systems,” IEEE Signal Trans on Processing Letters, vol. 48, no. 6, pp. 1521–1536, October 2000. [215] P. Chevalier, “Performances des séparations aveugles de sources aux ordres supérieurs,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 297–300. [216] P. Chevalier, A. Ferrol, and J. P. Denis, “New geometrical results about 4-th order direction finding methods performances,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 923–926, Elsevier. [217] P. Chevalier, G. Benoit, and A. Ferrol, “Direction finding after blind identification of sources steering vectors: The blind-MACXCOR and blind-MUSIC methods,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 923–926, Elsevier. [218] P. Chevalier, “Optimal separation of independent narrow-band sources: Concept and performance,” Signal Processing, vol. 73, pp. 27–47, 1999. [219] P. Chevalier, “On the blind implementation of the ultimate source separators for arbitrary noisy mixtures,” Signal Processing, vol. 78, pp. 277–287, 1999. [220] P. Chevalier and P. Comon, Séparation aveugle de sources, vol. TE 5- 250, Téchniques de l’Ingédnieur, Paris, 2002. [221] A. Chevreuil and Ph. Loubaton, “MIMO blind second-order equalization method and conjugate cyclostationarity,” IEEE Trans. on Signal Processing, vol. 47, no. 6, pp. 572–578, 2000. [222] A. Chevreuil, E. serpedin, Ph. Loubaton, and G. B. Giannakis, “Blind channel identification and equalization using periodic modulation precoders: Prformance analysis,” IEEE Trans. on Signal Processing, vol. 48, no. 6, pp. 1570–1586, 2000. [223] C. Y. Chi, “Fourier series based nonminimum phase model for statistical signal processing.,” IEEE Trans. on Signal Processing, vol. 47, no. 8, pp. 2228–2240, 1999. [224] C. Y. Chi and C. H. chen, “Two-dimensional frequency-domain blind system identification using higher order statistics with application to texture synthesis,” IEEE Trans. on Signal Processing, vol. 49, no. 4, pp. 864–877, April 2001. [225] P. Chi, Timing and frequency synchronization issues for narrowband wireless communication systems, Ph.D. thesis, University of California at Berkeley, USA, December 2002. [226] A. J. Chipperfield and P. J. Fleming, “The matlab genetic algorithm toolbox,” in IEE Colloquium on Applied Control Techniques using Matlab, January 1995, Dept of Automatic control and systems engineering, University of Sheffield, England. [227] S. Choi and A. Cichocki, “Adaptive blin separation of speech signals: Cocktail party problem,” in Proceedings of International Conference on Speech and Signal Processing 1997, ICASSP 1997, Munich, Germany, 1997. [228] S. Choi and A. Cichocki, “Blind signal deconvolution by spatio-temporal decorrelation and demixing,” in 7th IEEE Workshop on Neural Networks for Signal Processing (NNSP), Florida, USA, September 1997, pp. 426–435. [229] S. Choi, A. Cichocki, and S. I. Amari, “Two spatio-temporal decorrelation algorithms and their application to blind deconvolution of multiple channels,” in Proceedings of International Conference on Speech and Signal Processing 1999, ICASSP 1999, Arizona, USA, March 1999, pp. 1085–1088. [230] S. Choi, H. K. Kim, and H. S. Lee, “Speech recognition using quantized lsp parameters and their transformations in digital communication,” Speech Communication, vol. 30, pp. 223–233, 2000. [231] P. G. Ciarlet, Introduction ` a l’analyse numérique matricielle et ` a l’optimisation, Masson, Paris and Milan and Barcelone, 1990. [232] P. Ciblat, A. Chevreuil, and Ph. Loubaton, “α-repitation/modulation and blind second-order identification,” IEEE Trans. on Signal Processing, vol. 48, no. 11, pp. 3153–3161, November 2000. [233] A. Cichocki, S. Douglas, S. I. Amari, and P. Mierzejewski, “Independent component analysis for noisy data,” in Proc. of International Workshop on Independence & Artificial Neural Networks, Tenerife, SPAIN, February 9-10 1994, pp. 52–58. [234] A. Cichocki, W. Kasprzak, and S. I. Amari, “Multi-layer neural networks with a local adaptive learning rule for blind separation of source signals,” in Proceedings of the 1995 International Symposium on Nonlinear Theory and Its Applications (NOLTA ’95), Tokyo, Japan, 1995, pp. 61–65. [235] A. Cichocki and R. Unbehauen, “Robust neural networks with on-line learning for blind identification and blind separation of sources,” IEEE Trans. on circuits & systems, vol. 43, pp. 894–906, 1996. [236] A. Cichocki, S. I. Amari, and J. Cao, “Blind separation of delayed and convolutive signals with self-adaptive learning rate,,” in Proceedings of 1996 International Symposium on Nonlinear Theory and its Applications, 1996, pp. 229–232.

[237] A. Cichocki, S. I. Amari, and R. Thawonmas, “Blind signal extraction using self-adaptive non-linear hebbian learning rule,” in Proceedings of the 1996 International Symposium on Nonlinear Theory and Its Applications (NOLTA ’96), Kochi, JAPAN, 1996, pp. 377–380. [238] A. Cichocki, S. I. Amari, M. Adachi, and W. Kasprzak, “Self-adaptive neural networks for blind separation of sources,” in IEEE International Symposium on Circuits and Systems, Piscataway, NJ, U.S.A, December 1996, pp. 157–160. [239] A. Cichocki, I. Sabala, S. Choi, B. Orsier, and R. Szupiluk, “Self-adaptive independent component analysis for subgaussian and super-gaussian mixtures with an unknown number of sources and additive noise,” in Proceedings of the 1997 International Symposium on Nonlinear Theory and Its Applications (NOLTA ’97), Hawaii, U.S.A, December 1997, pp. 731–734. [240] A. Cichocki, I. Sabala, and S. I. Amari, “Intelligent neural networks for blind signal separation with unknown number of sources,” in Proc. of Conf. Engineering of Intelligent Systems, ESI-98, Tenerife, SPAIN, 1998. [241] A. Chichocki, S. C. Douglas, and S. Amari, “Robust techniques for independent component analysis (ica) with noisy data,” NeuroComputating, vol. 22, pp. 113–129, 1998. [242] A. Chichocki, J. Karhunen, W. Kasprzak, and R. Vigario, “Neural networks bor blind separation with unknown number of sources,” NeuroComputing, , no. 24, pp. 55–93, 1999. [243] A. Cichocki and S. I. Amari, Adaptive blind signal and image processing: Learning algorithms and applications, John Wely & Sons, 2002. [244] V. Clarkson, J. Perkins, and I. Mareels, “On the novel application of number theoretic methods to radar detection,” in International Conference on Signal Processing, Applications & Technology, ICSPAT’93, 1993. [245] A. Coatanhay, L. Soufflet, L. Staner, and P. Boeijinga, “EEG source identification: frequency analysis during sleep,” C. R. Biologies, , no. 325, pp. 273–282, 2002. [246] M. H. Cohen and A. G. Andreou, “Current-mode subthreshold MOS implementation of the Hérault-Jutten autoadaptative network,” IEEE Journal on Solide state Circuits, vol. 26, no. 5, pp. 714–727, May 1992. [247] P. Comon, “Statistical approach to the Jutten-Herault algorithm,” in Neuro-Computing: Algorithms, architectures and applications, J. Hérault and F. Fogelman-Soulié, Eds., Les Arcs, France, February 27-March 3 1989, pp. 81–88, Springer Verlag, NATO ASI Series, Series F, Vol 68. [248] P. Comon, “Séparation de mélanges de signaux,” in Actes du XIIème colloque GRETSI, Juan-Les-Pins, France, June 1989, pp. 137–140. [249] P. Comon, “Separation of stochastic processes whose a linear mixture is observed,” in Workshop on Higher-Order Spectral Analysis, Vail (CO), USA, June 1989, pp. 174–179. [250] P. Comon, “Separation of sources using higher-order cumulants,” in SPIE Vol. 1152 Advanced Algorithms and Architectures for Signal Processing IV, San Diego (CA), USA, August 8-10 1989. [251] P. Comon, “Analyse en composantes indépendantes et identification aveugle,” Traitement du signal, vol. 7, no. 5, pp. 435–450, December 1990. [252] P. Comon, “High-order separation, application to detection and localization,” in Signal Processing V, Theories and Applications (EUSIPCO’90), L. Torres, E. Masgrau, and M. A. Lagunas, Eds., Barcelona, Espain, 1990, pp. 277–280, Elsevier. [253] P. Comon, C. Jutten, and J. Hérault, “Blind separation of sources, Part II: Statement problem,” Signal Processing, vol. 24, no. 1, pp. 11–20, November 1991. [254] P. Comon, “Independent component analysis,” in International Workshop on High Order Statistics, J. L. Lacoume, M. A. Lagunas, and C. L. Nikias, Eds., Chamrousse, France, July 1991, pp. 111–120. [255] P. Comon, “Blind identification in presence of noise,” in Signal Processing VI, Theories and Applications (EUSIPCO’92), J. Vandewalle, R. Boite, M. Moonen, and A. Oosterlinck, Eds., Brussels, Belgium, August 1992, Elsevier. [256] P. Comon and Lacoume J. L., “Statistiques d’ordres supérieurs pour le traitement du signal,” in Ecole Predoctorale de physique, Traitement du signal-Développements Récents, Les Houches, France, August-September 1993. [257] P. Comon, “Independent component analysis, and the diagonalization of symmetric tensors,” in European Conference on Circuit Theory and Design - ECCTD, H. Dedieu, Ed., Davos, August 30-September 3 1993, pp. 185–190, Elsevier. [258] P. Comon, “Remarque sur la diagonilisation tensorielle par la méthode de jacobi,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 125–128. [259] P. Comon, “Independent component analysis, a new concept?,” Signal Processing, vol. 36, no. 3, pp. 287–314, April 1994. [260] P. Comon, “Circularit et signaux alatoires temps discret,” Traitement du Signal, , no. 5, pp. 417–420, 1994. [261] P. Comon, “Tensor diagonalization, a useful tool in signal processing,” in IFAC-SYSID, 10th IFAC Symposium on System Identification, M. Blanke and T. Soderstrom, Eds., Copenhagen, Denmark, July 4-6 1994, vol. 1, pp. 77–82. [262] P. Comon and B. Emile, “Estimation of time delays in the blind mixture problem,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 482–485, Elsevier. [263] P. Comon, “Quelques developpements recents en traitement du signal,” Tech. Rep., Université de Nice Sophia-Antipolis, 18 September 1995, Habilitation de diriger des recherches.

[264] P Comon, “Contrasts for multichannel blind deconvolution,” IEEE Signal Processing Letters, vol. 3, no. 7, pp. 209–211, 1996. [265] P. Comon, “Blind channel identification and extraction of more sources than sensors,” in In SPIE Conference on Advanced Algorithms and Architectures for Signal Processing, San Diego (CA), USA, July 19-24 1998, pp. 2–13, Keynote address. [266] P. Comon, O. Grellier, and B. Mourrain, “Closed-form blind channel identification with MSK inputs,” in 32th Annual Asilomar Conference on Signals, Systems, and Comupters, Pacific Grove, California, USA, November 1-4 1998, pp. 1569–1573. [267] P. Comon and O. Grellier, “Non-linear inversion of underdetermined mixtures,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, FRANCE, 11-15 January 1999, pp. 461–465. [268] P. Comon and O. GRELLIER, “Analytical blind identification of a SISO communication channel,” in 10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, Pocono Manor Inn, Pennsylvania, USA, 14 - 16 August 2000, pp. 206–210. [269] P. Comon, “Block methods for channel identification and source separation,” in IEEE Symposium on Adaptive Systems for Signal Processing Communication and Control, Lake Louise, Alberta, Canada, October 1-4 2000, pp. 87–92. [270] P. Comon, “Tensor decompositions, state of the art and applications,” in IMA Conf. Mathematics in Signal Processing, Warwick, UK, Dec. 18-20 2000. [271] P. Comon, “From source separation to blind equalization, contrast-based approaches,” in Int. Conf. on Image and Signal Processing (ICISP’01), Agadir, MOROCCO, May 3-5 2001. [272] P. Comon and E. Moreau, “Blind MIMO equalization and joint diagonalization criteria,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [273] P. Comon, E. Moreau, and L. Rota, “Séparation de mélanges convolutifs par diagonalisation conjointe,” in 18eme Colloque Gretsi, Toulouse, 10-13 Sept 2001. [274] P. Comon, R. Liu, and D. Slock, “Path-wise wide-sense polynomial receiver for downlink UMTS communications,” in 39th Allerton Conference Communication Control Computer, Allerton, Illinois, USA, Oct 3-5 2001. [275] P. Comon, E. Moreau, and L. Rota, “Blind separation of convolutive mixtures: A contrast-based joint diagonalization approach,” in Third International Workshop on Independent Component Analysis and signal Separation (ICA2001), San Diego, California, U.S.A, 9-12 December 2001, pp. 686–691. [276] P. Comon, E. Moreau, and L. Rota, “Blind separation of convolutive mixtures: A contrast-based joint diagonalization approach,” in IMA Conf. Mathematics in Communications II, Lancaster Univ., UK, 16-18 December 2002. [277] P. Comon and L. Rota, “Blind separation of independent sources from convolutive mixtures,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E86-A, no. 3, pp. 542–549, March 2003. [278] P Comon, “Contrasts, independent component analysis, and blind deconvolution,” International Journal of Adaptive Control and Signal Processing, pp. 1–16, 2004. [279] D. V. Compernolle, “Switching adaptive filters for enhancing noisy and reverberant speech from microphone array recordings,” IEEE, vol. S15b.7, pp. 833–836, 1990. [280] T. Conroy and J. B. Moore, “The limits of extended kalman filtering for pulse train deinterleaving,” IEEE Trans. on Signal Processing, vol. 46, no. 12, pp. 3326–3332, December 1998. [281] J. Constantin, Ch. Nasr, and D. Hamad, “Hessian algorithm used in multilayered neural networks controllers in robot control,” in Intelligent Engineering Systems through Artificial Neural Networks, Volume 11, New York, USA, 2001, pp. 497–502. [282] A. G. Constantinides and T. Stathaki, “Some bounds on second and higher order correlations for bandlimited random processes,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 478–481, Elsevier. [283] E. Conte, A. De Maio, and C. Galdi, “Signal detection in compound-gaussian noise: Neyman-Pearson and CFAR detectors,” IEEE Trans. on Signal Processing, vol. 48, no. 2, pp. 419–428, January 2000. [284] J. H. Conway and R. K. Guy, Le livre des nombres, Eyrolles, Paris, 1998. [285] R. M. Corless, P. M. Gianni, B. M. Trager, and S. M. Watt, “The singular value decomposition for polynomial systems,” in International Symposium on Symbolic and Algebraic Computation, Montral, Canada, 10-12 July 1995, pp. 195–207. [286] L. W. Couch, Digital and Analog Communication Systems, Prentice Hall, 2001. [287] T. M. Cover and J. A. Thomas, Elements of information theory, Wiely Series in Telecommunications, 1991. [288] D. D. Cox, “A penalty method for nonparametric estimation of the logarithmic derivative of a density function,” Ann. Instit. Statist. Math., vol. 37, pp. 271–288, 1985. [289] S. Cruces, L. Castedo, and A. Chichocki, “novel blind source separation algorithms using cumulants,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3152–3155. [290] S. Cruces, L. Castedo, and A. Chichocki, “Robust blind source separation algorithms using cumulants,” NeuroComputing, p. To appear, 2002.

[291] S. Cruces-Alvarez, A. Cichocki, and L. Castedo-Ribas, “An iterative inversion approach to blind source separation,” IEEE Trans. on Neural Networks, vol. 11, no. 6, pp. 1423–1437, November 2000. [292] X. Dai, “A new blind separation method of convolutive mixture of regular signal based on hiden representation and system deconvolution,” Signal Processing, vol. 81, pp. 173–182, 2001. [293] J. W. Dalle Molle and A. T. Parsons, “Classification of man made transients and biological noises using second order cumulant spectrum,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [294] A. Dapena, L. Castedo, and C. J. Escudero, “An unconstrained single stage criterion for blind source separation,” in Proceedings of International Conference on Speech and Signal Processing 1996, ICASSP 1996, Atlanta, Georgia, 1996. [295] G. Darmois, “Analyse générale des liaisons stochastiques,” Rev. Inst. Intern. Stat., vol. 21, pp. 2–8, 1953. [296] I. Daubechies, “Orthonormal bases of compactly supported wavelets,” Communication on Pure Applied Mathematics, vol. 41, pp. 906–966, 1988. [297] C. Deboor, “On local linear functionals which vanish at all B-splines but one,” Theory of Approximations and Applications, pp. 120–145, 1976. [298] C. Deboor, A practical guide to splines, Springer-Verlag, 1978. [299] G. Deco and W. Brauer, “Nonlinear higher-order statistical decorrelation by volume-conserving neural architectures,” Neural Networks, vol. 8, no. 4, pp. 525–535, 1995. [300] M. De Courville, P. Duhamel, P. Madec, and J. Palicot, “A least mean squares blind equalization techniques for ofdm systems,” Ann. Tlcommun., vol. 52, no. 1-2, pp. 12–20, 1997. [301] S. Dégerine and R. Malki, “Second order blind separation of sources based on canonical partial innovations,” IEEE Trans. on Signal Processing, vol. 48, no. 3, pp. 629–641, March 2000. [302] A. Dekorsy and K. D. Kammeyer, “Complex valued block codes for OFDM-CDMA application,” in Workshop on MCCDMA 99, 1999. [303] A. Dekorsy and K. D. Kammeyer, “A new OFDM-CDMA up-link concept with M-ary orthogonal modulation,” European Trans. on Telecommunications (ETT), 2003, Special Issue on Multi-Carrier Spread-Spectrum. [304] L. De Lathauwer, B. De Moor, and J. Vandewalle, “Blind source separation by higher-order singular value decomposition,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 175–178, Elsevier. [305] L. De Lathauwer, D. Callaerts, B. De Moor, and J. Vandewalle, “Fetal electrocardiogram extraction by sources subspace separation,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 134–138. [306] L. De Lathauwer, D. Callaerts, B. De Moor, and J. Vandewalle, Fetal electrocardiogram extraction by independent componenet analysis, Manchester, 1995. [307] L. De Lathauwer, B. De Moor, and J. Vandewalle, “Blind source separation by simultaneous third-order tensor diagonalization,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 2089–2092, Elsevier. [308] L. De Lathauwer, P. Comon, B. De Moor, and J. Vandewalle, “ICA algorithms for 3 sources and 2 sensors,” in IEEE SP Int Workshop on High Order Statistics, HOS 99, Caeserea, Israel, 12-14 June 1999, pp. 116–120. [309] L. De Lathauwer and P. Comon, “Blind source separation and multichannel deconvolution,” Signal Processing, vol. 73, no. 1-2, pp. 3–4, February 1999, Special issue on Blind source separation and multichannel deconvolution. [310] L. De Lathauwer, B. De Moor, and J. Vandewalle, “Fetal electrocardiogram extraction by blind sources subspace separation,” IEEE Trans. on Biomedical Engineering, vol. 47, no. 5, pp. 567–572, May 2000. [311] L. De Lathauwer, b. D. Moor, and J. Vandewalle, “SVD-based methodologies for fetal electrocardiogram extraction,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3771–3774. [312] L. De Lathauwer, b. D. Moor, and J. Vandewalle, “Independent component analysis and (simultaneous) third-order tensor diagonalization,” IEEE Trans. on Signal Processing, vol. 49, no. 10, pp. 2262–2271, October 2001. [313] L. De Lathauwer, B. De Moor, J. Vandewalle, and J.-F. Cardoso, “Independent component analysis of largely underdetermined mixtures,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 29–33. [314] L. De Lathauwer, “The canonical decomposition and blind identification with more inputs than outputs: Some algebraic results,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 781–784. [315] N. Delfosse and P. Loubaton, “Séparation adaptative de sources indépendantes par une approche de déflation,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 309–312. [316] N. Delfosse and P. Loubaton, “Adaptive blind separation of independent sources: A deflation approach,” Signal Processing, vol. 45, no. 1, pp. 59–83, July 1995. [317] N. Delfosse and P. Loubaton, “Séparation aveugle adaptative de mélanges convolutifs,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 281–284.

[318] N. Delfosse, Séparation aveugle des sources: Méthodes de type sous-espace, Ph.D. thesis, ENST Paris, December 1995. [319] N. Delfosse and P. Loubaton, “Adaptive blind separation of convolutive mixtures,” in Proceedings of International Conference on Speech and Signal Processing 1996, ICASSP 1996, Atlanta, Georgia, May 1996, pp. 2940–2943. [320] J. P. Delams, H. Gazzah, A. P. Liavas, and P. A. Regalia, “Statistical analysis of some second-order methods for blind channel identification/equalization with respect to channel undermodeling,” IEEE Trans. on Signal Processing, vol. 48, no. 7, pp. 1984–1998, 2000. [321] J. P. Delams, “Asymptotic performance of second-order algorithms,” IEEE Trans. on Signal Processing, vol. 50, no. 1, pp. 49–57, 2002. [322] P. A. Delaney and D. O. Walsh, “A bibliography of higer-order spectra and cumulants,” IEEE Signal Processing Magasine, pp. 61–70, July 1994. [323] G. Delmaire, R. Lherbier, and E. carlier, “Two joint estimation decision methods for pollutant source monitoring : A comparison,” in XI European Signal Processing Conference (EUSIPCO 2002), Toulouse, France, 2002, Elsevier. [324] D. Dembélé and G. Favier, “Recursive estimation of fourth-order cumulants with application to identification,” Signal Processing, vol. 68, pp. 127–139, July 1998. [325] P. Demartines, Analyse de données par réseaux de neurones auto-organis´ es, Ph.D. thesis, LTIRF-INP Grenoble, November 1994. [326] A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” Journal of the Royal Statistical Society, B, vol. 39, pp. 1–38, 1977. [327] Deng T. B., “New method for designing stable recursive variable digital filters,” Signal Processing, vol. 65, pp. 197–207, 1998. [328] O. Deniz and M. Castrillon, M. ans Hernandez, “Face recognition using independent component analysis and support vector machines,” Pattern Recognition Letters, vol. 24, pp. 2153–2157, 2003. [329] G. Desodt and D. Muller, “Complex independent components analysis applied to the separation of radar signals,” in Signal Processing V, Theories and Applications (EUSIPCO’90), L. Torres, E. Masgrau, and M. A. Lagunas, Eds., Barcelona, Espain, 1994, pp. 665–668, Elsevier. [330] Y. Deville, “A unified convergence analysis of the Héraul-Jutten neural network,” in ICANN, 1995. [331] Y. Deville and L. Andry, “Application of blind source separation techniques to multi-tag contactless identification systems,” in Proceedings of the 1995 International Symposium on Nonlinear Theory and Its Applications (NOLTA ’95), Las Vegas, U.S.A, December 1995, pp. 73–78. [332] Y. Deville, “A unified stability analysis of the Hérault-Jutten source separation neural network,” Signal Processing, vol. 51, no. 3, pp. 229–233, June 1996. [333] Y. Deville, “Application of the Hérault-Jutten source separation neural network to multi-tag radio-frequency identification systems,” in Ecole des Techniques Avancées en Signal Image Parole, Grenoble, France, September 1996, pp. 265–272. [334] Y. Deville and L. Andry, “Application of blind source separation techniques to multi-tag contactless identification systems,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E79-A, no. 10, pp. 1694–1699, October 1996. [335] Y. Deville and N. Charkani, “Analysis of the stability of time-domain source separation algorithms for convolutively mixed signals,” in Proceedings of International Conference on Speech and Signal Processing 1997, ICASSP 1997, Munich, Germany, 1997. [336] Y. Deville and N. Charkani, “Convergence of source separation neural networks operating with self-normalized weight updating terms,” in International Workshop on Independent Component Analysis and Blind Separation of Signals, J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 227–232. [337] Y. Deville, “Towards industrial applications of blind source separation and independent componenet analysis,” in International Workshop on Independent Component Analysis and Blind Separation of Signals, J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 19–24. [338] Y. Deville and N. Damour, J. Charkani, “Improved multi-tag radio-frequency identification systems based on new source separation neural networks,” in International Workshop on Independent Component Analysis and Blind Separation of Signals, J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 449–454. [339] Y. Deville and M. Benali, “Differential source separation : concept and application to a criterion based on differential normalized kurtosis,” in Signal Processing VII, Theories and Applications (EUSIPCO’2000), Tamper, Finland, September 2000, Elsevier. [340] Y. Deville, F. Abrard, and M. Benali, “A new source separation concept and its validation on a preliminary speech enhancement configuration,” in Proceedings of CFA2000, Lausanne, Switzerland, September 2000, pp. 610–613, Elsevier. [341] Y. Deville and S. Savoldelli, “A second order differential approach for underdetermined convolutive source separation,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [342] K. Diamantaras and E. Chassioti, “Blind separation of n binary sources from one observation: A deterministic approach,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 93–98.

[343] K. Diamantaras, “Blind separation of multiple binary sources using a single linear mixture,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 2889–2892. [344] K. Diamantaras, “Blind channel identification based on the geometry of the received signal constellation,” IEEE Trans. on Signal Processing, vol. 50, no. 5, pp. 1133–1143, May 2002. [345] Z. Ding and L. Qiu, “Blind MIMO channel identification from second order statistics using rank deficient channel convolution matrix,” IEEE Trans. on Signal Processing, vol. 51, no. 2, pp. 535–544, February 2003. [346] S. Dodel, J. M. Herrmann, and T. Geisel, “Localization of brain activity - blind separation for fMRI data,” NeuroComputing, , no. 32-33, pp. 701–708, 2000. [347] M. Dogan and J. M. Mendel, “Application o cumulants to array processing - part i: Aperture extension and array calibration,” IEEE Trans. on Signal Processing, vol. 43, no. 5, pp. 1200–1216, 1995. [348] D. L. Donoho, “On minimum entropy deconvolution,” in Applied Time Series Analysis II, Tulsa, 1980, pp. 565–608. [349] J.L. Doob, Stochastic processes, Wiley Publications in Statistics, 1953. [350] S. C. Douglas, A. Cichocki, and S. I. Amari, “Multichannel blind separation and deconvolution of sources with arbitrary distributions, in the book neural networks for signal processing,” in Proc. of the 1997 IEEE Workshop (NNSP-97), N.Y. IEEE Press, September 1997, pp. 436–445. [351] S. C. Douglas, S. Y. Kung, and S. I. Amari, “On the numerical stabilities of prinicipal, minor, and independent component analysis algorithms,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 419–424. [352] S. C. Douglas, S. I. Amari, and S. Y. Kung, “On gradient adaptation with unit-norm constraints,” IEEE Trans. on Signal Processing, vol. 48, no. 6, pp. 1843–1847, 2000. [353] S. C. Douglas, “Blind source separation and independent component analysis: A crossroads of tools and ideas,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 1–10. [354] R. O. Duda and P. E. Hart, Pattern classification and scene analysis, John Wiley, NY, 1973, Ch6 describes the estimation of a mixture density from data samples. [355] P. J. Durka, D. Ircha, and K. J. Blinowska, “Stochastic time-frequency dictionaries for matching pursuit,” IEEE Trans. on Signal Processing, vol. 49, no. 3, pp. 507–510, March 2001. [356] G. D’urso and L. Cai, “Sources separation method applied to reactor monitoring,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [357] G. D’Urso, “Les techniques de séparation de sources appliquées ` a la surveillance d’installations EDF,” in Actes du l’Ecole des technique avancées en signal, image et parole, Grenoble, France, septembre 1996, pp. 255–263. [358] H. Egon, Statistique et probabilités, Hachette, Paris, 1992. [359] F. Ehlers and H. G. Schuster, “Blind separation of convolutive mixtures and an application in automatic speech recognition in a noisy environment,” IEEE Trans. on Signal Processing, vol. 45, no. 10, pp. 2608–2612, October 1997. [360] A. Einstein, Investigations on the theory of the Brownian Movement, Dover Publications, New York, 1956. [361] M. Elhilali, T. Chi, and S. Shamma, “A spectro-temporal modulation index (stmi) for assessement of speech intelligibility,” Speech Communication, 2002. [362] N. Elhor, R. Bertrand, J. G. Postaire, and D. Hamad, “Neural networks for wind turbine supervision,” Electrotechnik und Informationtechnik Journal, pp. 366–369, 1999. [363] S. D. Elton and D. A. Gray, “The application of circular statistics to specific radar pulse train detection,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, Elsevier. [364] S. D. Elton and B. J. Slocumb, “A robust kalman filter for estimation and tracking of a class of periodic discrete event processes,” in Fourth International Symposium on Signal Processing and its Applications (ISSPA’96), Gold Coast, Australia, August 25-30 1996, pp. 184–187. [365] S. D. Elton and B. J. Slocumb, “A state space approach to joint AOA and period estimation for a class of periodic discrete event process,” in IEEE Conf. of TENCON Digital Signal Processing Applications (TENCON’96), Perth, WA, Australia, 1996, pp. 686–691. [366] B. Emile, P. Comon, and J. LeRoux, “Estimation of time delays between wide-band sources,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 111–115. [367] B. Emile and P. Comon, “Estimation de temps de retard entre signaux colorés,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 285–288. [368] B. Emile, P. Comon, and J. LEROUX, “Estimation of time delays with fewer sensors than sources,” IEEE Trans. on Signal Processing, vol. 46, no. 7, pp. 2012–2015, September 1998. [369] B. Emile and P. Comon, “Estimation of time delays between unknown colored signals,” Signal Processing, vol. 69, pp. 93–100, 1998.

[370] D. Erdogmus, K. E. Hild II, and J. C. Principe., “Blind source separation using renyi’s a-marginal entropies,” NeuroComputing, vol. 49, no. 1, pp. 25–38, 2002. [371] A. Eriksson, P. Stoica, and T. S¨ oderstr¨ om, “On-line subspace algorithms for tracking moving sources,” IEEE Trans. on Signal Processing, vol. 42, no. 9, pp. 2319–2330, September 1994. [372] J. Eriksson and V. Koivunen, “Identifiability and separability of linear ICA models revisited,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 23–27. [373] J. Eriksson and V. Koivunen, “Characteristic-function-based independent component analysis,” Signal Processing, vol. 83, pp. 2195–2208, 2003. [374] A. Essebbar and N. Thirion, “Wideband sources localization using higher order statistics,” in HOS 95, Girona-Spain, 12-14 June 1995, pp. 51–55. [375] P. Etter, Underwater acoustic modeling principles, techniques and applications, Elsevier, New York, 1991. [376] G. Faucon, S. T. Mezalek, and R. Le Bouquin, “Study and comparison of three structures for enhancement of noisy speech,” in Proceedings of International Conference on Speech and Signal Processing 1989, ICASSP 1989, Glasgow, Scotland, May 1989, pp. 385–388. [377] G. Faucon and R. Le Bouquin, “debruitage de la parole pour les radio-mobiles,” in Actes du XIIIème colloque GRETSI, Juan-Les-Pins, France, September 1991, pp. 733–736. [378] G. Favier, D. Dembele, and J. L. Peyre, “ARMA identification using high-order statistics based linear methods: an unified presentation,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 203–207, Elsevier. [379] K. Fazel, “Performance of cdma/ofdm for mobile communication system,” in Proceedings of IEEE International Conference on Universal Personnal Communication, Ottawa, Canada, October 1993, pp. 975–979. [380] W. Feller, An introduction to probability theory and its applications. Wiley series in probability and mathematical statistics, John Wiley, 1968. [381] Ch. Ch. Feng and Ch. Y. Chi, “Performances of cumulant based inverse filters for blind deconvolution,” IEEE Trans. on Signal Processing, vol. 47, no. 7, pp. 1922–1935, 1999. [382] M. Feng and K.-D. Kammeyer, “Suppression of gaussian noise using cumulants: A quantitative analysis,” in Proceedings of International Conference on Speech and Signal Processing 1997, ICASSP 1997, Munich, Germany, 1997. [383] M. Feng and K.-D. Kammeyer, “Modified subspace smoothing technique for multipath direction finding,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Rhodes, Greece, September 1998, Elsevier. [384] M. Feng and K.-D. Kammeyer, “Blind source separation for communication signals using antenna arrays,” in IEEE International Conference on Universal Personal Communications (ICUPC98), Florence, Italy, October 1998. [385] M. Feng and K.-D. Kammeyer, “Application of source separation algorithms for mobile communication environments,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999. [386] J. Feng, “Training neuron models with the informax principle,” Neurocomputing, vol. 44-46, pp. 97–101, 2002. [387] E. R. Ferrara and B. Widrow, “Multichannel adaptive filtering for signal enhacement,” IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. ASSP-29, no. 3, pp. 766–770, June 1981. [388] L. Féty, Méthodes de traitement d’antenne adaptées aux radiocommunications, Ph.D. thesis, ENST Paris, 1988. [389] C. Févotte and C. Doncarli, “Two contributions to blind source separation using time-frequency distributions,” IEEE Signal Processing Letters, vol. 11, no. 3, pp. 386–389, March 2004. [390] H. M. Finucan, “A note on kurtosis,” Journal of the Royal Statistical Society (Series B), vol. 26, pp. 111–112, 1964. [391] S. Fiori, “Blind signal processing by the adaptive activation function neurons,” Neural Networks, vol. 13, pp. 597–611, 2000. [392] S. Fiori, “Blind separation of circularly distributed source signals by the neural extended APEX algorithm,” Neurocomputing, vol. 34, pp. 239 – 252, 2000. [393] C. Firmin, D. Hamad, J. G. Postaire, and R. D. Zhang, “Gaussian neural networks for glass bottles inspection: A learning procedure,” International Journal of Neural Systems, vol. 8, no. 1, pp. 41–46, February 1997, Sepecial issue on Neural Ntworks for Computer Vision Applications. [394] E. Fishler and H. Messer, “Order statistics approach for determining the number of sources using an array of sensors,” IEEE Signal Processing Letters, vol. 6, no. 7, pp. 179–182, July 1999. [395] P. Flandrin, Time-Frequency / Time-Scale analysis, Academic Press, Paris, 1999. [396] G. D. Forney, “Convolutional codes I: Agebraic structure,” IEEE Trans. on Information Theory, vol. IT-16, no. 6, pp. 720–738, 1970. [397] G. D. Forney, “Minimal bases of rational vector spaces, with applications to multivariable linear systems,” SIAM J. Control, vol. 13, no. 3, pp. 493–520, 1975. [398] J. C. Fort, “Stabilité de l’algorithme de séparation de sources de Jutten et Hérault,” Traitement du signal, vol. 8, no. 1, pp. 35–42, 1991.

[399] R. Fortet, Statistique, Dunod, Paris, 1972. [400] C. Fourgeaud and A. Fuchs, Statistique, Dunod, Paris, 1972. [401] Jr. Frank Ayres, Théorie et applications du calcul différentiel et intégral, McGraw-Hill, New York and Paris, 1972. [402] J. A. Freeman, Simulating neural networks with mathematica, MASSON, 1994. [403] Z. Fu and E. M. Dowling, “Conjugate gradient eigenstructure tracking for adaptive spectral estimation,” IEEE Trans. on Signal Processing, vol. 43, no. 5, pp. 1151–1160, May 1995. [404] M. Fujise, “Radio over fiber transmission technology for its and mobile communications,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E84-A, no. 8, pp. 1808–1814, August 2001, Special Section on Digital Signal Processing. [405] M. Gabrea, E. Grivel, and M. Najim, “A single microphone Kalman filter-based noise canceller,” IEEE Signal Processing Letters, vol. 6, no. 3, pp. 55–57, March 1999. [406] M. Gaeta and J. L. Lacoume, “Estimateurs du maximum de vraisemblance étendus ` a la séparation de sources non gaussiennes,” Traitement du Signal, vol. 7, no. 5, pp. 419–434, 1990. [407] M. Gaeta and J. L. Lacoume, “Sources separation without a priori knowledge: the maximum likelihood solution,” in Signal Processing V, Theories and Applications (EUSIPCO’90), L. Torres, E. Masgrau, and M. A. Lagunas, Eds., Barcelona, Espain, 1990, pp. 621–624, Elsevier. [408] M. Gaeta and J. L. Lacoume, “Source separation versus hypothesis,” in International Workshop on High Order Statistics, J. L. Lacoume, M. A. Lagunas, and C. L. Nikias, Eds., Chamrousse, France, July 1991, pp. 269–272. [409] M. Gaeta, Les statistiques d’ordre supérieur appliquées ` a la séparation de sources, Ph.D. thesis, CEPHAG-ENSIEG Grenoble, July 1991. [410] F. Gamboa, “Separation of sources having unknown discrete supports,” in Proc. IEEE-ATHOS Workshop on HigherOrder Statistics (HOS’95), Begur, Spain, 12-14 June 1995, pp. 56–60. [411] F. Gamboa and E. Gassiat, “Source separation when the input sources are discrete or have constant modulus,” IEEE Trans. on Signal Processing, vol. 45, no. 12, pp. 3062–3072, December 1997. [412] P. Garat, Approche statistique pour la séparation aveugle de sources, Ph.D. thesis, INP Grenoble, December 1994. [413] C. W. Gardiner, Handbook of stochastic methods for physics, chemistry, and the natural sciences, Springer, New York, 1993. [414] W. A. Gardner, “Correlation estimation and time-series modeling for nonstationary processes,” Signal Processing, vol. 15, no. 1, pp. 31–41, 1988. [415] D. Gaucher and C. Gervaise, “Feasibility of passive oceanic acoustic tomography : a cramer rao bounds approach,” in Oceans 2003 Marine Technology and Ocean Science Conference, San Diego, USA, 22-26 September 2003, pp. 56–60. [416] D. Gaucher, C. Gervaise, and G. Jourdain, “Feasibility of passive oceanic acoustic tomography in shallow water context: Optimal design of experiments,” in European Conference on UNDERWATER ACOUSTICS ECUA 2004, Delft, Netherlands, 5-8 July 2004, pp. 56–60. [417] S. Gazor and W. Zhang, “Speech probability distribution,” IEEE Signal Processing Letters, vol. 10, no. 7, pp. 204–207, July 2003. [418] H. Gazzah, Identification aveugle au second ordre: ordre et diversite des cannaux, Ph.D. thesis, ENST Paris, 2000. [419] H. Gazzah, A. Regalia, J. P. Delmas, and K. Abed-Meraim, “A blind multichannel identification algorithm robust to order overestimation,” IEEE Trans. on Signal Processing, vol. 50, no. 6, pp. 1449–1458, June 2002. [420] P. Georgiev and A. Cichocki, “Robust independent component analysis via time-delayed cumulant functions,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E86-A, no. 3, 2003. [421] W. H. Gerstacker and D. P. Taylor, “Blind channel order estimation based on second order statistics,” IEEE Signal Processing Letters, vol. 10, no. 2, pp. 39–42, February 2003. [422] C. Gervaise, A. Quinquis, and N. Martins, “Time frequency approach of blind study of acoustic submarine channel and source recognition,” in Physics in Signal and Imane Processing, PSIP 2001, Marseille, France, January 2001. [423] C. Gervaise, A. Quinquis, and I. Luzin, “High resolution identification of an underwater channel from unknown transient stimuli,” in 18eme Colloque Gretsi, Toulouse, 10-13 Sept 2001. [424] D. Gesbert, P. Duhamel, and S. Mayrargue, “Subspace-based adaptive algorithms for the blind equalization of multichannel fir filters,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 712–715, Elsevier. [425] D. Gesbert, Egalisation et identification multi-voies: Méthodes auto-adaptatives au second-ordre, Ph.D. thesis, ENST Paris, March 1997. [426] D. Gesbert, P. Duhamel, and S. Mayrargue, “On-line blind multichannel equalization based on mutually referenced filters,” IEEE Trans. on Signal Processing, vol. 45, no. 9, pp. 2307–2317, September 1997. [427] Z. Ghahramani and S. Roweis, “Learning nonlinear dynamical systems using an EM algorithm,” 1999. [428] X. Giannakopoulos, “Comparison of adaptive independent component analysis algorithms,” Tech. Rep., EPFL, Switzerland, March 1998.

[429] G. B. Giannakis and S. D. Halford, “Blind fractionally spaced equalization of noisy FIR channels: Direct and adaptive solutions,” IEEE Trans. on Signal Processing, vol. 45, no. 9, pp. 2277–2292, September 1997. [430] G. B. Giannakis, P. A. Anghel, and Z. Wang, “Wideband generalized multi-carrier cdma over frequency-selective wireless channels,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000. [431] G. B. Giannakis and E. Serpedin, “A bibliography on nonlinear system identification,” Signal Processing, vol. 81, pp. 533–580, 2001. [432] M. Girolami and C. Fyfe, “Negentropy and kurtosis as projection pursuit indices provide generalised ica algorithms,” Tech. Rep., University of Paisley, Scotland, July 1997, Technical Report. [433] M. Girolami and C. Fyfe, “an extended exploratory projection pursuit network with linear and nonlinear anti-hebbian lateral connections applied to the cocktail party problem,” Neural Networks, vol. 10, no. 9, pp. 1607–1618, 1997. [434] M. Girolami, “The latent variable data model for exploratory data analysis and visualization: A generalisation of the nonlinear infomax algorithm,” Neural Processing Letters, vol. 8, no. 1, pp. 27–39, 1998. [435] M. Girolami, “A nonlinear model of the binaural cocktail party effect,” NeuroComputating, vol. 22, pp. 201–215, 1998. [436] M. Girolami, “A variational method for learning sparse and overcomplete representations,” Neural Computation, vol. 13, no. 11, pp. 2517 – 2532, 1998. [437] M. Girolami, Self-organization neural networks: Independent component analysis and blind signal separation, SpringerVerlag Scientific Publishers, New York, London, Tokyo, 1999. [438] M. Girolami, Ed., Advances in independent component analysis (Perspectives in neural computing), Springer-Verlag Scientific Publishers, New York, London, Tokyo, 2000. [439] C. D. Giurc˘ aneanu and T˘ abu¸s, “On the sign of kurtosis,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 499–502. [440] F. Godtliebsen, J. S. Marron, and P. Chaudhuri, “Significance in scale space for density estimation,” Submitted to IEEE-TPAMI, 2002. [441] G. H. Golub and C. F. Van Loan, Matrix computations, The johns hopkins press- London, 1984. [442] E. G¨ onen and J. M. Mendel, “Applications of cumulants to array processing-part iii: Blind beamforming for coherent signals,” IEEE Trans. on Signal Processing, vol. 45, no. 9, pp. 2252–2264, September 1997. [443] E. G¨ onen, J. M. Mendel, and M. C. Doˇ gan, “Applications of cumulants to array processing-part iv: Direction finding in coherent signals case,” IEEE Trans. on Signal Processing, vol. 45, no. 9, pp. 2265–2276, September 1997. [444] A. Gorokhov and Ph. Loubaton, “Second order blind identification of convolutive mixtures with temporally correlated sources: A subspace based approch,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 2093–2096, Elsevier. [445] A. Gorokhov, Blind separation of convolutive mixtures: Second order methods, Ph.D. thesis, ENST Paris, 1997. [446] A. Gorokhov and Ph. Loubaton, “Subspace based techniques for second order blind separation of convolutive mixtures with temporally correlated sources,” IEEE Trans. on Circuits and Systems, vol. 44, pp. 813–820, September 1997. [447] A. Gorokhov, M. Kristensson, and B. Ottersten, “Robust blind second-order deconvolution,” IEEE Signal Processing Letters, vol. 6, no. 1, pp. 13–16, January 1999. [448] A. Gorokhov and P. Stoica, “Generalized quadratic minimization and blind multichannel deconvolution,” IEEE Trans. on Signal Processing, vol. 48, no. 1, pp. 201–213, January 2000. [449] K. Gosse and P. Duhamel, “Perfect reconstruction versus MMSE filter banks in source coding,” IEEE Trans. on Signal Processing, vol. 45, no. 9, pp. 2188–2202, September 1997. [450] X. Gourdon, Les maths en tête: Algèbre, Ellipses- Paris, 1994. [451] B. Grais, Méthodes statistiques, Dunod, Paris, 1990. [452] E. Granger, M. A. Rubin, S. Grossberg, and P. Lavoie, “A what-and-where fusion neural network for recognition and tracking of multiple radar emitters,” Tech. Rep., Boston University, USA, December 2000, Technical Report CAS/CNSTR-2000-029. [453] D. A. Gray, B. J. Slocumb, and S. D. Elton, “Parameter estimation for periodic dicrete event processes,” in Proceedings of International Conference on Speech and Signal Processing 1994, ICASSP 1994, Adelaide, Australia, April 18-22 1994. [454] O. Grellier and P. Comon, “Blind separation and equalization of a channel with MSK inputs,” in In SPIE Conference on Advanced Algorithms and Architectures for Signal Processing, San Diego (CA), USA, July 19-24 1998, pp. 26–34. [455] O. Grellier and P. Comon, “Performance of blind discrete source separation,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Rhodes, Greece, September 1998, pp. 2061–2064, Elsevier. [456] O. Grellier and P. Comon, “Blind separation of discrete sources,” IEEE Signal Processing Letters, vol. 5, no. 8, pp. 212–214, August 1998. [457] O. Grellier and P. Comon, “Analytical blind discrete source separation,” in Signal Processing VII, Theories and Applications (EUSIPCO’2000), Tamper, Finland, September 2000, Elsevier. [458] O. Grellier, P. Comon, B. Mourrain, and P. Trebuchet, “Analytical blind channel identification,” IEEE Trans. on Signal Processing, vol. 50, no. 9, pp. 2196–2207, 2002.

[459] R. Gribonval, L. Benaroya, E. Vincent, and C. Févotte, “Proposals for performance measurement in source separation,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 763–768. [460] M. Guenach, Receiver design for wideband CDMA communication systems, Ph.D. thesis, Université catholique de Louvain, Belgique, 2002. [461] X. Guyon, Champs aléatoires sur réseau : modélisation, statistique et applications. Techniques stochastiques, MASSON, 1993. [462] T. Gustafsson, U. Lindgren, and H. Sahlin, “Statistical analysis of signal separation method based on second order statistics,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000. [463] T. Gustafsson, U. Lindgren, and H. Sahlin, “Statistical analysis of signal separation method based on second order statistics,” IEEE Trans. on Signal Processing, vol. 49, no. 2, pp. 441–444, February 2001. [464] T. Gustafsson and B. D. Rao, “Statistical analysis of subspace-based estimation of reduced-rank linear regressions,” IEEE Trans. on Signal Processing, vol. 50, no. 1, pp. 151–158, January 2002. [465] M. Habl, C. Bauer, C. Ziegaus, E.W. Lang, and F. Schulmeyer, “Analyzing brain tumor related EEG signals with ICA algorithms,” in First International Conference on Artificial Neural Networks in Medicine and Biology, Goteborg, SWEDEN, May 13-16 2000. [466] W. Hachem, F. Desbouvries, and Ph. Loubaton, “MIMO channel blind identification in the presence of spatially correlated noise,” IEEE Trans. on Signal Processing, vol. 50, no. 3, pp. 651–661, March 2002. [467] D. Hamad, M. Betrouni, P. Biela, and J. G. Postaire, “Neural networks inspection system for glass bottles production: A comparative study,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 12, no. 4, pp. 505–516, 1998. [468] D. Hamad, “Réseaux de neurones pour la classification non-supervisée,” Tech. Rep., Univ. des Sciences et Technologies de Lille, 10 Juillet 1997, Habilitation de diriger des recherches. [469] M. Handa, T. Nagai, and A. Kurematsu, “Frequency domain multi-channel speech separation and its applications,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [470] W. H¨ ardle, Smoothing techniques with implementation in S, Springer-Verlag, 1991. [471] G. H. Hardy, J. E. Littlewood, and G. P´ olya, Inequalities, Cambridge University Press, 1973. [472] S. Harmeling, F. Meinecke, and K.-R. Mueller, “Analysing ICA components by injecting noise,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 149–154. [473] C. Anton-Haro, J. A. R. Fonollosa, and J. R. Fonollosa, “Blind multiuser channel estimation in asynchronous CDMA signals,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 241–246, January 1997. [474] W. A. Harrison, J. S. lim, and E. Singer, “Adaptivenoise cancelation in a fighter cockpit enviromment,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 1984, ICASSP’84, San Diego, USA, 1984. [475] F. Harroy, J. L. Lacoume, and M. A. Lagunas, “A general adaptive algorithm for nongaussian source separation without any constraint,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 1161–1164, Elsevier. [476] F. Harroy and J. L. Lacoume, “Maximum likelihood estimators and cramer-rao bounds in source separation,” Signal Processing, vol. 55, pp. 167–177, 1996. [477] F. Harroy, Séparation de sources non gaussiennes: Performance et robustesse statistique, Ph.D. thesis, INP Grenoble, September 1994. [478] C. Havran, L. Hupet, J. Czyz, J. Lee, L. Vandendorpe, and M. Verleysen, “Independent component analysis for face authentication,” in Knowledge-Based Intelligent Information Engineering Systems & Applied Technologies, Crema, Italy, 16-18 September 2002, pp. 1207–1211, IOS Press. [479] M. H. Hayes, Statistical digital signal processing and modeling, New York, wiley, 1996. [480] S. Haykin, Adaptive filter theory, Prentice Hall, 1991. [481] S. Haykin, Ed., Blind deconvolution, Prentice Hall, 1994. [482] S. Haykin, Neural Networks, Prentice Hall, 1991. [483] S. Haykin, Unsupervised adaptive filtering, vol I, Blind source separation, Wiely, 2000. [484] S. Haykin, Unsupervised adaptive filtering, vol II, Blind deconvolution, Wiely, 2000. [485] L. He and M. Amin, “A dual-mode technique for improved blind equalization for qam signals,” IEEE Signal Processing Letters, vol. 10, no. 2, pp. 29–31, February 2003. [486] J. Hérault and B. Ans, “Réseaux de neurones ` a synapses modifiables: Décodage de messages sensoriels composites par un apprentissage non supervisé et permanent,” C. R. Acad. Sci. Paris, vol. série III, pp. 525–528, 1984.

[487] J. Hérault, C. Jutten, and B. Ans, “Détection de grandeurs primitives dans un message composite par une architecture de calcul neuromimétique en apprentissage non supervisé,” in Actes du Xème colloque GRETSI, Nice, France, 20-24, May 1985, pp. 1017–1022. [488] J. Hérault and C. Jutten, “Space or time adaptive signal processing by neural networks models,” in Intern. Conf. on Neural Networks for Computing, Snowbird (Utah, USA), 1986, pp. 206–211. [489] J. Hérault and C. Jutten, Réseaux neuronaux et traitement du signal, Hermes, Paris, 1994. [490] F. Herrmann and A. K. Nandi, “Blind separation of linear instantaneous mixtures using closed-form estimators,” Signal Processing, vol. 81, pp. 1537–1556, 2001. [491] K. E. Hild, D. Erdogmus, and J. Pr´ıncipe, “Blind source separation using Renyi’s mutual information,” IEEE Signal Processing Letters, vol. 8, no. 6, pp. 174–176, June 2001. [492] K. E. Hild, D. Erdogmus, and J. Pr´ıncipe, “On-line minimum mutual information method for time-varying blind source separation,” in Third International Workshop on Independent Component Analysis and signal Separation (ICA2001), San Diego, California, U.S.A, 9-12 December 2001, pp. 126–131. [493] G. Hinton and T. J. Sejnowski, Eds., Unsupervised learning, MIT Press, 1999. [494] F. Hlawatsch and G. F. Bourdeaux-Bartels, “Linear and quadratic time-frequency signal representations,” IEEE Signal Processing Magazine, pp. 21–67, April 1992. [495] Se Hochreiter and J. Schmidhuber, “Lococode performs nonlinear ICA withoutout knowing the number of sources,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 149–154. [496] P. G. Hoel, Statistique mathématique, Armand Colin, Paris, 1990. [497] O. E. Holland and C. R. Melhuish, “Getting the most from the least: Lessons for the nanoscale from the minimal mobile agents,” in ALIFE V, 1996, pp. 59–66. [498] L. Hong and K. C. Ho, “Identification of digital modulation types using the wavelet transform,” in In Proc. IEEE MILitary COMmunication conference (MILCOM’99), Atlantic City, NJ, USA, Octobre 1999, pp. 427–431. [499] R. A. Horn and Ch. R. Johnson, Matrix analysis, Cambridge University Press, 1985. [500] G. Hory, “A new approach to joint diagonalization,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 151–155. [501] S. Hosseini and C. Jutten, “On the separability of nonlinear mixtures of temporally correlated sources,” IEEE Signal Processing Letters, vol. 10, no. 2, pp. 43–46, February 2003. [502] T. Hoya, Y. Loke, J. A. Chambers, and P. A. Naylor, “Application of the leaky extended LMS (XLMS) algorithm in sterophonic acoustic echo cancellation,” Signal Processing, vol. 64, pp. 87–91, 1998. [503] S. D. Howard and S. Sirianunpiboon, “A robust recursive filter for radar pulse train parameter estimation and tracking,” in Fourth International Symposium on Signal Processing and its Applications (ISSPA’96), Gold Coast, Australia, August 25-30 1996. [504] C. Y. Huang and A. Polydoros, “Likelihood methods for MPSK modulation classification,” IEEE Trans. on Communications, vol. 43, no. 2/3/4, pp. 1493–1504, 1995. [505] J Huang, N. Ohnishi, and N. Sugie, “A biomimetic system for localization and separation of multiple sound sources,” in Proceedings of the 1994 International Symposium on Nonlinear Theory and Its Applications (NOLTA ’94), Hamamatsu, Japan, May 1994, pp. 967–970. [506] J Huang and N. Ohnishi, “Robot with ears : Sound localization and separation,” in Proc. Int. Conf. Signal Processing Applications and Technology (ICSPAT’95), Boston, U.S.A, October 1995, pp. 1697–1702. [507] J Huang, N. Ohnishi, and N. Sugie, “A biomimetic system for localization and separation of multiple sound sources,” IEEE Trans. on Instrumentation and Measurement, vol. 44, no. 3, pp. 733–738, June 1995. [508] J Huang, N. Ohnishi, and N. Sugie, “Sound separation based on perceptual grouping of sound segments,” in Proceedings of the 1995 International Symposium on Nonlinear Theory and Its Applications (NOLTA ’95), Las Vegas, U.S.A, December 1995, pp. 67–72. [509] J. Huang, N. Ohnishi, and N. Sugie, “Building ears for robot: Sound localization and separation,” in The First International Symposium on Artificial Life and Robotics AROB’1, February 1996, pp. 102–106. [510] J. Huang, N. Ohnishi, and N. Sugie, “Auditory spatial processing in reverberant environment,” in Proc. Int. Tech. Conf. Circuits/Systems, Computers and Communications (ITC-CSCC’97), July 1997, pp. 353–356. [511] J. Huang, N. Ohnishi, G. Xiaolan, and N. Sugie, “Echo avoidance and delayed neural inhibition - a model of the precedence effect -,” in Proc. IJCAI-97 Workshop on Computational Auditory Scene Analysis (CASA’97), August 1997. [512] J. Huang, N. Ohnishi, and N. Sugie, “Building ears for robot: Sound localization and separation,” in IEEE-RSJ International Conference on Intelligent Robots and Systems innovative Robotics for Real-World Applications, September 1997, pp. 683–689. [513] J. Huang, N. Ohnishi, and N. Sugie, “Building ears for robots: Sound localization and separation,” Artificial Life and Robotics, vol. 1, no. 4, pp. 157–163, 1997.

[514] J Huang, N. Ohnishi, and N. Sugie, “Sound localization in reverberant environment based on the model of the precedence effect.,” IEEE Trans. on Instrumentation and Measurement, vol. 46, no. 4, pp. 842–846, August 1997. [515] J Huang, N. Ohnishi, and N. Sugie, “Spatial localization of sound sources: Azimuth and elevation estimation,” in IEEE Instrumentation and Measurement Technology Conference, Saint Paul, Minnesota, USA, May 18-21 1998, pp. 330–333. [516] J. Huang, T. Supaongprapa, I Terakura, F. Wang, N. Ohnishi, and N. Sugie, “A model based sound localization system and its application to robot navigation,” Robotics and Autonomous Systems (Elsevier Science), vol. 27, no. 4, pp. 199–209, 1999. [517] J. Huang, N. Ohnishi, X. Guo, and N. Sugie, “Echo avoidance in a computaional model of the precedence effect,” Speech Communication (Elsevier Science), vol. 27, no. 3-4, pp. 223–233, 1999. [518] Y. Huang, J. Benesty, and J. Chen, “Optimal step size of the adaptive multichannel LMS algorithm for blind SIMO identification,” IEEE Signal Processing Letters, vol. 12, no. 3, pp. 173–176, March 2005. [519] R. Huez, D. Nuzillard, and A. Billat, “Denoising using blind source separation for pyroelectric sensors,” EURASIP Journal on Applied Signal Processing, , no. 1, pp. 53–65, 2001. [520] A. Hyv¨ aerinen and E. Oja, “A fast fixed point algorithm for independent component analysis,” Neural computation, vol. 9, pp. 1483–1492, 1997. [521] A. Hyv¨ aerinen, “Indenpent component analysis in the presence of gaussian noise by maximizing joint likelihood,” NeuroComputating, vol. 22, pp. 49–67, 1998. [522] A. Hyv¨ arinen and E. Oja, “Independent componenet analysis by general nonlinear hebbian-like learning rules,” Signal Processing, vol. 64, pp. 301–313, 1998. [523] A. Hyv¨ arinen, J. S¨ arel¨ a, and R. Vig´ ario, “Spikes and bumpes: artefacts generated by independent component analysis with insufficient sample size,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 425–429. [524] A. Hyv¨ arinen and P. Pajunen, “Nonlinear independent componenet analysis: Existance and uniqueness results,” Neural Networks, vol. 12, pp. 429–439, 1999. [525] A. Hyv¨ arinen, “Fast and robust fixed-point algorithms for independent component analysis,” IEEE Trans. on Neural Networks, vol. 10, no. 3, pp. 626–634, May 2000. [526] A. Hyv¨ arinen and E. Oja, “Independent componenet analysis: algorithms and applications,” Neural Networks, vol. 13, pp. 411–430, 2000. [527] A. Hyv¨ arinen, J. Karhunen, and E. Oja, Independent component analysis, John Wiley & Sons, 2001. [528] A. Hyv¨ arinen, P. O. Hoyer, and J. Hurri, “Extensions of ICA as models of natural images and visual processing,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 963–974. [529] M. Ibnkahla, “Statistical analysis of neural network modeling and identification of nonlinear systems with memory,” IEEE Trans. on Signal Processing, vol. 50, no. 6, pp. 1508–1517, June 2002. [530] J. Igual, L. Vergara, A. Camacho, and R. Miralles, “Independent component analyses with prior information about the mixing matrix,” NeuroComputing, , no. 50, pp. 419–438, 2003. [531] B. C. Ihm and D. J. Park, “Blind separation of sources using higher-order cumulants,” Signal Processing, vol. 73, pp. 267–276, 1999. [532] A. Iline, H. Valpola, and E. Oja., “State changes by nonlinear blind source separation,” in Third International Workshop on Independent Component Analysis and signal Separation (ICA2001), San Diego, California, U.S.A, 9-12 December 2001, pp. 710–715. [533] S. Shiro Ikeda and K. Toyama, “ICA for noisy neurobiological data,” in In Proceedings of the International Joint Conference of Neural Networks (IJCNN2000), Como, Italy, July 2000. [534] M. Ikram and D. Morgan, “A multiresolution approach to blind separation of speech signals in a reverberant environment,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [535] Y. Inouye, “Modeling of multichannel time series and extrapolation of matrix-valued autocorrelation sequences,” IEEE Trans. on Acoustics, Speech and Signal Processing, vol. ASSP-31, no. 1, pp. 45–55, 1983. [536] Y. Inouye and T. Umeda, “Parameter estimation multichannel ARMA processes using fourth-order cumulants,” in International Siganl Processing Workshop on Higher Order Statistics, Chamrousse, France, July 1991, pp. 249–252. [537] Y. Inouye, K. Hirano, and B. Sako, “Blind identification of linear MIMO systems driven by colored inputs,” IEEE Trans. on Signal Processing, vol. 45, pp. 1543–1550, 1997. [538] Y. Inouye and K. Hirano, “Cumulant-based blind identification of linear multi-input-multi-output systems driven by colored inputs,” IEEE Trans. on Signal Processing, vol. 45, no. 6, pp. 1543–1552, 1997. [539] Y. Inouye and T. Sato, “Iterative algorithm based on multistage criteria for multichannel blind deconvolution,” IEEE Trans. on Signal Processing, vol. 47, no. 6, pp. 1759–1764, 1999. [540] Y. Inouye and K. Tanebe, “Super-exponential algorithms for multichannel blind deconvolution,” IEEE Trans. on Signal Processing, vol. 48, no. 3, pp. 881–888, 2000.

[541] C. Ioana, Contribution ` a la caractérisation des structures Temps-Fréquence non-linéaires, Ph.D. thesis, Université de Bretagne Occidentale, Septembre 2003. [542] R. Jackson, D. Pycock, M. Xu, M. Knowles, and S. Harman, “Multi-scale event detection and period extraction,” in IEE Colloquium on Time-Scale and Time-Frequency Analysis and applications, London, UK, February 2000. [543] M. Jafari, H. Seah, and J. Chambers, “A combined kalman filter and natural gradient algorithm approach for blind separation of binary distributed sources in time-varying channels,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [544] P. Jaffard, Statistique, Masson, Paris, 1990. [545] g. J. Jang, T. W. Lee, and Y. H. Oh, “Single channel signal separation using time-domain basis functions,” IEEE Signal Processing Letters, vol. 10, no. 6, pp. 168–171, Jun 2003. [546] U. G. Jani, E. M. Dowling, R. M. Golden, and Z. Wang, “Multiuser interference suppression using block shanno constant modulus algorithm,” IEEE Trans. on Signal Processing, vol. 48, no. 5, pp. 1503–1506, May 2000. [547] L. Jaulin, Solution global et garantie de problèmes ensemblistes, Ph.D. thesis, Université de Paris XI, Orsay, France, Février 1994. [548] L. Jaulin, Le calcul ensembliste par analyse par intervalles et ses applications, Ph.D. thesis, Université de Paris XI, Orsay, France, Février 2000. [549] A. Jefremov and B. Kleijn, “Sline-based continuous-time pitch estimation,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2002, ICASSP 2002, Orlando, Florida, U.S.A, 13-17 May 2002. [550] B. Jelonnek and K. D. Kammeyer, “Eigenvector algorithm for blind equalization,” in IEEE Signal Processing Workshop on Higher-Order Statistics, South Lac Tahoe, USA (CA), June 1993, pp. 19–23. [551] B. Jelonnek and K. D. Kammeyer, “A closed form solution to blind equalization,” Signal Processing, 1994. [552] B. Jelonnek and K. D. Kammeyer, “A closed form solution to blind equalization,” EURASIP Signal Processing, vol. 36, no. 3, pp. 251–259, April 1997, Special issue on Higher order Statistics. [553] B. Jelonnek, D. Boss, and K. D. Kammeyer, “Generalized eigenvector algorithm for blind equalization,” Signal Processing, vol. 61, pp. 237–264, 1997. [554] M. Joho, R. Lambert, and H. Mathis, “Elementary cost functions for blind separation of non-stationary source signals,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001, pp. 2793–2796. [555] J.-M. Jot, L. Cerveau, and O. Warusfel, “Analysis and synthesis of room reverberation based on a statistical timefrequency model,” 1997. [556] A. Jourjine, S. Rickard, and O. Yilmaz, “Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 2985–2988. [557] W. Jun, “Wideband blind identification and separation of independent sources,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 2077–2080, Elsevier. [558] T. P. Jung, C. Humphries, T. w. Lee, S. Makeig, M. J. McKeown, V. Iragui, and T. J. Sejnowski, “Extended ICA removes artifacts from electroencephalographic recordings,” in Advances in Neural Information Processing Systems, Michael I. Jordan, Michael J. Kearns, and Sara A. Solla, Eds. 1998, vol. 10, The MIT Press. [559] T. Jung, C. Humphries, M. Lee, V. Iragui, S. Makeig, and T. Sejnowski, “Removing electroencephalographic artifacts: Comparison between ICA and PCA,” in IEEE International Workshop on Neural Networks for Signal Processing, 1998, pp. 63–72. [560] . Jung, C. Humphries, T. Lee, M. McKeown, V. Iragui, S. Makeig, and T. Sejnowski, “Removing electroencephalographic artifcats by blind source separation,” Psychophysiology, vol. 37, pp. 167–178, March 2000. [561] C. Jutten, Calcul neuro-mimétique et traitement du signal: Analyse en composantes indépendantes, Ph.D. thesis, UJF-INP Grenoble, 1987. [562] C. Jutten and J. Hérault, “Une solution neuromimétique du problème de séparation de sources,” Traitement du signal, vol. 5, no. 6, pp. 389–403, 1988. [563] C. Jutten and J. Hérault, “Independent components analysis versus principal components analysis,” in Signal Processing IV, Theories and Applications (EUSIPCO’88), J. L. Lacoume, A. Chéhikian, N. Martin, and J. Malbos, Eds., Grenoble, France, September 1988, pp. 643–646, Elsevier. [564] C. Jutten and J. Hérault, “Analog implementation of a neuromimetic auto-adaptive algorithm,” in Neuro-Computing: Algorithms, architectures and applications, J. Hérault and F. Fogelman-Soulié, Eds., Les Arcs, France, February 27-March 3 1989, pp. 145–152, Springer Verlag, NATO ASI Series, Series F, Vol 68. [565] C. Jutten and J. Hérault, “Blind separation of sources, Part I: An adaptive algorithm based on a neuromimetic architecture,” Signal Processing, vol. 24, no. 1, pp. 1–10, 1991. [566] C. Jutten, L. Nguyen Thi, E. Dijkstra, E. Vittoz, and Caelen J., “Blind separation of sources: An algorithm for separation of convolutive mixtures,” in International Signal Processing Workshop on Higher Order Statistics, Chamrousse, France, July 1991, pp. 273–276.

[567] C. Jutten, A. Guerin, and Nguyen Thi L., “Adaptive optimization of neural algorithms,” in International work-conference on Artificial and Natural Networks, IWANN’91, Granada, Spain, 17-19 September 1991, pp. 54–61. [568] C. Jutten, L. Nguyen Thi, and J. Hérault, “Nouveaux algorithmes de séparation de sources,” in Con. satellite du cong. Europée de mathématiques: Aspects théoriques des reseaux de neurones, Paris, France, July 1992. [569] C. Jutten and J. F. Cardoso, “Separation of sources: Really blind ?,” in International symposium on nonlinear theory and its applications, nolta’95, Las Vegas, Nevada, U. S. A., December 1995, pp. 79–84. [570] C. Jutten, “Introduction ` a la séparation de sources,” in International symposium on nonlinear theory and its applications, nolta’95, Las Vegas, Nevada, U. S. A., December 1995, pp. 79–84. [571] J. Christian and A. Taleb, “Source separation: From dusk till dawn,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000. [572] C. Jutten and J. Karhunen, “Advances in nonlinear blind source separation,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 245–256. [573] C. Jutten, M. Babaie-Zadeh, and S. Hosseini, “Three easy ways for separating nonlinear mixtures?,” Signal Processing, vol. 84, pp. 217–229, 2004. [574] A. Kab´ an and M. Girolami, “A dynamic probabilistic model to visualise topic evolution in text streams,” Journal of Intelligent Information Systems, vol. 18, no. 2, pp. 107–125, 2002, Special Issue on Automated Text Categorization. [575] A.M. Kagan, Y.V. Linnik, and C.R. Rao, Characterization problems in mathematics statistics, John Wiley & Sons, 1973. [576] T. Kailath, Linear systems, Prentice Hall, 1980. [577] N. Kalouptsidis, P. Koukoulas, and V. J. Mathews, “Blind identification of bilinear systems,” IEEE Trans. on Signal Processing, vol. 51, no. 2, pp. 484–499, February 2003. [578] H. K¨ alvi¨ ainen, E. Oja, and L. Xu, “Motion detection using randomized hough transform,” in 7th Scandinavian Conference on Image Analysis, Aalborg, Denemark, August 1995, pp. 72–79. [579] E. R. Kandel, J. H. Schwartz, and T. M. Jessel, Eds., The Principles of Neural Science, Prentice Hall, 3rd edition, 1991. [580] Y. Kaneda and J. Ohga, “Adaptive microphone-array system for noise reduction,” IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. ASSP-34, no. 6, pp. 1391–1400, December 1986. [581] A. Kannan and V. U. Reddy, “Maximum likelihood estimation of constellation vectors for blind separation of co-channel BPSK signals and its performance analysis,” IEEE Trans. on Signal Processing, vol. 45, no. 7, pp. 1736–1741, July 1997. [582] A. Kardec Barros, A. Mansour, and N. Ohnishi, “Adaptive blind elimination of artifacts in ECG signals,” in International ICSC Workshop on Independence & Artificial Neural Networks 98, Tenerife-Spain, 11-13 February 1998. [583] A. Kardec Barros, A. Mansour, and N. Ohnishi, “Removing artifacts from ECG signals using independent components analysis,” NeuroComputing, vol. 22, pp. 173–186, 1999. [584] A. Kardec Barros, T. Rutkowski, F. Itakura., A. Mansour, and N. Ohnishi, “Estimation of speech embedded in a reverberant environment with multiple sources of noise,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [585] J. karhunen, E. Oja, L. Wang, R. Vigario, and J. Joutsensalo, “A class of neural networks for independent componenet analysis,” Tech. Rep., Helsiniki University of Technology, Faculty of information Technology, Lab of Comuter and Information Science in Finland, October 1995. [586] J. karhunen and J. Joutsensalo, “Generalizations of principal component analysis, optimization problems, and neural networks,” Neural Networks, vol. 8, no. 4, pp. 549–562, 1995. [587] J. karhunen, L. Wang, and J. Joutsensalo, “Neural estimation of basis vectors in independent component analysis,” in International Conference on Artificial Neural Networks ICANN’95, Paris, France, 9-13 Octobre 1995. [588] J. karhunen, L. Wang, and R. Vigario, “Nonlinear PCA type approaches for source separation and independent component analysis,” in International Conference on Neural Networks ICNN’95, Perth, Australia, 27 November - 1 December 1995. [589] J. Karhunen, “Neural approaches to independent component analysis and source separation,” in ESANN’96, European Symposium on Artificial Neural Networks, Bruges, Belgium, April 1996, pp. 249–266. [590] J. Karhunen, P. Pajunen, and E. Oja, “The nonlinear PCA criterion in blind source separation: Relations with other applications,” Neurocomputing, , no. 22, pp. 5–20, 1998. [591] J. Karvanen and V. Koivunen, “Blind separation methods based on Pearson system and its extensions,” Signal Processing, , no. 82, pp. 663–673, 2002. [592] M. Kawakatsu, “Application of ICA to MEG noise reduction,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 535–541. [593] M. Kawamoto, K. Matsuoka, and M. Oya, “Blind separation of sources using temporal correlation of the observed signals,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E80-A, no. 4, pp. 111–116, April 1997. [594] M. Kawamoto, K. Matsuoka, and N. Ohnishi, “Blind signal separation of convolved non-stationary signals,” in Proc. International Symposium on Nonlinear Theory and its Applications, Hawaii, 1998, pp. 1001–1004.

[595] M. Kawamoto, A. Kardec Barros, and N. Ohnishi, “A neural network for blind separation of convolved non-stationary signals,” in International ICSC Workshop on Independence & Artificial Neural Networks 98, Tenerife-Spain, 11-13 February 1998. [596] M. Kawamoto, K. Matsuoka, and N. Ohnishi, “A method of blind separation for convolved non-stationary signals,” Neurocomputing, , no. 22, pp. 157–171, 1998. [597] M. Kawamoto, A. Kardec Barros, A. Mansour, K. Matsuoka, and N. Ohnishi, “Blind separation for convolutive mixtures of non-stationary signals.,” in Fifth International Conference on Neural Information Processing, S. Usui and T. Omori, Eds., Kitakyushu, Japan, 21-23 October 1998, pp. 743–746. [598] M. Kawamoto, A. Kardec Barros, A. Mansour, K. Matsuoka, and N. Ohnishi, “Real world blind separation of convolved non-stationary signals.,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 347–352. [599] M. Kawamoto, A. Kardec Barros, A. Mansour, K. Matsuoka, and N. Ohnishi, “Blind signal separation for convolved non-stationary signals,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. J82-A, no. 8, pp. 1320–1328, August 1999, Japanese paper. [600] M. Kawamoto, A. Kardec Barros, A. Mansour, K. Matsuoka, and N. Ohnishi, “Blind signal separation for convolved non-stationary signals,” Electronics and Communications in Japan Part 3, 2000, Published by John Wiley & Sons, Inc. [601] M. Kawamoto, Y. Inouye, and R. Liu, “Blind deconvolution algorithms for MIMO-FIR channels driven by white but fourth-order colored signals,” in 34th Annual Asilomar Conference on Signals, Systems, and Comupters, Pacific Grove, California, U.S.A, September 2000, vol. 2, pp. 1202–1206. [602] M. Kawamoto, Y. Inouye, A. Mansour, and R. Liu, “Blind deconvolution algorithms for MIMO-FIR systems driven by fourth-order colored signals,,” in Third International Workshop on Independent Component Analysis and signal Separation (ICA2001), San Diego, California, U.S.A, 9-12 December 2001, pp. 692–697. [603] M. Kawamoto, Y. Inouye, A. Mansour, and R. Liu, “A deflation algorithm for the blind deconvolution of MIMO-FIR channels driven by fourth-order colored signals,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2002, ICASSP 2002, Orlando, Florida, U.S.A, 13-17 May 2002, pp. 1651–1654. [604] M. Kawamoto and Y. Inouye, “A deflation algorithm for the blind source-factor separation of MIMO-FIR channels driven by colored sources,” IEEE Signal Processing Letters, vol. 10, no. 11, pp. 343, November 2003. [605] S. Kay, “Can detectability be improved by adding noise?,” IEEE Signal Processing Letters, vol. 7, no. 1, pp. 8–10, January 2000. [606] Kayhan, “Representation and analysis of complex chirp signals,” Signal Processing, vol. 66, pp. 111–116, 1998. [607] A. V. Keerthi and J. J. Shynk, “Separation of cochannel signals in TDMA mobile radio,” IEEE Trans. on Signal Processing, vol. 46, no. 10, pp. 2684–2697, October 1998. [608] M. Kendall and A. Stuart, The advanced theory of statistics: Distribution theory, Charles Griffin & Company Limited, 1961, volume 1. [609] M. Kendall and A. Stuart, The advanced theory of statistics: Inference and relationship, Charles Griffin & Company Limited, 1961, volume 1. [610] M. Kendall and A. Stuart, The advanced theory of statistics: Design and analysis, and time-series, Charles Griffin & Company Limited, 1961, volume 1. [611] E. KERHERVE, W. AKMOUCHE, and A. QUINQUIS, “Wavelet and noise reduction : Application to the time features estimation for ofdm signals,” in Proceedings of ICSPAT99, Orlando (fl), USA, November 1999. [612] E. KERHERVE, W. AKMOUCHE, and A. QUINQUIS, “Ofdm bandwidth estimation using wavelet decomposition,” in Proceedings of CSNDSP 2000, Pool, UK, July 2000. [613] E. KERHERVE, W. AKMOUCHE, and A. QUINQUIS, “Ofdm bandwidth estimation : Application of the wavelet decomposition,” in Proceedings of EUROCOMM 2000, Munich, Germany, May 2000. [614] H. Ketterer, F. Jondral, and A. H. Costa, “Classification of modulation modes using time-frequency methods,” in Proceedings of International Conference on Speech and Signal Processing 1999, ICASSP 1999, Arizona, USA, March 1999. [615] E. T. Kofler and C. T. Leondes, “New approach to the pulse train de-interleaving problem,” INT. J. Systems SCI., vol. 20, no. 12, pp. 2663–2671, 1989. [616] C. Komninakis, C. Fragouli, A. H. Sayed, and R. D. Wesel, “Multi-input multi-output fading channel tracking and equalization using kalman estimation,” IEEE Trans. on Signal Processing, vol. 50, no. 5, pp. 1065–1075, May 2002. [617] I. Kopriva and A. Persin, “Blind separation of optical tracker responses into independent components discriminates optical sources,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 31–36. [618] I. Kopriva, Q. Du, H. Szu, and W. Wsaylkiwskyj, “Independent component analysis approach to image sharping in the presence of atmospheric turbulence,” Optics Communications, vol. 233, pp. 7–14, 2004. [619] S. Kotz and N. L. Johnson, Encyclopedia of statistical sciences, University of Amesterdam, 1993. [620] P. Koukoulas, J. Malliaros, and N. Kalouptsidis, “Efficient algorithms for Volterra system identification using crosscumulants,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994.

[621] A. Koutras, E. Dermatas, and G. Kokkinakis, “Blind signal separation and speech recognition in the frequency domain,” in 6th International Conference on Electronics, Circuits and Systems, Pafos, Cyprus, Jun 1999, pp. 427–430. [622] A. Koutras, E. Dermatas, and G. Kokkinakis, “Blind speech separation of moving speakers in real reverberant environments,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 1133–1136. [623] M. Kristensson and B. Ottersten, “A statistical approach to subspace based blind identification,” IEEE Trans. on Signal Processing, vol. 46, no. 6, pp. 1612–1623, June 1998. [624] M. Krob and M. Benidir, “Fonction de contraste pour l’identification aveugle d’un modéle linéaire quadratique,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 101–104. [625] M. Krob, Identification aveugle de modèles non linéaires ` a l’aide de statistiques d’ordre supérieur, Ph.D. thesis, Université de Paris-Sud, 1994. [626] B. J. A. Kr¨ ose and P. Patrick Van Der Smagt, An introduction to neural networks, University of Amesterdam, 1993. [627] J. L. Lacoume and P. Ruiz, “Sources identification: A solution based on cumulants,” in IEEE ASSP WorkshopV, Mineapolis, USA, August 1988. [628] J. L. Lacoume and M. Gaeta, “The general source separation problem,” in Fifth ASSP Workshop on estimation and modeling, Rochester New-York, October 1990, pp. 154–158. [629] J. L. Lacoume and M. Gaeta, “Complex random variables: A tensorial approach,” in International Workshop on High Order Statistics, J. L. Lacoume, M. A. Lagunas, and C. L. Nikias, Eds., Chamrousse, France, July 1991. [630] J. L. Lacoume, M. Gaeta, and W. Kofman, “Source separation using higher order statistics,” JATP, vol. 54, no. 10, pp. 1217–1226, 1992. [631] Lacoume J. L., P. Comon, C. Servière, M. Boumahdi, V. Capdevielle, and N. Thirion, “Statistiques d’ordres supérieurs pour le traitement du signal (illustrations),” in Traitement du signal-Développements Récents, Les Houches, France, August-September 1993. [632] J. L. Lacoume and F. Harroy, “Performances in blind source separation,” in Proc. IEEE-ATHOS Workshop on HigherOrder Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 25–29. [633] J. L. Lacoume, P. O. Amblard, and P. Comon, Statistiques d’ordre supérieur pour le traitement du signal, Mason, Paris, 1997. [634] J.-L. Lacoume, “A survey of source separation,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 1–5. [635] B. Laheld and J. F. Cardoso, “Séparation adaptative de sources en aveugle. implantation complexe sans contraintes,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, 13-16 September 1993, pp. 329–332. [636] B. Laheld and J. F. Cardoso, “Adaptive source separation with uniform performance,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 1–4, Elsevier. [637] B. Laheld, Séparation auto-adaptative de sources. Implantations et performances, Ph.D. thesis, ENST Paris, 1994. [638] W. K. lai and P. C. Ching, “A novel blind estimation algorithm,” IEEE Trans. on Signal Processing, vol. 45, no. 7, pp. 1763–1769, July 1997. [639] H. Lappalainen, “Ensemble learning for independenmt component analysis,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 7–12. [640] I. Landau, Identification et commande de systèmes, Hermès, seconde édition, 1993. [641] P. Lander, E. J. Berbari, and R. Lazzara, “Optimal filtering and quality of signal-averged ECG,” circulation, vol. 91, no. 5, pp. 1495–1505, 1995. [642] P. Lascaux and R. Théodor, Analyse numérique matricielle appliquée ` a l’art de l’ingénieur, Masson, Paris and Milan and Barcelone, 1994, Tome 1. [643] P. Lascaux and R. Théodor, Analyse numérique matricielle appliquée ` a l’art de l’ingénieur, Masson, Paris and Milan and Barcelone, 1994, Tome 2. [644] C. Latombe, Détection et caractérisation des signaux ` a plusieurs composantes ` a partir de la matrice interspectrale, Ph.D. thesis, INPG Grenoble, 1983. [645] M. Lavielle, E. Moulines, and J. F. Cardoso, “On a stochastic approximation version of the EM algorithm,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 61–63. [646] P. Lazar and D. Schwartz, Eléments de probabilités et statistique, Flammarion Médcine-sciences, Paris, 1988, 4th edition. [647] Y. Le Cun, “A learning scheme for assymetric threshold network,” in Proceedings of COGNITICA’85, Paris, France, 1985, pp. 599–604. [648] Ch. Ch. Lee and J. H. Lee, “An efficient method for blind digital separation of array data,” Signal Processing, , no. 77, pp. 229–234, 1999.

[649] K. S. M. Lee, M. J. Rowe, and V. Krishnamurthy, “Pulse train deinterleaving: Algorithms and cost criteria,” in Proceedings of International Conference on Speech and Signal Processing 1999, ICASSP 1999, Arizona, USA, March 15-19 1999, pp. 2475–2478. [650] T. W. Lee, A. J. Bell, and R. H. Lambert, “Blind source separation of nonlinear mixing models,” in Advances in Neural Information Processing Systems, Michael C. Mozer, Michael I. Jordan, and Thomas Petsche, Eds. 1997, vol. 9, pp. 758–764, The MIT Press. [651] T. W. Lee, A. J. Bell, and R. Orglmeister, “Blind source separation of real world signals,” in Proceedings of International Conference on Neural Networks, Houston, June 1997. [652] T. W. Lee, A. J. Bell, and R. H. Lambert, “Blind separation of delayed and convolved sources,” in Advances in Neural Information Processing Systems 9, 1997, pp. 758–764. [653] T. W. Lee, Independent component analysis: Theory and Applications, Kluwer Academic Publishers, 1998. [654] T. W. Lee, M. Girolami, and T. J. Sejnowski, “Independent component analysis for mixed sub-gaussian and supergaussian sources,” Neural Computation, vol. 11, no. 2, pp. 417–442, 1999. [655] T. W. Lee, M. S. Lewicki, M. Girolami, and T. J. Sejnowski, “Blind source separation of more sources than mixtures using overcomplete representations,” IEEE Signal Processing Letters, vol. 6, no. 4, pp. 87–90, April 1999. [656] T. W. Lee, M. Girolami, A Bell, and T. J. Sejnowski, “A unified information theoritic framework for independent component analysis,” Computers and Mathematics with Applications, vol. 39, pp. 1–21, 2000. [657] T. W. Lee, M. Girolami, A Bell, and T. J. Sejnowski, “A unified information theoritic framework for independent component analysis,” International Journal on Mathematical and Computer Modelling, vol. 38, pp. 1–21, 2000. [658] R. Le Bouquin, Traitemnet pour la reduction du bruit sur la parole application aux communications radio-mobiles., Ph.D. thesis, L’université de Rennes I, July 1991. [659] D. Le Guen and A. Mansour, “Automatic recognition algorithm for digitally modulated signals,” in IASTED International Conference on Signal Processing, Pattern Recognition, and Applications (SPPRA 2002), Crete, Greece, 25-28 June 2002. [660] D. Le Guen and A. Mansour, “Automatic recognition algorithm for digitally modulated signals,” in 6th Baiona workshop on signal processing in communications, Baiona, Spain, 25-28 June 2003. [661] J. Lelong-Ferrand and J. M. Arnaudiès, Algèbre, Dunod, Paris, 1990. [662] L. W. Lemley, “Electronic warefare innovations,” Naval Engineers Journal, vol. 108, no. 5, pp. 29–36, September 1996. [663] A. Le Pladec, G. Burel, and Ch. Jacquemont, “Synthèse et implementation de filtres ` a bande passante variable ` a faible complexité ` a l’aide des bancs de filtres,” Traitement du signal, vol. 19, no. 3, pp. 217–233, 2002. [664] J. Le Roux, D. Rossille, C. Huet, and J. L. Peyre, “Prise en compte de la stationnarité dans les algorithmes d’analyse spectrale et d’identification fondés sur la mesure des corrélations et spectres d’ordre supérieur,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 81–84. [665] M. Lewicki and T. J. Sejnowski, “Learning non-linear overcomplete representations for efficient coding,” Advances in neural Information Processing Systems, vol. 10, pp. 815–821, 1998. [666] M. Lewicki and T. J. Sejnowski, “Learning overcomplete representations,” Neural Computation, vol. 12, no. 2, pp. 337–365, 2000. [667] H. Li and D. Zoltowski, “Blind equalization in antenna array CDMA signals,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 161–171, January 1997. [668] Q. Li, E. W. Bai, and Y. Ye, “Blind channel equalization and ǫ-approximation algorithms,” IEEE Trans. on Signal Processing, vol. 49, no. 11, pp. 2823–2831, November 2001. [669] Q. Li, E. W. Bai, and Z. Ding, “Blind source separation of signals with known alphabets using ǫ-approximation algorithms,” IEEE Trans. on Signal Processing, vol. 51, no. 1, pp. 1–10, January 2003. [670] S. Li and T. J. Sejnowski, “Adaptive separation of mixed brod-band sound sources with delays by a beamforming Hérault-Jutten network,” IEEE journal of oceanic engineering, vol. 20, no. 1, pp. 73–79, January 1995. [671] T. Li and N. D. Sidiropoulos, “Blind digital signal separation using successive interface cancellation iterative least squares,” IEEE Trans. on Signal Processing, vol. 48, no. 11, pp. 3146–3152, November 2000. [672] T. Li, J. Wang, and J. M. Zurada, “Blind extraction of singularly mixed sources signals,” IEEE Trans. on Neural Networks, vol. 11, no. 6, pp. 1413–1422, November 2000. [673] X. Lil and H. H. Fan, “Direct blind multiuser detection for CDMA in multipath without channel estimation,” IEEE Trans. on Signal Processing, vol. 49, no. 1, pp. 63–73, January 2001. [674] Y. Li and K. J. Ray Liu, “Adaptive blind source separation and equalization for multiple-input/multiple-output systems,” IEEE Trans. on Information Theory, vol. 44, no. 7, pp. 2864–2876, November 1998. [675] Y. Li, J. Wang, and J. M. Zurada, “Blind extraction of singularly mixed source signals,” IEEE Trans. on Neural Networks, vol. 11, no. 6, pp. 1413–1422, 2002. [676] Y. Li and J. Wang, “Sequential blind extraction of instantaneously mixed sources,” IEEE Trans. on Signal Processing, vol. 50, no. 5, pp. 997–1006, May 2002.

[677] Y. Li, A. Cichocki, and S. Amari, “Sparse component analysis for blind source separation with less sensors than sources,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 89–94. [678] A. P. Liavas, A. R. Regalia, and J. P. Delams, “Robustness of least-squares and subspace methods for blind channel identification / equalization with respect to effective channel undermodeling/overmodeling,” IEEE Trans. on Signal Processing, vol. 47, no. 6, pp. 1636–1644, June 1999. [679] J. S. Lim and A. V. Oppenheim, “All-pole modeling of degraded speech,” IEEE trans. on Acoustics, Speech, and Signal Processing, vol. ASSP-26, no. 3, pp. 197–210, June 1978. [680] J.K. Lin and J.D. Cowan, “Faithful representation of separable input distributions,” Neural Computation, vol. 9, pp. 1305–1320, 1997. [681] U. Lindgren, H. Sahlin, and H. Broman, “Source separation using second order statistics,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 699–702, Elsevier. [682] U. Lindgren and H. Broman, “Source separation using a criterion based on second-order statistics,” IEEE trans. on Signal Processing, vol. 46, no. 7, pp. 1837–1850, July 1998. [683] H. liu and M. D. Zoltowski, “Blind equalization in antenna array CDMA systems,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 161–171, January 1997. [684] R. Liu and P. Comon, “Wide-sense polynomial equalizers in digital communications,” in 18eme Colloque Gretsi, Toulouse, 10-13 Sept 2001. [685] X. Liu and J. Hérault, “Color image processing by a neural network model,” in INNC Proceedings, Paris, France, July 1990, pp. 3–6. [686] X. Liu, Analyse d’images couleur en composantes indpendantes par rseau de neurones, Ph.D. thesis, INP Grenoble, 1991. [687] T. H. Liu and J. M. Mendel, “A subspace-based direction finding algorithm using fractional lower order statistics,” IEEE Trans. on Signal Processing, vol. 49, no. 8, pp. 1605–1613, August 2001. [688] Z. Liu, Y. Xin, and G. Giannakis, “Space time frequency coded OFDM over frequency selective fading channels,” IEEE Trans. on Signal Processing, vol. 50, no. 10, pp. 2465–2477, October 2002. [689] L. Ljung, System identification - Theory for the user, Prentice Hall, 1987. [690] A. Logothetis, V. Krishnamurthy, and V. Poor, “Estimation of 1-bit quantized time-series with markov regime,” Signal Processing, vol. 58, pp. 273–292, 1997. [691] A. Logothetis and V. Krishnamurthy, “An interval-amplitude algorithm for deinterleaving stochastic pulse train sources,” IEEE Trans. on Signal Processing, vol. 46, no. 5, pp. 1344–1350, May 1998. [692] P. J. Loughlin and K. L. Davidson, “Instantaneous kurtosis,” IEEE Signal Processing Letters, vol. 7, no. 6, pp. 156–159, June 2000. [693] D. G. Luenberger, Introduction to linear and nonlinear programming, Addison-Wesley Publishing Company, 1973. [694] O. Macchi and E. Moreau, “Self-adaptive source separation by direct and recursive networks,” in International Conference on Digital Signal Processing (DSP’93), Limasol, Cyprus, May 1993, pp. 1154–1159. [695] O. Macchi and E. Moreau, “Self-adaptive source separation using correlated signals and cross-cumulants,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [696] O. Macchi, ,” Part of Digital Signal Processing In Telecommunications edited by A. R. Figueiras-Vidal. [697] O. Macchi and E. Moreau, “Self-adaptive source separation, part I: Convergence analysis of a direct linear neural network controled by the Hérault-Jutten algorithm,” IEEE Trans. on Signal Processing, vol. 45, no. 4, pp. 918–925, April 1997. [698] O. Macchi and E. Moreau, “Adaptive unsupervised separation of discrete sources,” Signal Processing, vol. 73, pp. 49–66, 1999. [699] U. Madhow, “Blind adaptive interference suppression for the near-far resistant acquisition and demodulation of directsequence CDMA signals,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 124–136, January 1997. [700] S. Makeig, A. J. Bell, T-P. Jung, J. Terrence, and T. J. Sejnowski, “Independent component analysis of ElectroEncephaloGraphic data,” Advances in Neural Information Processing Systems, vol. 8, pp. 145–151, 1996, MIT Press Cambridge. [701] J. Makhoul, “Linear prediction: A tutorial review,” Proceedings of the IEEE, vol. 63, no. 4, pp. 561–580, Avril 1975. [702] A. Makovec and G. Ramponi, “High-order moments for texture segmentation in presence of noise,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [703] Z. Malouche, O. Macchi, and E. Moreau, “Séparation adaptative de sources binaires ` a l’aide d’un réseau de neurones non linéaires bouclés,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 305–309. [704] Z. Malouche and O. Macchi, “Unsupervised separation of discrete sources with a combined extended anti-hebbian adaptation,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 1267–1270, Elsevier. [705] A. Mansour and C. Jutten, “Fourth order criteria for blind separation of sources,” IEEE Trans. on Signal Processing, vol. 43, no. 8, pp. 2022–2025, August 1995.

[706] A. Mansour and C. Jutten, “A simple cost function for instantaneous and convolutive sources separation,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 301–304. [707] A. Mansour and C. Jutten, “A direct solution for blind separation of sources,” IEEE Trans. on Signal Processing, vol. 44, no. 3, pp. 746–748, March 1996. [708] A. Mansour, C. Jutten, and Ph. Loubaton, “Subspace method for blind separation of sources and for a convolutive mixture model,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 2081–2084, Elsevier. [709] A. Mansour, Contributions ` a la séparation de sources, Ph.D. thesis, INPG Grenoble, 12-January 1997. [710] A. Mansour, C. Jutten, and Ph. Loubaton, “Robustesse des hypothèses dans une méthode sous-espace pour la séparation de sources,” in Actes du XVIème colloque GRETSI, Grenoble, France, September 1997, pp. 111–114. [711] A. Mansour, A. Kardec Barros, and N. Ohnishi, “Subspace adaptive algorithm for blind separation of convolutive mixtures by conjugate gradient method,” in The First International Conference and Exhibition Digital Signal Processing (DSP’98), Moscow, Russia, June 30-July 3 1998, pp. I–252–I–260. [712] A. Mansour, C. Jutten, and N. Ohnishi, “Kurtosis: Definition and properties,” in International Conference on Multisource-Multisensor Information Fusion, H. R. Arabnia and D. D. Zhu, Eds., Las Vegas, USA, 6-9 July 1998, pp. 40–46. [713] A. Mansour, A. Kardec Barros, M. Kawamoto, and N. Ohnishi, “A fast algorithm for blind separation of sources based on the cross-cumulant and levenberg-marquardt method.,” in Fourth International Conference on Signal Processing (ICSP’98), Y. Baozong and T. Xiaofang, Eds., Beijing, China, 12-16 October 1998, pp. 323–326. [714] A. Mansour, A. Kardec Barros, and N. Ohnishi, “Comparison among three estimators for high order statistics.,” in Fifth International Conference on Neural Information Processing (ICONIP’98), S. Usui and T. Omori, Eds., Kitakyushu, Japan, 21-23 October 1998, pp. 899–902. [715] A. Mansour, “Kurtosis and probability density functions,” in TECHNICAL Report of IEICE, Sapporo, Japan, February 1999, pp. 19–24. [716] A. Mansour and N. Ohnishi, “A blind separation algorithm based on subspace approach,” in IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP’99), A. E. C ¸ etin, L. Akarun, A. Ert¨ uz¨ un, M. N. G¨ urcan, and Y. Yardimci, Eds., Antalya, Turkey, June 20-23 1999, pp. 268–272. [717] A. Mansour, “The blind separation of non stationary signals by only using the second order statistics.,” in Fifth International Symposium on Signal Processing and its Applications (ISSPA’99), M. Deriche, Boashash, and W. W. Boles, Eds., Brisbane, Australia, August 22-25 1999, pp. 235–238. [718] A. Mansour and N. Ohnishi, “Multichannel blind separation of sources algorithm based on cross-cumulant and the levenberg-marquardt method.,” IEEE Trans. on Signal Processing, vol. 47, no. 11, pp. 3172–3175, November 1999. [719] A. Mansour and C. Jutten, “What should we say about the kurtosis?,” IEEE Signal Processing Letters, vol. 6, no. 12, pp. 321–322, December 1999. [720] A. Mansour, C. Jutten, and Ph. Loubaton, “An adaptive subspace algorithm for blind separation of independent sources in convolutive mixture,” IEEE Trans. on Signal Processing, vol. 48, no. 2, pp. 583–586, February 2000. [721] A. Mansour, A. Kardec Barros, and N. Ohnishi, “Blind separation of sources: Methods, assumptions and applications.,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83-A, no. 8, pp. 1498–1512, August 2000. [722] A. Mansour and N. Ohnishi, “A batch subspace ica algorithm.,” in 10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, Pocono Manor Inn, Pennsylvania, USA, 14 - 16 August 2000, pp. 63–67. [723] A. Mansour and N. Ohnishi, “Discussion of simple algorithms and methods to separate non-stationary signals,” in Fourth IASTED International Conference On Signal Processing and Communications (SPC 2000), M. H. Hamza, Ed., Marbella, Spain, 19 - 22 September 2000, pp. 78–85. [724] A. Mansour, M. Kawamoto, and N. Ohnishi, “Blind separation for instantaneous mixture of speech signals: algorithms and performances.,” in IEEE Conf. of Intelligent Systems and Technologies for the Next Millennium (TENCON 2000), Kuala Lumpur, Malaysia, 24-27 September 2000, pp. I–26 – I–32. [725] A. Mansour, C. G. Puntonet, and N. Ohnishi, “A new geometrical blind separation of sources algorithm,” in The 5th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI’2001), Florida, USA, 22-25 July 2001, pp. 350–355, This paper has been selected as one of the best papers presented in the session Image and Multidimensional Signal Processing IV. [726] A. Mansour, C. G. Puntonet, and N. Ohnishi, “A simple ICA algorithm based on geometrical approach.,” in Sixth International Symposium on Signal Processing and its Applications (ISSPA 2001), M. Deriche, Boashash, and W. W. Boles, Eds., Kuala-Lampur, Malaysia, August 13-16 2001, pp. 9–12. [727] A. Mansour, “A mutually referenced blind multiuser separation of convolutive mixture algorithm,” Signal Processing, vol. 81, no. 11, pp. 2253–2266, November 2001. [728] A. Mansour, M. Kawamoto, and N. Ohnishi, “A survey of the performance indexes of ICA algorithms,” in 21st IASTED International Conference on Modelling, Identification and Control (MIC 2002), Innsbruck, Austria, 18 - 21 February 2002, pp. 660–666.

[729] A. Mansour, N. Ohnishi, and C. G. Puntonet, “Blind multiuser separation of instantaneous mixture algorithm based on geometrical concepts,” Signal Processing, vol. 82, no. 8, pp. 1155–1175, 2002. [730] A. Mansour and M. Kawamoto, “Ica papers classified according to their applications & performances.,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E86-A, no. 3, pp. 620–633, March 2003. [731] A. Mansour, M. Kawamoto, and C. G. Puntonet, “A time-frequency approach to blind separation of under-determined mixture of sources,” in International Conference on Applied Simulation and Modelling (ASM2003), Marbella, Spain, 3-5 September 2003, pp. 413–418. [732] A. Mansour, “Batch mutually referenced separation algorithm for mimo convolutive mixtures,” in International Workshop on Independent Component Analysis and signal Separation (ICA2004), Granada, Spain, 22-24 September 2004, pp. 453–460. [733] A. Mansour, “Rapport d’avancement de l’tude 6.1 : Sparation de sources du poste 6 : Fusion pour la diversit d’information et l’assimilation de donnes,” Tech. Rep., ENSIETA, Juin 2004, Projet Mthodes d’Observations Discrtes de l’Environnement (MODE). [734] A. Mansour and C. Gervaise, “Ica applied to passive ocean acoustic tomography,” WSEAS Trans. on Acoustics and Music, vol. 1, no. 2, pp. 83–89, April 2004. [735] A. Mansour, “Premier rapport d’tude de l’tude 6.1 : Sparation de sources du poste 6 : Fusion pour la diversit d’information et l’assimilation de donnes,” Tech. Rep., ENSIETA, January 2005, Projet Mthodes d’Observations Discrtes de l’Environnement (MODE). [736] P. Marchand, P. O. Amblard, and Lacoume J. L., “Statistiques d’ordre supérieur ` a deux pour des signaux cyclostationnaires ` a valeurs complexes,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 69–72. [737] H. K. Mardia, “New techniques for the ndeinterleaving of repetitiven sequences,” Proceedings of the IEEE, vol. 136, no. 4, pp. 149–154, 1997, Pt. F. [738] N. Maria, Adéquation matériel-logiciel pour calculateur neuromimétique, Ph.D. thesis, INPG Grenoble, 1994. [739] R. Marken and W. Powers, “random-walk chemotaxis: Trial and error as a control process,” Behavioral Neuroscience, vol. 106, no. 6, pp. 1348–1355, 1989. [740] S. L. Marple, “Are quadratic time-frequency representations really necessary ?,” in Proceedings of International Conference on Speech and Signal Processing 1996, ICASSP 1996, Atlanta, Georgia, May 1996. [741] G. C. Marques and L. B. Almeida, “Separation of nonlinear mixtures using pattern repulsion,” in International Workshop on Independent Component Analysis and Blind Separation of Signals, J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 277 – 282. [742] H. Mathis and S. Douglas, “On optimal and universal nonlinearities for blind signal separation,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001, pp. 2777–2780. [743] A Martin and A. Mansour, “Comparative study of high order statistics estimators,” in 2004 International Conference on Software, Telecommunications and Computer Networks, Split (Croatia), Dubrovnik (Croatia), Venice (Italy), October 10-13, 2004 2004, pp. 511–515. [744] A Martin and A. Mansour, “Comparative study of high order statistics estimators,” in ITST 2005 - 5th International Conference on ITS Telecommunications, Brest, France, Juin 27-29 2005, p. To appear. [745] R. Martin-Clemente and J. I. Acha, “New equation and iterative algorithm for blind separation of sources,” Signal Processing, , no. 82, pp. 861–873, 2002. [746] N. Martins, S. Jesus, C. Gervaise, and A. Quinquis, “A time-frequency approach to blind deconvolution in multipath underwater channels,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2002, ICASSP 2002, Orlando, Florida, U.S.A, 13-17 May 2002. [747] M. Martone, M, “On MMSE real-time antenna array processing using fourth-order statistics in the U.S. cellular TDMA system,” IEEE Journal On Selected Areas In Communications, vol. 16, no. 8, pp. 1396–1410, october 1998. [748] H. Mathis and M. Joho, “Blind signal separation in noisy environments using a three-step quantizer,” Neurocomputing, vol. 49, pp. 61–78, 2002. [749] K. Matsuoka, M. Oya, and M. Kawamoto, “A neural net for blind separation of nonstationary signals,” Neural Networks, vol. 8, no. 3, pp. 411–419, 1995. [750] J. Max, Méthodes et techniques de traitement du signal et applications aux mesures physiques, Masson, Paris, 1988. [751] S. Mayrargue, “Spatial equalization of a radio-mobile channel without beamforming using the constant modulus algorithm,” in Proc. COST on adaptive algorithms in communications, Bordeaux, France, October 1992, pp. 215–224. [752] M. Mboup and P. A. Regalia, “An a priori error bound for the steiglitz-mcbride method in reduced order cases,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 748–751, Elsevier. [753] D.I. Mc Closkey, “Kinesthetic sensibility,” Physiol. Reviews, vol. 58, no. 4, pp. 763–820, 1978. [754] P. McCullagh, Tensor methods in statistics, Chapman and Hall, 1987.

[755] M.J. Mckeown, S. Makeig, G.G. Brown, T-P. Jung, S.S. Kinderm, A.J. Bell, and T.J. Sejnowski, “Analysis of fMRI data by blind separation into independent spatial components,” Human Brain Mapping, vol. 6, pp. 160–188, 1998. [756] M.J. Mckeown, L. K. Hansen, and T.J. Sejnowski, “Independent component analysis of functional mri: what is signal and what is noise,” Current Opinion in Neurobiology, , no. 13, pp. 620–629, 2003. [757] J. M. Mendel, “Tutorial on higher-order statistics (spectra) in signal processing and system theory: Theoretical results and some applications,” IEEE Proc, vol. 79, pp. 277–305, 1991. [758] L. Mevel, A. Benveniste, M. Basseville, and M. Goursat, “Blind subspace-based eigenstructure identification under nonstationary excitation using moving sensors,” IEEE Trans. on Signal Processing, vol. 50, no. 1, pp. 41–57, January 2002. [759] X. Milhaud, Statistique, Belin, Paris, 2001. [760] D. J. Milojevic and B. M. popovic, “Improved algorithm for the deinterleaving of radar pulses,” IEE Proceedings-F, vol. 139, no. 1, pp. 98–104, February 1992. [761] M. Misiti, Y. Misiti, G. Oppenheim, and J. M. Poggi, “Wavelet toolbox: For use with matlab,” 1996. [762] N. Mitianoudis and T. Stathaki, “Overcomplete source separation using laplacian mixture models,” IEEE Signal Processing Letters, vol. 12, no. 4, pp. 277–280, April 2005. [763] T. J. Moir, “The application of servo theory to the LMS algorithm,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 1277–1280, Elsevier. [764] L. Molgedey and G. Schuster, “Separation of a mixture of independent signals using time delayed correlations,” Physical Review Letters, vol. 72, no. 23, pp. 3634–3637, 1994. [765] J. B. Moore and V. Krishnamurthy, “Deinterleaving pulse train using discrete time stochastic dynamic linear models,” IEEE Trans. on Signal Processing, vol. 42, no. 11, pp. 3092–3103, November 1994. [766] J. J. Moré, “The Levenberg-Marquart algorithm: Implementation and theory.,” In G.E. Waston, editor, Lecture Notes in Mathematics 630, pp. 105–116, 1978. [767] E. Moreau and O. Macchi, “New self-adaptive algorithms for source separation based on contrast functions,” in IEEE Signal Processing Workshop on Higher-Order Statistics, South Lac Tahoe, USA (CA), June 1993, pp. 215–219. [768] E. Moreau and O. Macchi, “Séparation auto-adaptative de sources sans blanchiment prealable,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, 13-16 September 1993, pp. 325–328. [769] E. Moreau and O. Macchi, “Two novel architectures for the self adaptive separation of signals,” in IEEE International Conference on Communication, Geneva, Switzerland, 23-26 May 1993, vol. 2, pp. 1154–1159. [770] E. Moreau, Apprentissage et adaptativité. Séparation auto-adaptative de sources indépendantes, Ph.D. thesis, Université de Paris-Sud, 1995. [771] E. Moreau and O. Macchi, “High-order contrasts for self-adaptive source separation,” International journal of adptive control and signal processing, pp. 19–46, 1996. [772] E. Moreau and J. C. Pesquet, “Generalized contrasts for multichannel blind deconvolution of linear systems,” IEEE Signal Processing letters, vol. 4, no. 6, pp. 182–183, 1997. [773] E. Moreau and O. Macchi, “Self-adptive source separation Part II: Comparison of the direct, feedback and mixed linear network,” IEEE Trans. on Signal Processing, vol. 46, no. 1, pp. 39–50, 1998. [774] E. Moreau and N. Thirion-Moreau, “Nonsymmetrical contrasts for sources separation,” IEEE Trans. on Signal Processing, vol. 47, no. 8, pp. 2241–2252, 1999. [775] E. Moreau and P. Comon, “Comments on blind beamforming for multiple non-gaussian signals and the constant modulus algorithm,” IEEE Trans. on Signal Processing, vol. 48, no. 11, pp. 3248–3250, 2000. [776] E. Moreau, “An any order generalization of jade for complex source signals,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [777] E. Moreau, “A generalization of joint-diagonalization criteria for source separation,” IEEE Trans. on Signal Processing, vol. 49, no. 3, pp. 530–541, March 2001. [778] E. Morice, M. Bertrand, and C. Penglaou, Dictionnaire de statistique, Dunod, Paris, 1968. [779] E. Moline, J. Tsutsui, T. okamoto, A. Mansour, M. Kawamoto, and Y. Inouye, “A method for segregation of speech signals,” in 5th IEEE Hiroshima Student Symposium, Hiroshima, Japan, December 2003, pp. 161–166. [780] P. Moulin, “The role of information theory in watermarking and its application to image watermarking,” Processing, vol. 81, pp. 1121–1139, 2000.

Signal

[781] E. Moulines and J.-F. Cardoso, “Second-order versus fourth-order MUSIC algorithms: an asymptotical statistical analysis,” in Proc. IEEE Signal Processing Workshop on Higher-Order Statistics, Chamrousse, France, June 1991. [782] E. Moulines and J.-F. Cardoso, “Direction finding algorithms using fourth-order statististics,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 1992, ICASSP 1992, San Francisco, USA, March 1992, pp. 723–26. [783] E. Moulines, Duhamel P., J. F. Cardoso, and Mayrargue S., “Subspace methods for the blind identification of multichannel FIR filters,” IEEE Trans. on Signal Processing, vol. 43, no. 2, pp. 516–525, February 1995.

[784] B. Muquet, M. De Courville, and P. Duhamel, “Subspace-based blind and semi-blind channel estimation for OFDM systems,” IEEE Trans. on Signal Processing, vol. 50, no. 7, pp. 1699–1712, July 2002. [785] N. Murata, S. Ikeda, and A. Ziehe, “An approach to blind source separation based on temporal structure of speech signals,” NeuroComputing, , no. 22, pp. 1–24, 1998. [786] N. Murata and S. I. Amari, “Statistical analysis of learning dynamics,” Signal Processing, , no. 74, pp. 3–28, 1999. [787] N. Murata, M. Kawanabe, A. Ziehe, K. R. Muller, and S. I. Amari, “On line learning in changing environments with applications in supervised and unsupervised learning,” Neural Networks, , no. 15, pp. 743–760, 2002. [788] J. J. Murillo-Fuentes and F. J. Gonz´ alez-Serrano, “Independent component analysis with sinusoidal fourth-order contrasts,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001, pp. 345–350. [789] J. D. Murray, Mathematical biology, Springer Verlag, 1989. [790] J.-P. Nadal and N. Parga, “Nonlinear neurons in the low-noisy limit: A factorial code maximizes information transfer,” Network, vol. 5, pp. 565–581, 1994. [791] J. P. Nadal, E. Korutcheva, and F. Aires, “Blind source separation in the presence of weak sources,” Neural Networks, vol. 13, pp. 589–596, 2000. [792] A. F. Naguib and A. Paulraj, “A base-station antenna array receiver for cellular DS/CDMA with m-ary orthogonal modulation,” in Proc. 28th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, Canada, November 1994. [793] A. F. Nguib, A. Paulraj, and T. Kailath, “Capacity improvement with base-station antenna arrays in cellular CDMA,” IEEE Trans. Vehicular Technology, vol. VT-43, pp. 691–698, 1994. [794] A. F. Nguib and A. Paulraj, “Performance of wireless CDMA with m-ary orthogonal modulation and cell site antenna arrays,” IEEE Journal on Selected Areas in Communications, 1996. [795] K. I. Nakadai, K. Hidai, H. G. Okuno, and H. kitano, “Real-time speaker localization and speech separation by audiovisual integration,” in 17th international Joint Conference on Artificial Intelligence (IJCAI-01), Seatle, USA, August 2001, pp. 1425–1432. [796] A. k. Nandi and K. tutschku, “Machine condition monitoring based on higher order spectra and statistics,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [797] A. k. Nandi and D. Mampel, “On robust estimation of cumulants,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 470–473, Elsevier. [798] A. K. Nandi, “Identification of fir systems using third order cumulants,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 199–202, Elsevier. [799] A. K. Nandi and D. M¨ ampel, “Development of an adaptive generalised trimmed mean estimator to compute third-order cumulants,” Signal Processing, vol. 57, pp. 271–282, 1997. [800] A. Nandi, Ed., Blind Estimation Using Higher-Order Statistics, Kluwer, 1999. [801] S. S. Narayanan and A. A. Alwan, “Toward articulatory-acoustic models for liquid approximants based on MRI and EPG data. Part I. The laterals,” The Journalof the Acoustical Society of America, vol. 101, no. 2, pp. 1064–1077, February 1997. [802] Ch. Nasr, J. Constantin, and D. Hamad, “LSPB trajectories used in multilayered neural networks controllers in robot control,” in Intelligent Engineering Systems through Artificial Neural Networks, Volume 11, New York, USA, 2001, pp. 509–514. [803] Pin T. NG, “Smoothing spline score estimation,” SIAM journal sci. comput., vol. 15, no. 5, pp. 1003–1025, September 1994. [804] L. Nguyen Thi, C. Jutten, and J. Caelen, “Separation aveugle de parole et de bruit dans un mélange convolutif,” in Actes du XIIIème colloque GRETSI, Juan-Les-Pins, France, September 1991, pp. 737–740. [805] L. Nguyen Thi, C. Jutten, and J. Caelen, “Speech enhancement: Analysis and comparison of methods in various real situations,” in Signal Processing VI, Theories and Applications (EUSIPCO’92), J. Vandewalle, R. Boite, M. Moonen, and A. Oosterlinck, Eds., Brussels, Belgium, August 1992, pp. 303–306, Elsevier. [806] L. Nguyen Thi, Séparation aveugle de sources ` a large bande dans un mélange convolutif, Ph.D. thesis, INP Grenoble, January 1993. [807] L. Nguyen Thi and C. Jutten, “Comparaison de quelques algorithmes adaptatifs de séparation aveugle de sources dans un mélange convolutif,” in Actes du XIVème Colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 333–336. [808] H. L. Nguyen Thi and C. Jutten, “Whitening for blind separation of sources,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [809] L. Nguyen Thi and C. Jutten, “Blind sources separation for convolutive mixtures,” Signal Processing, vol. 45, no. 2, pp. 209–229, 1995. [810] L. Nguyen Thi, S. Van Gerven, C. Jutten, and D. Van Compernolle, “Stability study for source separation in convolutive mixtures of two sources,” Signal Processing, vol. 62, pp. 163–171, 1997.

[811] T. V. Nguyen, J. Ch. Patra, and A. Das, “A post nonlinear geometric algorithm for independent component analysis,” Digital Signal Processing, , no. 15, pp. 276–294, 2005. [812] J. M. Nicolas, “Introduction aux statistiques de deuxième espèce : applications des logs-moments et des logs-cumulants ` a l’analyse des lois d’images radar,” Traitement du signal, vol. 19, no. 3, pp. 139–167, 2002. [813] C. L. Nikias and J. M. Mendel, “Signal processing with higher-order spectra,” IEEE Signal Processing Magazine, vol. 10, no. 3, pp. 10–37, 1993. [814] T. Nishikawa, H. Saruwatari, and K. Shikano, “Blind source separation based on multi-stage ICA combining frequencydomain ICA and time-domain ICA,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2002, ICASSP 2002, Orlando, Florida, U.S.A, 13-17 May 2002. [815] B. Noble and J. W. Daniel, Applied linear algebra, Prentice-Hall, 1988. [816] G. Noone, “A neural approach to automatic pulse repetition interval modulation recognition,” in Proceedings of Information Decision and Control 99, Robin Evans, Lang White, Daniel McMichael, and Len Sciacca, Eds., Adelaide, Australia, February 1999, pp. 213–218. [817] D. Nuzillard and J. M. Nuzillard, “Blind source separation applied to non-orthogonal signals,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 25–30. [818] M. Ohata and K. Matsuoka, “Stability analysis of information-theoretic blind separation algorithms in the case where the sources are nonlinear processes,” IEEE Trans. on Signal Processing, vol. 50, no. 1, pp. 69–76, January 2002. [819] S. Ohno and G. B. Giannakis, “Blind identification for fixed fragment-size packet transmissions with distributed redundancy over multipath fading channels,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 733–738. [820] E. Oja, H. Ogawa, and J. Wangviwattana, “Learning in nonlinear constrained hebbian networks,” in Proc. ICANN 91, 1991, pp. 385–390. [821] E. Oja, “The nonlinear PCA learning rule in independent component analysis,” Neurocomputing, vol. 17, pp. 25–45, 1997. [822] E. Oja, “From neural learning to independent components,” NeuroComputating, vol. 22, pp. 187–199, 1998. [823] E. Oja, “Nonlinear PCA criterion and maximum likelihood in independent component analysis,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 143–148. [824] E. Oja and M. Plumbley, “Blind separation of positive sources using non-negative PCA,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 11–16. [825] H. G. Okuno, S. Iketa, and T. Nakatani, “Ijcai combining independent component analysis and sound stream segregation,” in Workshop on Computational Auditory Scene Analysis CASA’99, Stokholom, Sweden, August 2002, pp. 92–98. [826] H. G. Okuno, K. Nakadai, T. Lourens, and H. kitano, “Separating three simultaneous speeches with two microphones by integrating auditory and visual processing,” in European Conference on Speech Processing, Aalborg, Denmark, September 2001, pp. 2643–2646. [827] F. Ollivier, Conception et réalisation d’un sonar lateral bathymétrique ` a haute résolution avec voies performées compensées en attitude, Ph.D. thesis, Université de Paris 6, Avril 1995. [828] R. Onn and A. O. Steinhardt, “A multiwindow method for spectrum estimation and sinusoid detection in an array environment,” IEEE Trans. on Signal Processing, vol. 42, no. 11, pp. 3006–3015, November 1994. [829] S. J. Orfanidis, Introduction to signal processing, Prentice-Hall, New Jersey, 1995. [830] C. Ottonello and S. Pagnan, “Kurtosis in frequency domain for transient detection,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [831] K. Oweiss and D. Anderson, “A new technique for blind source separation using subband subspace analysis in correlated multichannel signal environments,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [832] P. Pajunen, A. Hyv¨ arinen, and J. Karhunen, “Nonlinear blind source separation by self-organizing maps,” in International Conference on Neural Information Processing (ICONIP’96), Hong-Kong, September 1996, pp. 1207–1210. [833] P. Pajunen and J. Karhunen, “A maximum likelihood approach to nonlinear blind source separation,” in ICANN, Lausanne, Switzeland, October 1997, pp. 541–546. [834] P. Pajunen, “Blind source separation using algorithmic information theory,” NeuroComputating, vol. 22, pp. 35–48, 1998. [835] P. Pajunen, Extensions opf linear independent component analysis: Neural and information-theoretic methods, Ph.D. thesis, Helsinki University of Technology, Finland, May 1998. [836] P. Pajunen and J. Karhunen, “Least-squares methods for blind source separation based on nonlinear PCA,” International Journal of Neural Systems, vol. 8, no. 5-6, pp. 601–612, 1998. [837] J. A. Palmer and K. Kreutz-Delgado, “A general framework for component estimation,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 41–46.

[838] F. Palmieri, A. Budillon, M. Calabrese, and D. Mattera, “Searching for binary factorial code using the ica framework,” NeuroComputating, vol. 22, pp. 131–144, 1998. [839] C. B. Papadias and A. J. Paulraj, “A constant modulus algorithm for multiuser signal separation in the presence of delay spread using antenna arrays,” IEEE Signal Processing Letters, vol. 4, no. 6, pp. 178–181, Jun 1997. [840] C. Papadias, “A multi-user kurtosis algorithm for blind source separation,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3144–3148. [841] C. K. Papadopoulos and C. L. Nikias, “Parameter estimation of exponentially damped sinusoids using higher order statistics,” IEEE Trans. on Acoustics Speech and Signal Processing, vol. 38, no. 8, pp. 1424–1436, August 1990. [842] A. Papoulis, Probability, random variables, and stochastic processes, McGraw-Hill, New York, 1991. [843] N. Parga and J. P. Nadal, “Blind source separation with time-dependent mixtures,” Signal Processing, vol. 80, pp. 2187–2194, 2000. [844] H.-M. Park et al., “On subband-based blind signal separation for noisy speech recognition,” Electronic Letters, vol. 35, no. 23, pp. 2011–2012, 1999. [845] H. Park, S.-I. Amari, and K. Fukumizu, “Adaptive natural gradient learning algorithms for various stochastic models,” Neural Networks, vol. 13, no. 7, pp. 755–764, 2000. [846] L. Parra, G. deco, and S. Miesbach, “statistical independence and novelty detection with information preserving nonlinear maps,” Neural Computation, vol. 8, pp. 260–269, 1996. [847] L. Parra and C. V. Alvino, “Convolutive blind separation of non-stationnary sources,” IEEE Trans. on Speech and Audio Processing, vol. 8, no. 3, pp. 320–327, May 2000. [848] L. Parra and C. V. Alvino, “Geometric source separation : merging convolutive source separation with geometric beamforming,” IEEE Trans. on Speech and Audio Processing, vol. 10, no. 6, pp. 352–362, September 2002. [849] A. Papanderou Suppappola and S. B. Suppappola, “Sonar echo ranging using signals with non-linear time frequency characterisics,” IEEE Signal Processing Letters, vol. 11, no. 3, pp. 393–396, March 2004. [850] W. Papoulis, Theory of relativity, Dover Publications, New York, 1958. [851] D. I. Pazaitis and A. G. Constantinides, “A kurtosis-driven variable step-size LMS algorithm,” in Proceedings of International Conference on Speech and Signal Processing 1996, ICASSP 1996, Atlanta, Georgia, May 1996. [852] D. I. Pazaitis and A. G. Constantinides, “A new robust adaptive step size LMS algorithm,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 180–183, Elsevier. [853] K. Pearson, “On lines and plances of closest fit to system of points in space,” Phil. Trans., vol. clxxxvii. A, pp. 559–572, 1996. [854] M Pedzisz and A. Mansour, “Hos based distinctive features for preliminary signal classification,” in International Workshop on Independent Component Analysis and signal Separation (ICA2004), Granada, Spain, 22-24 September 2004, pp. 115–1164. [855] M Pedzisz and A. Mansour, “Carrier synchronization based on renyi’s entropy,” in 2004 International Conference on Software, Telecommunications and Computer Networks, Split (Croatia), Dubrovnik (Croatia), Venice (Italy), October 10-13, 2004 2004, pp. 498–501. [856] M Pedzisz and A. Mansour, “Automatic modulation recognition of MPSK signals using constellation rotation and its 4-th order cumulant,” Digital Signal Processing, vol. 15, no. 3, pp. 295–304, 2005. [857] M Pedzisz and A. Mansour, “Hos-based multi-component frequency estimation,” in 13th European conference on Signal Processing, Theories and Applications (EUSIPCO’2005), Antalya, Turkey, September 2005, p. To appear, Elsevier. [858] J. Perkins and I. Coat, “Pulse train deinterleaving via the hough transform,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 1992, ICASSP’92, San Fransisco, CA, USA, March 1992. [859] J. Pesquet, B. Chen, and A. Petropulu, “Frequency-domain contrast functions for separation of convolutive mixtures,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [860] Th. Petermann, D. Boss, and K.-D. Kammeyer, “Blind GSM channel estimation under channel coding conditions,” in 38th Conference on DEcision and Control (cdc99), Phoenix, USA, December 1999, pp. 180–185. [861] B. Petersen, “Contraction mappings,” June 22 1999. [862] N. Petrochilos and P. Comon, “ML estimation of SSR signals, identifiability and Cramer-Rao bounds,” in Signal Processing VII, Theories and Applications (EUSIPCO’2000), Tamper, Finland, September 2000, pp. 4–8, Elsevier. [863] N. Petrochilos and P. Comon, “Blind identification of linear-quadratic channels,” in 10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, Pocono Manor Inn, Pennsylvania, USA, 14 - 16 August 2000, pp. 181–185. [864] J. L. Peyre, L. LeRoux, D. Rossille, and G. Favier, “MA HOS modelization from samples of band-limited third order stationary signals,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [865] D. T. Pham, P. Garat, and C. Jutten, “Separation of a mixture of independent sources through a maximum likelihood approach,” in Signal Processing VI, Theories and Applications (EUSIPCO’92), J. Vandewalle, R. Boite, M. Moonen, and A. Oosterlinck, Eds., Brussels, Belgium, August 1992, pp. 771–774, Elsevier.

[866] D. T. Pham and P. Garat, “Séparation aveugle de sources temporellement corrélées,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, September 1993, pp. 317–320. [867] D. T. Pham, “Séparation aveugle de sources via une analyse en composantes indépendantes,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 289–292. [868] D.T. Pham, “On the discrtisation error in the computation of the empirical characyteristic function,” Journal of Statist. Comput. Simul., vol. 53, pp. 129–141, 1995. [869] D.T. Pham, “Blind separation of instantaneous mixtures via an independent component analysis,” IEEE Trans. on Signal Processing, vol. 44, no. 11, pp. 2768–2779, 1996. [870] D. T. Pham and P. Garat, “Blind separation of mixture of indepndent sources through a quasi-maximum likelihood approach,” IEEE Trans. on Signal Processing, vol. 45, no. 7, pp. 1712–1725, July 1997. [871] D.T. Pham, “Mutual information approach to blind separation of stationary sources,” in Proceedings of ICA’99, Aussois, France, January 1999, pp. 215–220. [872] D.T. Pham and J. F. Cardoso, “Blind separation of instantaneous mixtures of non stationary sources,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 187–192. [873] D. T. Pham, “Blind separation of instantaneous mixtures of sources based on order statistics,” IEEE Trans. on Signal Processing, vol. 48, no. 2, pp. 1712–1725, Feburary 2000. [874] D. T. Pham, “Blind separation of instantaneous mixtures of sources via the Gaussian mutual information criterion,” Signal Processing, vol. 81, pp. 855–870, February 2001. [875] D. T. Pham and J. F. Cardoso, “Blind separation of instantaneous mixtures of nonstationary sources,” IEEE Trans. on Signal Processing, vol. 49, no. 9, pp. 1837–1848, September 2001. [876] D. T. Pham, “Mutual information approach to blind separation of stationary sources,” IEEE Trans. on Information Theory, vol. 48, no. 7, pp. 1935–1946, July 2002. [877] D.-T. Pham, “Fast algorithm for estimating mutual information, entropies and score functions,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 17–22. [878] D. T. Pham, Ch Servière, and H. Boumaraf, “Blind separation of convolutive audio mixtures using nonstationary,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003. [879] D. T. Pham, Ch Servière, and H. Boumaraf, “Blind separation of speech mixtures on nonstationary,” in 7th International Symposium on Signal Processing and its Applications (ISSPA 2003), Paris, France, 1-4 July 2003. [880] T. Q. Phong, R. Horaud, A. Yassine, and P. D. Tao, “Object pose from 2-d to 3-d point and line correspondences.,” International Journal of Computer Vision, vol. 15, no. 3, pp. 225–243, 1994. [881] B. Picinbono, Théorie des signaux et des systèmes, Dunod, Paris, 1989. [882] B. Picinbono, Signaux aléatoires, Tome 1, Dunod, Paris, 1993. [883] B. Picinbono, Signaux aléatoires, Tome 2, Dunod, Paris, 1994. [884] B. Picinbono, Signaux aléatoires, Tome 3, Dunod, Paris, 1995. [885] B. Picinbono, “On circularity,” IEEE Trans. on Signal Processing, vol. 42, no. 12, pp. 225–243, December 1994. [886] S. Pinet, Etude et reconnaissance de signaux ` a modulations numériques rapides ` a partir de transformations TempsFréquence, Ph.D. thesis, Université de Nice - Sophie Antipolis, Janvier 1995. [887] K. Piwnicki, “Modulation methods related to sine-wave crossings,” IEEE Trans. on Communications, vol. Com-31, no. 4, pp. 503–508, 1983. [888] M. J. Porsani and T. J. Ulrych, “Levinson-type algorithms for polynomial fitting and for Cholesky and Q factors of hankel and Vandermonde matrices,” IEEE Trans. on Signal Processing, vol. 43, no. 1, pp. 63–70, Januray 1995. [889] I. Potamitis, G. Tremoulis, and N. Fakotakis, “Multi-speaker DOA tracking using interactive multiple models and probabilitic data association,” in 8th European Conference on Speech Commuication and Technology (EUROSPEECH 2003), Geneva, Switzerland, 1-4 September 2003, pp. 517–520. [890] H. Pozidis, A. P. Petropulu, and T. J. Enders, “Comparison between SOS and HOS methods for blind equalization of microwave radio channels,” in IEEE SP Int Workshop on High Order Statistics, HOS 99, Caeserea, Israel, 12-14 June 1995. [891] S. Prakriya and D. Hatzinakos, “Blind identification of linear subsystems of LTI-ZMNL-LTI models with cyclostationary inputs,” IEEE Trans. on Signal Processing, vol. 45, no. 8, pp. 2023–2036, August 1997. [892] S. Prakriya, “Eigenanalysis-based blind methods for identification, equalization, and inversion of linear time-invariant channels,” IEEE Trans. on Signal Processing, vol. 50, no. 7, pp. 1525–1532, July 2002. [893] S. Prasad and N. C. Menicucci, “Fisher information with respect to cumulants,” IEEE Trans. on Information Theory, vol. 50, no. 4, pp. 638–642, April 2004. [894] W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling, Numerical recipes in C, Cambridge University Press, London, 1998.

[895] A. Prieto, C. G. Puntonet, and B. Prieto, “A neural algorithm for blind separation of sources based on geometric prperties.,” Signal Processing, vol. 64, no. 3, pp. 315–331, 1998. [896] A. Prieto, B. Prieto, C. G. Puntonet, A. Ca˜ nas, and P. Mart´ın-Smith, “Geometric separation of linear mixtures of sources: Application to speech signals,” in International Workshop on Independent Component Analysis and Blind Separation of Signals, J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 295 – 300. [897] J. C. Principe and D. Xu, “Information-theoretic learning using renyi’s quadratic entropy,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 407–412. [898] J. Principe, D. Xu, and J. Fisher, “Information theoretic learning,” 1999. [899] E. Punskaya, C. Andrieu, A. Doucet, and W. J. Fitzgerald, “Bayesian curve fitting using MCMC with applications to signal segmentation,” IEEE Trans. on Signal Processing, vol. 50, no. 3, pp. 747–757, March 2002. [900] C. G. Puntonet, Nuevos algoritmos de separaci´ on de fuentes en medios lineales, Ph.D. thesis, University of Granada, SPAIN, September 1994. [901] C. G. Puntonet, M. Rodriguez, and A. Prieto, “A geometrical based procedure for source separation mapped to a neural network,” in From natural to artificial neural computation, Torremolimos, Malaga , Spain, 7-9 June 1995, pp. 898–905. [902] G. Puntonet, C., A. Mansour, and C. Jutten, “Geometrical algorithm for blind separation of sources,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 273–276. [903] C. G. Puntonet, A. Prieto, C. jutten, M. Rodriguez Alvarez, and J. Ortega, “Separation of sources: A geometry-based procedure for reconstruction of n-valued signals,” Signal Processing, vol. 46, no. 3, pp. 267–284, 1995. [904] C. G. Puntonet and A. Prieto, “Neural net approach for blind separation of sources based on geometric properties,” NeuroComputing, vol. 18, no. 3, pp. 141–164, 1998. [905] C.G. Puntonet, M.R. Alvarez, A. Prieto, and Prieto B, “Separation of speech signals for nonlinear mixtures,” Lecture Notes in Computer Science, 1607 (II), pp. 665–673, 1999. [906] C.G. Puntonet, C. Bauer, E. W. Lang, M. R. Alvarez, and B. Prieto, “Adaptive-geometric methods: Application to the separation of EEG signals,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 273–278. [907] C.G. Puntonet, A. Mansour, M. R. Alvarez, B. Prieto, and F. Rojas, “A stochastic and competitive network for the separation of sources,” in The 9th European Symposium on Artificial Neural Networks (ESANN 2001), Bruges, Belgium, 25-27 April 2001. [908] C.G. Puntonet and A. Mansour, “Blind separation of sources using density estimation and simulated annealing,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E84-A, no. 10, pp. 2539– 2547, 2001. [909] C.G. Puntonet, A. Mansour, and F. Rojas, “Competitive learning, simulated annealing and genetic algorithms for the separation of sources,” in The 6th IASTED International Conference Artificial Intelligence & Soft Computing (ASC 2002), Banff, Alberta, Canada, 17-19 July 2002. [910] C. G. Puntonet, A. Mansour, C. Bauer, and E. Lang, “Separation of sources using simulated annealing and competitive learning,” NeuroComputing, vol. 49, no. 12, pp. 39–60, 2002. [911] A. Quinquis, “Mieux comprendre et mieux décider par les méthodes temps-fréquence,” Tech. Rep., Université de Bretagne Occidentale, Juin 1999, Habilitation de diriger des recherches. [912] L. R. Rabiner and B. H. Juang, “An introduction to hidden Markov models,” IEEE ASSP MAGAZINE, pp. 4–16, January 1986. [913] L. R. Rabiner, “A tutorial on hidden Markov models and selected applications in speech recognition,” Proceedings of the IEEE, vol. 77, no. 2, pp. 257–286, February 1986. [914] K. Rahbar and J. Reilly, “Blind separation of convolved sources by joint approximate diagonalization of cross-spectral density matrices,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [915] T. S. Rao and M. M. Gabr, “The estimation of the bispectral density function and the detection of periodicities in a signal,” J. Mult. Anal., vol. 27, no. 2, pp. 484–504, 1988. [916] T. S. Rao and M. M. Gabr, “The estimation of spectrum, inverse spectrum and inverse autocovariances of a stationary time series,” Journal of Time Serie Analysis, vol. 10, no. 2, pp. 183–202, 1989. [917] T. S. Rao, “Nonlinear (non gaussian) time series and higher order spectra,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [918] L. K. Rasmussen, A. J. Grant, and P. D. Alexander, “An extrinsic kalman filter for iterative multiuser decoding,” IEEE Trans. on Information Theory, vol. 50, no. 4, pp. 642–648, April 2004. [919] P. A. Regalia, “Past input reconstruction in fast least-squares algorithms,” IEEE Trans. on Signal Processing, vol. 45, no. 9, pp. 2231–2240, September 1997. [920] P. A. Regalia and M. Mboup, “Properties of some blind equalization criteria in noisy multiuser environments,” IEEE Trans. on Signal Processing, vol. 49, no. 11, pp. 3112–3122, November 2001.

[921] S. Reimann, “Oscillation and pattern formation in a system of self-regulating cells,” Physica, vol. D, no. 114, pp. 338–361, 1998. [922] S. Reimann, “Stability and equilibrated structure,” in Proc. of the 3-rd German Workshop on Artificial Life, C. Wilke, S. Altmeyer, and Th. Martinez, Eds. 1998, Harry Deutsch Verlag. [923] S. Reimann and A. Mansour, “Navigation by weighted chance,” in The Second International Conference on Intelligent Processing and Manufacturing of Materials IPMM’99, J. A. Meech, M. M. Veiga, M. H. Smith, and S. R. LeClair, Eds., July 10 - 15 1999, pp. 1103 – 1107. [924] S. Reimann and A. Mansour, “From life to robotics: social robots?,” in The Fifth International Symposium on Artificial Life and Robotics AROB 5th’00, M. Sugisaka and H. Tanaka, Eds., January 26 - 28 2000, pp. 359–362. [925] S. Reimann and A. Mansour, “Oriention by weighted randomness,” Artificial Life and Robotics, vol. 4, no. 2, pp. 119–123, 2000. [926] C. H. Reinsch, “Smoothing by spline functions,” Numer. Math., vol. 10, pp. 177–183, 1967. [927] A. A. G. Requicha, “The zeros of entire functions: Theory and engineering applications,” Proceedings of the IEEE, vol. 68, no. 3, pp. 308–328, March 1980. [928] S. Rickard, R. Balan, and J. Rosca, “Blind source separation based on space-time-frequency diversity,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 493–498. [929] J. H. Rindel, “The use of computer modeling in room acoustics,” in International Conference Baltic-Acoustic, Vilnius, Lithuania, 2000, pp. 219–229. [930] T. Ristaniemi, K. Raju, J. Karhunen, and E. Oja, “Inter-cell interference cancellation in CDMA array systems by independent component analysis,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 739–744. [931] S. Roberts and R. Everson, Independent component analysis, Principles and practice, Cambridge University Press, Cambridge, 2001. [932] W. Roberts and Y. Ephraim, “Hidden markovmodeling of speech using toeplitz covariance matrices,” Speech Communication, vol. 31, pp. 1–14, 2000. [933] M. Rodrigues-Alvarez, F. Rojas, C. G. Puntonet, and A. Mansour, “Blind separation of speech signals based on latticeica geometric procedure,” in The 7th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI’2003), Florida, USA, 27-30 July 2003, pp. 350–355. [934] J.-P. Roll, Contribution ` a la proprioception musculaire, ` a la perception et au contrˆ ole du mouvement chez l’homme, Ph.D. thesis, Université d’Aix-Marseille 1, 1981. [935] J. Rosca, J. Ruanaidh, A. Jourjine, and S. Rickard, “Broadband direction of arrival estimation based on second order statistics,” in Neural Information Processing System, Denever, Colorado, USA, November 29 - December 4 1999. [936] R. Rosipal and M. Girolami, “An expectation-maximization approach to nonlinear component analysis,” Neural Computation, vol. 13, no. 3, pp. 505–510, 2001. [937] R. Rosipal and M. Girolami, “Kernel pca for feature extraction and de-noising in non-linear regression,” Computation & applications, vol. 10, no. 3, pp. 231–243, 2001.

Neural

[938] G. Roussel, E. Ternisien, and M. Benjelloun, “Estimation d’un modéle stationnaire de dispersion et localisation de source. application ` a la surveillance de la pollution,” Traitement du signal, vol. 19, no. 1, pp. 37–48, 2002. [939] G. Roussel, E. Ternisien, and M. Benjelloun, “A unifying review of linear Gaussian models,” Neural Computation, , no. 11, pp. 305–345, 1999. [940] S. Roweis and Z. Ghahramani, “An em algorithm for identification of nonlinear dynamical systems,” 2001. [941] Walter Rudin, Principles of mathematical analysis, McGraw-Hill Higher Education, New-York, 1976. [942] P. Ruiz and J. L Lacoume, “Extraction of independent sources from correleted inputs: A solution based on cumulants,” in Proc. Workshop on Higher-Order Spectral Analysis, 1989, pp. 146–151. [943] P. Ruiz, “Sources identification using cumulants: Limits and precautions of use,” in Proc. IEEE Signal Processing Workshop on Higher-Order Statistics, Chamrousse, France, June 1991, pp. 257–260. [944] B. Sagi, S. C. Nemat-Nasser, R. Kerr, R. Hayek, C. Downing, and R. Hecht-Nielsen, “A biologically motivated solution to the cocktail party problem.,” Neural Computation, vol. 13, pp. 1575–1602, 1998. [945] H. Sahlin and H. Broman, “Separation of real-world signals,” Signal Processing, vol. 64, pp. 103–113, 1998. [946] M. Sahmoudi, K. Abed-Meraim, and M. Benidir, “Blind separation of impulsive alpha-stable sources using minimum dispersion criterion,” IEEE Signal Processing Letters, vol. 12, no. 4, pp. 281–284, April 2005. [947] A. Sandouk, A study on throughput and outage probability of wireless packet CDMA systems in multimedia environment, Ph.D. thesis, Nagoya University, Nagoya-Japan, April 2001. [948] V. D. A. Sanchez, “Frontiers of research in bss/ica,” NeuroComputing, , no. 49, pp. 7–23, 2002. [949] H. Saruwatari, S. Kajita, K. Takeda, and F. Itakura, “Speech enhancement using nonlinear microphone array with noise adaptive complementory beamforming,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000.

[950] H. Saruwatari, S. Kurita, and K. Takeda, “blind source separation combined frequency-domain ICA and beamforming,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [951] A. H. Sayed and T. Kailath, “A state-space approach to adaptive RLS filtering,” IEEE Signal Processing Magazine, pp. 18–60, July 1994. [952] G. Scarano, “Cumulant series expansion of hybrid nonlinear moments of complex random variables,” IEEE Trans. on Signal Processing, vol. 39, no. 4, pp. 1001–1003, 1991. [953] L. L. Scharf, Statistical signal processing: Detection, estimation, and time series analysis, Addison-Welsey Publishing Company, 1993. [954] C. D. Schleher, Introduction to electronic warfare, Artech House, New York and London, 1986. [955] D. W. E. Schobben and P. C. W. Sommen, “A frequency domain blind separation method based on decorrelation,” IEEE Trans. on Signal Processing, vol. 50, no. 8, pp. 1855–1865, August 2002. [956] M. Shulkin and H. W. Marsh, “Sound absorption in sea water,” Journal of the Acoustical Society of America, vol. 134, pp. 864–865, 1962. [957] T. Sekiguchi and Y. Karasawa, “Wideband beamspace adaptive array utilizing fir fan filters for multibeam forming,” IEEE Trans. on Signal Processing, vol. 48, no. 1, pp. 277–284, January 2000. [958] S. Selvan and R. Srinivasan, “Removal of ocular artifacts from EEG using an efficient neural network based adaptive filtering technique.,” IEEE Signal Processing Letters, vol. 6, no. 12, pp. 330–332, December 1999. [959] E. Serpedin and G. B. Giannakis, “Blind channel identification and equalization with modulation-induced cyclostationarity,” IEEE Trans. on Signal Processing, vol. 46, no. 7, pp. 1930–1943, July 1998. [960] C. Serviére and V. Capdevielle, “An identification method of FIR digital filters in frequency-domain,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 1058–1061, Elsevier. [961] C. Servière, J. L. Lacoume, and C. Jutten, “De l’ordre 2 ... aux ordres supérieurs en traitement du signal,” Tech. Rep., Ecole des techniques avancées: Signal Image Parole, ENSIEG Grenoble-France, September 1996. [962] J. Sijbers, J. Den Dekker, P. Scheunders, and D.. Van Dyck, “Maximum-mikelihood estimation of rician distribution parameters,” IEEE Trans. on Medical Imaging, vol. 17, no. 3, pp. 357–361, 1998. [963] B. W. Silverman, Density Estimation for Statistics and Data Analysis, Champon & Hall, New York and London, 1986. [964] S. Shahbazpanahi and S. Valaee, “Distributed source localization using esprit algorithm,” IEEE Trans. on Signal Processing, vol. 49, no. 10, pp. 2169–2178, October 2001. [965] O. Shalvi and E. Weistein, “New criteria for blind deconvolution of non-minimum-phase systems (channels),” IEEE Trans. on Information Theory, vol. 36, no. 2, pp. 312–321, March 1990. [966] O. Shalvi and E. Weistein, “Maximum likelihood and lower bounds in system identification with non-gaussian inputs,” IEEE Trans. on Information Theory, vol. 36, no. 2, pp. 328–329, March 1994. [967] S. Shamsunder and G. B. Giannakis, “Modeling of non-gaussian array data using cumulants: DOA estimation of more sources with less sensors,” Signal Processing, vol. 30, pp. 279–297, 1993. [968] L. Shaolin and T. J. Sejnowski, “Adaptive separation of mixed broad-band sound sources with delays by a beamforming Hérault-Jutten network,” IEEE Journal of Oceanic Engineering, vol. 20, no. 1, pp. 73–79, January 1995. [969] Z. Shi and F. W. Fairman, “Harmonic retrieval via state space and fourth-order cumulants,” IEEE Trans. on Signal Processing, vol. 42, no. 5, pp. 1109–1119, May 1994. [970] Z. Shi, H. Tang, and Y. Tang, “A new fixed-point algorithm for independent component analysis,” NeuroComputing, , no. 56, pp. 467–473, 2004. [971] A. N. Shiryayev, Probability, Spring, 1984. [972] V. Shtrom and H. Fan, “New class of zero-forcing cost functions in blind equalization,” IEEE Signal Trans on Processing Letters, vol. 46, no. 10, pp. 2674–2683, October 1998. [973] H. C. Shyu, C. C. Chang, Y. J. Lee, and C. H. Lee, “Radar signal clustering and deinterleaving by a neural network,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E80-A, no. 5, pp. 903–911, May 1997. [974] C. Simon, C. Vignat, Ph. Loubaton, and C. Jutten, “Quelques remarques mthodologiques concernant la sparation des mlanges convolutifs par l’approche de dcorrlation,” in Actes du XVIème colloque GRETSI, Grenoble, France, September 1997, pp. 11–14. [975] C. Simon, Séparation aveugle des sources en mélange convolutif, Ph.D. thesis, l’université de Marne la Vallée, Novembre 1999, (In French). [976] P. K. Simpson, Artificial neural systems, Pergamon Press, 1991. [977] P. Sircar and S. Sharma, “Complex FM signal model for non-stationary signals,” Signal Processing, vol. 57, pp. 283–304, 1997.

[978] S. Sirianupiboon, G. Noone, and S. Howard, “Robust and recursive radar pulse train parameter estimator,” in Fourth International Symposium on Signal Processing and its Applications (ISSPA’96), Gold Coast, Australia, August 25-30 1996. [979] J. Sj¨ oberg, Q. Zhang, L. Ljung, A. Benveniste, B. Delyon, P. Y. Glorennec, H. Hjalmarsson, and A. Juditsky, “Nonlinear black-box modeling in system identification: A unified overview,” Automatica, vol. 31, no. 12, pp. 1691–1724, 1995. [980] V. P. Skitovic, “Linear forms of independent random variables and the normal distribution law,” Izvestiya Akademii Nauk SSSR. Seriya Matematiceskaya, vol. 18, pp. 185–200, 1954, in Russian. [981] D. T. Slock, “Blind fractionally-spaced equalization based on cyclostationarity and second order statistics,” in Proc. Workshop Athos working group, Sophia-Antipolis, France, September 1993. [982] D. T. Slock, “Blind fractionally-spaced equalization perfect reconstruction filter-banks and multichannel linear prediction,” in Proceedings of International Conference on Speech and Signal Processing 1994, ICASSP 1994, Adelaide, Australia, April 18-22 1994, vol. 4, pp. 585–588. [983] P. Smaragdis, “Blind separation of convolved mixtures in the frequency domain,” NeuroComputing, , no. 22, pp. 21–34, 1998. [984] J. C. So, “The sub-gaussian distribution of currency futures: stable paretian or nonstationary,” The Review of Economics and Statistics, vol. 69, pp. 100–107, 1987. [985] T. S¨ oderstr¨ om and P. Stoica, “Emitter waveform estimation in array signal processing,” INT. J. CONTROL, vol. 61, no. 5, pp. 965–980, 1995. [986] J. Sohn, N. Soo Kim, and W. Sung, “A statistical model-based voice activity dectection,” IEEE Signal Processing Letters, vol. 6, no. 1, pp. 1–3, January 1999. [987] M. Solazzi, A. Uncini, and F. Piazza, “Nonlinear blind source separation by spline neural networks,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [988] V. Solo, “The stability of LMS,” IEEE Trans. on Signal Processing, vol. 45, no. 12, pp. 3017–3026, December 1997. [989] M. M. Sondhi and G. W. Elko, “Adaptive optimization of microphone arrays under a nonlinear constraint,” in Proceedings of International Conference on Speech and Signal Processing 1986, ICASSP 1986, Tokyo, Japan, 1986, pp. 981–984. [990] E. Sorouchyari, “Blind separation of sources, Part III: Stability analysis,” Signal Processing, vol. 24, no. 1, pp. 21–29, 1991. [991] A. Souloumiac and J. F. Cardoso, “Comparaison de méthodes de séparation de sources,” in Actes du XIIIème colloque GRETSI, Juan-Les-Pins, France, September 1991, pp. 661–664. [992] A. Souloumiac and J. F. Cardoso, “Performances en séparation de sources,” in Actes du XIVème colloque GRETSI, Juan-Les-Pins, France, Septmber 1993, pp. 321–324. [993] A. Souloumiac, Utilisation des statistiques d’ordre supérieur pour le filtrage et la séparation de sources en traitement d’antenne, Ph.D. thesis, ENST Paris, 1993. [994] M. R. Spiegel, Formules et tables de mathématiques, McGraw-Hill, New York and Paris, 1978. [995] R. Srinivasan, “Some results inimportance sampling and an application to detection,” Signal Processing, vol. 65, pp. 73–88, 1998. [996] L. Stankovic and V. Kathovnik, “Algorithm for the instantaneous frequency estimation using time-frequency distributions with adaptive window width,” IEEE Signal Processing Letters, vol. 5, no. 9, pp. 224–227, September 1998. [997] P. T. Stathaki, “Eigenanalysis of two dimensional third order cumulant matrices for texture validation,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [998] M. Stetter, I. Schiel, T. Otto, F. Sengpiel, M. Hubener, T. Bonhoeffer, and K. Obermayer, “Principal component analysis and blind separation of sources for optical imaging of intrinsic signals,” NeuroImage, 2000. [999] A. G. Stogioglou and S. McLaughlin, “New results in blind deconvolution and system identification of FIR systems,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [1000] P. Stoica and T. S¨ oderstr¨ om, “Parameter identifiability problem in signal processing,” IEE Proc.-Radar, Sonar Navig., vol. 141, no. 3, pp. 133–136, June 1994. [1001] B. Stoll and E. Moreau, “A generalized ICA algorithm,” IEEE Signal Processing Letters, vol. 7, no. 4, pp. 90–92, April 2000. [1002] P. Strobach, “Square hankel SVD subspace tracking algorithms,” Signal Processing, vol. 57, pp. 1–18, 1997. [1003] A. Strope and A. Alwan, “A model of dynamic auditory perception and its application to robust word recognition,” IEEE Trans. on Speech and Audio Processing, vol. 5, no. 5, pp. 451–462, September 1997. [1004] A. Stuart and J. Keith Ord, Kendall’s advanced theory of statistics, Oxford University Press, 1991, volume 2. [1005] B. Suard, A. F. Naguib, G. Xu, and A. Paulraj, “Performance of CDMA mobile communication systems using antenna arrays,” in Proceedings of International Conference on Speech and Signal Processing 1994, ICASSP 1994, Minneapolis, USA, 1993, vol. 4, pp. 153–156. [1006] J. Summers, R. Torres, and Y. Shimizu, “Statistical-acoustics models of energy decay in systems of coupled rooms and their relation to geometrical acoustics,” Journal of Acoustical Society of America, vol. 116(2), pp. 958–969, August 2004.

[1007] D. X. Sun and L. Deng, “Non-stationary hidden Markov models for speech recognition,” Mathematics and its Applications, vol. 80, pp. 161–182, May 1996. [1008] A. Swami and J. Mendel, “Cumulant-based approach to the harmonic retrieval and related problems,” IEEE Trans. on Signal Processing, vol. 39, no. 5, pp. 1099–1109, May 1991. [1009] A. Swami, G. Giannakis, and S. Shamsunder, “A unified approach to modeling multichannel ARMA processes using cumulants,” IEEE Trans. on Signal Processing, vol. 42, pp. 898–913, April 1994. [1010] A. Swami and P. Tichavsky, “Strong ergodicity conditions for the nth-order moment (cumulant) of multiple sinusoids,” Signal Processing, vol. 65, pp. 257–266, 1998. [1011] H. Szu, T. Yamakawa, and C. Hsu, “Visual image communication using advanced neural networks,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 121–126. [1012] F. Talantzis and D. B. Ward, “Robustness of multichannel equalization in acoustical reverberant environments,” Journal of Acoustical Society of America, vol. 114(2), pp. 833–841, 2003. [1013] F. Talantzis, D. B. Ward, and P. A. Naylor, “Expected performance of a family of blind source separation algorithms in a reverebrant room,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2004, ICASSP 2004, Montreal, Canada, May 17-21 2001. [1014] A. Taleb and C. Jutten, “Entropy optimization, application to blind source separation,” in ICANN, Lausanne, Switzeland, October 1997, pp. 529–534. [1015] A. Taleb and C. Jutten, “Non-linear source separation: the post-non-linear mixtures,” in ESANN’97, Bruges, Belgium, April 1997, pp. 279–284. [1016] A. Taleb, C. Jutten, and S. Olympieff, “Source separation in post nonlinear mixtures: An entropy-based algorithm,” in ICASSP’98, Seattle (WA), USA, 1998, pp. 2089–92. [1017] A. Taleb and Ch. Jutten, “Batch algorithm for source separation in postnonlinear mixtures,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 155–160. [1018] A. Taleb, J. Sole i Casals, and C. Jutten, “Blind inversion of Wiener systems,” in International work-conference on Artificial and Natural Networks, IWANN’99, Alicante, Spain, 2-4 June 1999. [1019] A. Taleb and C. Jutten, “Source separation in post nonlinear mixtures,” IEEE Trans. on Signal Processing, vol. 47, no. 10, pp. 2807–2820, October 1999. [1020] A. Taleb and G. Cirrincione, “Against the convergence of the minor component analysis neurons,” IEEE-NN, vol. 10, no. 1, pp. 207, January 1999. [1021] A. Taleb, Séparation de sources dans des mélanges post non-linéaires, Ph.D. thesis, Inpg, 1999, (In French). [1022] A. Taleb, J. Sole I. Casals, and C. Jutten, “Quasi-nonparametric blind inversion of Wiener systems,” IEEE Tr. on SP, 1999, Submitted. [1023] A. Taleb, “An algorithm for the blind identification of n independent signals with 2 sensors,” in Sixth International Symposium on Signal Processing and its Applications (ISSPA 2001), M. Deriche, Boashash, and W. W. Boles, Eds., Kuala-Lampur, Malaysia, August 13-16 2001. [1024] A. Taleb, “A generic framework for blind source separation in structured nonlinear models,” IEEE Trans. on Signal Processing, vol. 50, no. 8, pp. 1819–1830, August 2002. [1025] Y. Tan, J. Wang, and J. M. Zurada, “Nonlinear blind source separation using a radial basis function network,” IEEE Trans. on Neural Networks, vol. 12, no. 1, pp. 124–134, January 2001. [1026] T. Tanaka, “A statistical-mechanics appraoch to large-system analysis of CDMA multiuser detectors,” IEEE Trans. on Information Theory, vol. 48, no. 11, pp. 2888–2910, November 2002. [1027] B. Tang, A. Shen, A. Alwan, and G. Pottie, “A perception based embedded subband speech coder,” IEEE Trans. on Speech and Audio Processing, vol. 5, no. 2, pp. 131–140, 1997. [1028] O. Tanrikulu and A. G. Constantinides, “A novel adaptive filtering algorithm utilising the kurtosis of the adaptation error,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [1029] M. Taroudakis, “Ocean acoustic tomography,” in Lecture Notes of the Tutorial Course fro Young Acousticians from European Countries, Gdansk, Poland, 23-24 June 2002. [1030] P. Tassi, Méthodes statistiques, Economica, Paris, 1989. [1031] R. L. Taylor and T. C. Hu, “Sub-gaussian techniques in proving strong laws of large numbers,” The teaching of Mathematics, pp. 295–299, 1987. [1032] F. J. Theis, C. Puntonet, and E. W. Lang, “Nonlinear geometric ICA,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 275–280. [1033] F. J. Theis, E. W. Lang, and C. G. Puntonet, “A geometric algorithm for overcomplete linear ica,” NeuroComputing, , no. 56, pp. 381–398, 2004. [1034] R. Théodor, Initiation ` a l’analyse numérique, Masson, Paris, 1984, 3 éme édition. [1035] C. W. Therrien, Discrete random signals and satistical signal processing, Prentice-Hall International Editions, 1992.

[1036] J. Thiemann, Acoustic noise suppression for speech signals using auditory masking effects, Ph.D. thesis, Department of Electrical & Computer Engineering, McGill University, Canada, July 2001. [1037] N. Thirion, J. Mars, and J. L. Lacoume, “Séparation aveugle de signaux large bande: Un nouveau challenge en prospection sismique,” in Actes du XVème colloque GRETSI, Juan-Les-Pins, France, 18-21 September 1995, pp. 1335–1338. [1038] N. Thirion, Séparation d’ondes en prospection sismique, Ph.D. thesis, CEPHAG, INPG Grenoble, 1995. [1039] N. Thirion, J. Mars, and J. L. Boelle, “Separation of seismic signals: A new concept based on a blind algorithm,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 85–88, Elsevier. [1040] N. Thirion, J. Mars, and J. L. Boelle, “Analytical links between steering vectors and eigenvectors,” in Signal Processing VIII, Theories and Applications (EUSIPCO’96), Triest, Italy, September 1996, pp. 81–84, Elsevier. [1041] N. Thirion and E. Moreau, “Generalized criteria for blind multivariante signal equalization,” IEEE Signal Processing Letters, vol. 9, no. 2, pp. 72–74, February 2002. [1042] L. Tong, Y. F. Soon, V. C.and Huang, and R. Liu, “Amuse: An algorithm for multiple unkown signal extraction,” in Proc. IEEE ISCAS, New Orleans, 1990, pp. 1365–1368. [1043] R. L. L. Tong and Y. H. V. C. Soon, “Indeterminacy and identifiability of blind identification,” IEEE Trans. on CAS, vol. 38, pp. 499–509, May 1991. [1044] L. Tong, G. Xu, and T. Kailath, “A new approach to blind identification and equalization of multipath channels,” in The 25th Asilomar Conference, Pacific Grove, 1991, pp. 856–860. [1045] L. Tong, S. Yu, Y. Inouye, and R. Liu, “A necessary and sufficient condition on blind identification,” in Proc. IEEE Signal Processing Workshop on Higher-Order Statistics, Chamrousse, France, June 1991, pp. 261–264. [1046] L. Tong, Y. Inouye, and R. W. Liu, “Waveform-preserving blind estimation of multiple independent sources,” IEEE Trans. on Signal Processing, vol. 41, no. 7, pp. 2461–2470, July 1993. [1047] L. Tong, Xu G., and T. Kailath, “Fast blind equalization via antenna arrays,” in Proceedings of International Conference on Speech and Signal Processing 1994, ICASSP 1994, Minneapolis, USA, 1993, vol. 4, pp. 272–275. [1048] L. Tong, G. Xu, and T. Kailath, “Blind identification and equalization based on second-order statistics: A time domain approach,” IEEE Trans. on Information Theory, vol. 40, no. 2, pp. 340–349, March 1994. [1049] D. J. Tong and S. perreau, “Multichannel blind identification from subspace to maximum liklehood methods,” IEE Proceedings-F, vol. 86, no. 10, pp. 1951–1968, Octobre 1998. [1050] K. Torkkola, “Blind separation of convolutive sources based on information maximization,” in IEEE Workshop on Neural Networks for Signal Processing VI, Kyoto, Japan, September 1996, pp. 423–432. [1051] M. Torlak and G. Xu, “Blind multiuser channel estimation in asynchronous CDMA signals,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 137–147, January 1997. [1052] M. K. Tsatsanis, “Inverse filtering criteria for CDMA signals,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 102–112, January 1997. [1053] M. K. Tsatsanis and G. B. Giannakis, “Subspace methods for blind estimation of time-varying FIR channels,” IEEE Trans. on Signal processing, vol. 40, no. 12, pp. 3084–3093, December 1997. [1054] D. W. Tufts and R. Kumaresan, “Singular value decomposition and improved frequency estimation using linear prediction,” IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. ASSP-30, no. 4, pp. 671–675, August 1982. [1055] D. W. Tufts and R. Kumaresan, “Estimation of frequencies of multiple sinusoids: Making linear prediction perform like maximum likelihood,” Proceedings of the IEEE, vol. 70, no. 9, pp. 975–989, September 1982. [1056] H. H. Yang, S. I. Amari, and A. Cichocki, “Adaptive blind separation of convolutive mixtures of independent linear signals,” Signal Processing, vol. 73, pp. 139–152, 1999. [1057] M. Unser, A. Aldroubi, and M. Eden, “B-spline signal processing: Part i-theory,” IEEE Trans. on Signal Processing, vol. 41, no. 2, pp. 821–832, February 1993. [1058] M. Unser and T. Blu, “Wavelet theory demystified,” IEEE Trans. on Signal Processing, vol. 51, no. 2, pp. 470–483, February 2003. [1059] R. L´ opez-Valcarce and S. Dasgupta, “Blind channel equalization with colored sources based on second-order statistics: A linear prediction approach,” IEEE Trans. on Signal Processing, vol. 49, no. 9, pp. 2050–2059, September 2001. [1060] R. L´ opez-Valcarce and S. Dasgupta, “Blind equalization of nonlinear channels from second-order statistics,” IEEE Trans. on Signal Processing, vol. 49, no. 12, pp. 3084–3097, December 2001. [1061] S. Vallez, A. Martin, C. Gervaise, A. Mansour, and A. Khenchaf, “Contribution to passive acoustic ocean tomographypart IV: A data fusion strategy for blind source separation and classification,” in IEEE Conference & Exhibition OCEANS’05 Europe, Brest, France, 2005, p. To appear. [1062] H. Valpola, A. Honkela, and J. Karhunen, “Nonlinear static and dynamic blind source separation using ensemble learning,” in Int. Joint Conf. on Neural Networks, IJCNN’01, Washington D.C., USA, 2001, pp. 2750–2755. ¨ [1063] H. Valpola, T. Ostman, and J. Karhunen, “Nonlinear independent factor analysis by hierarchical models,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 257–262.

[1064] D. Van Compernolle, “Switching adaptive filters for enhancing noisy and reverberant speech from microphone array recordings,” in Proceedings of International Conference on Speech and Signal Processing 1990, ICASSP 1990, Albuquerque, USA, April 3-6 1990, pp. 833–836. [1065] P. Vandaele and M. Moonen, “An SVD + Viterbi algorithm for multiuser adaptive blind equalization of mobile radio channels,” IEEE Signal Processing Letters, vol. 6, no. 10, pp. 260–264, October 1999. [1066] A. J. Van Der Veen, S. Talwar, and A. Paubray, “Blind identification of FIR channels carrying multiple finite alphabet signals,” in Proceedings of International Conference on Speech and Signal Processing 1994, ICASSP 1994, 1995, pp. 1213–1216. [1067] A. van der Veen and A. Paulraj, “An analytical constant modulus algorithm,” IEEE Trans. Signal Processing, vol. 44, no. 5, pp. 1136–1155, May 1996. [1068] A. van der Veen, “Analytical method for blind binary signal separation,” IEEE Trans. Signal Processing, vol. 45, no. 4, pp. 1078–1082, April 1997. [1069] A. J. Van Der Veen, “Blind separation of BPSK sources with residual carriers,” Signal Processing, vol. 73, no. 1, pp. 67–79, 1999. [1070] S. Van Gerven and D. Van Compernolle, “Feedforward and feedback in a symmetric adaptive noise canceller: stability analysis in a simplified case,” in Signal Processing VI, Theories and Applications (EUSIPCO’92), J. Vandewalle, R. Boite, M. Moonen, and A. Oosterlinck, Eds., Brussels, Belgium, August 1992, pp. 1081–1084, Elsevier. [1071] S. Van Gerven, D. Van Compernolle, L. Nguyen Thi, and C. Jutten, “Blind separation of sources: A comparative study of a 2nd and a 4th order solution,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 1153–1156, Elsevier. [1072] S. Van Gerven and D. Van Compernolle, “Signal separation by symmetric adaptive decorrelation: Stability, convergence, and uniqueness,” IEEE Trans. on Signal Processing, vol. 43, no. 7, pp. 1602–1612, July 1995. [1073] S. Van Gerven., Adaptive noise cancellation and signal separation with applications to speech enhancement, Ph.D. thesis, K.U.Leuven, E.S.A.T., Belgium, March 1996. [1074] R. Van Nee and R. Prasad, OFDM for wireless multimedia communications, Artech House Publishers, 2000. [1075] H. L. Van Trees, Detection, estimation, and modulation theory: part I detection, estimation, and linear modulation theory, John Wiley and Sons, Inc. New York, 1977. [1076] S. Vembu, S. Verdu, R. A. Kennedy, and W. sethares, “Convex cost functions in blind equalization,” IEEE Trans. on Signal Processing, vol. 42, no. 8, pp. 1952–1960, August 1994. [1077] W. Verhelst, “Overlap-add methods for time-scaling of speech,” Speech Communication, vol. 30, pp. 207–221, 2000. [1078] R. Vetter, J.-M. Vesin, P. Celka, and U. Scherrer, “Observer of the human cardiac sympathetic nerve activity using noncausal blind source separation,” IEEE Trans. on Biomedical Engineering, vol. 46, pp. 322–330, March 1999. [1079] R. Vetter, J.-M. Vesin, P. Celka, and U. Scherrer, “Observer of the autonomic cardiac outflow in humans using non-causal blind source separation,” in First International Workshop on Independent Component Analysis and Signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 161–166. [1080] R. Vetter, J.-M. Vesin, P. Celka, and U. Scherrer, “Blind source separation in highly noisy environments,” in First International Workshop on Independent Component Analysis and Signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 161–166. [1081] R. Vetter, N. Virag, J.-M. Vesin, P. Celka, and U. Scherrer, “Observer of autonomic cardiac outflow based on blind source separation of ECG parameters,” IEEE Trans. on Biomedical Engineering, vol. 47, no. 5, pp. 578–582, May 2000. [1082] M. Viberg and A. L. Swindlehurst, “A bayesian approach to auto-calibration for parametric array signal processing,” IEEE Trans. on Signal Processing, vol. 42, December 1994. [1083] J. Vidal, V. Codony, J. R. Fonollosa, and J. A. R. Fonollosa, “Multivariate fractionally-spaced system identification and equalization,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. [1084] J. Vidal, A. Bonafonte, A. R. Fonollosa, and N. F. De Losada, “Parametric modeling of PDF using a convolution of one-sided exponentials: Application to HMM,” in Signal Processing VII, Theories and Applications (EUSIPCO’94), M.J.J. Holt, C.F.N. Cowan, P.M. Grant, and W.A. Sandham, Eds., Edinburgh, Scotland, September 1994, pp. 54–57, Elsevier. [1085] E. Vittoz and X. Arreguit, “CMOS integration of Hérault-Jutten cells for separation of sources,” in Workshop on Analog VLSI and Neural Systems, Portland, USA, May 1989. [1086] B. Vrcelj and P. P. Vaidyanathan, “Efficient implementation of the all-digital interpolation,” IEEE Trans. on Image Processing, vol. 10, no. 11, pp. 1639–1646, November 2001. [1087] F. Vrins and M. Verleysen, “Information theoretic versus cumulant-based contrasts for multimodal source separation,” IEEE Signal Processing Letters, vol. 12, no. 3, pp. 190–193, March 2005. [1088] J. L. Vuattoux and E. Le Carpentier, “Non-causal ARMA model identification by maximizing the kurtosis,” in Signal Processing on Higher Order Statistics, Banff, Alberta, Canada, July 1997, pp. 234–238. [1089] A. K. Wang and W. Ren, “Convergence analysis of the filtered-U algorithm for active noise control,” Signal Processing, vol. 73, pp. 255–266, 1999.

[1090] L. Wang and J. S. Lim, “The unimportance of phase in speech enhancement,” IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. ASSP-30, no. 4, pp. 679–681, August 1982. [1091] L. Wang and J. M. Mendel, “Adaptive eigensubspace algorithms for direction or frequency estimation and tracking,” IEEE Trans. on Acoustics, Speech and Signal Processing, vol. ASSP-36, no. 2, pp. 241–251, February 1988. [1092] L. Wang and J. M. Mendel, “Cumulant-based parameter estimation using neural networks,” IEEE, pp. 2369–2372, 1990. [1093] X. Wang and H. V. Poor, “Blind adaptive multiuser detection in multipath CDMA channels based on subspace tracking,” IEEE Trans. on Signal Processing, vol. 46, no. 11, pp. 3030–3044, November 1998. [1094] Y. Y. Wang, J. T. Chen, and W. H. fang, “TST-Music for joint DOA-delay estimation,” IEEE Trans. on Signal Processing, vol. 49, no. 4, pp. 721–729, April 2001. [1095] E. Weinstein, M. Feder, and A. V. Oppenheim, “Multi-channel signal separation by decorrelation,” IEEE Trans. on Speech, and Audio Processing, vol. 1, no. 4, pp. 405–414, October 1993. [1096] K. Waheed, K. Desai, and Salem; F. M., “Blind multi user detection in DS-CDMA systems using natural grafient based symbol recovery structures,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 727–732. [1097] B. Widrow and S. D. Stearns, Adaptive signal processing, Prentice-Hall, New Jersey, 1985. [1098] R.. Wiley, Electronic Intelligence: The analysis of radar signals, Artech House, 1993. [1099] E. Wilczok, “New uncertainty principles for the continuous gabor transform and the continuous wavelet transform,” Documenta Math, vol. 5, pp. 201–226, 2000. [1100] J. O. Wisbeck, A. Kardec Barros, and R. G. Ojeda, “Application of ICA in the separation of brething artifacts in ECG signals,” in Fifth International Conference on Neural Information Processing, S. Usui and T. Omori, Eds., Kitakyushu, Japan, 21-23 October 1998. [1101] T. F. Wong, T. M. Lok, J. S. Lehnert, and M. D. Zoltowski, “A linear receiver for direct-sequence spread-spectrum multiple-access systems with antenna arrays and blind adaptation,” IEEE Signal Trans on Processing Letters, vol. 44, no. 2, pp. 659–676, March 1998. [1102] H. Wu, M. Siegel, and P. Khosla, “Vehicle sound signature recognition by frequency vector pricipal component analysis,” in IEEE Instrumentation and Measurement Technology Conference, St. Paul Minnesota, USA, May 18-20 1998, pp. 2025– 2028. [1103] H. C. Wu and J. C. Principe, “Simultaneous diagonalization in the frequency domain (SDIF) for source separation,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 245–250. [1104] T. Wysocki, H. Razavi, and B. Honary, Digital signal processing for communication systems, Kluwer Academic Publishers, Boston, 1997. [1105] J. Xavier and V. Barroso, “An analytical solution for 2nd order statistics based blind MIMO channel identification,” in IEEE third conference on Telecommunications, April 2001. [1106] J. Xi and J. P. Reilly, “Blind separation of signals in a convolutive environment,” in Proceedings of International Conference on Speech and Signal Processing 1997, ICASSP 1997, Munich, Germany, 1997, pp. 1327–1331. [1107] L. Xu, C. C. Cheung, and S. I. Amari, “Learned parametric mixture based ICA algorithm,” NeuroComputing, , no. 22, pp. 69–80, 1998. [1108] L. Xu, “Bayesian Kullback Ying-Yang dependence reduction theory,” NeuroComputing, , no. 22, pp. 81–111, 1998. [1109] I. Yamada and T. Ezaki, “An orthogonal matrix optimization by dual cayley parametrization technique,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 35–40. [1110] G. Yan and H. Fan, “A Newton-like algorithm for complex variables with applications in blind equalization,” IEEE Trans. on Signal Processing, vol. 48, no. 2, pp. 553–556, February 2000. [1111] T. Yamaguchi, K. Hirokawa, and K. Itoh, “Independent component analysis by transforming a scatter diagram of mixtures of signals,” Optics Communications, , no. 173, pp. 107–114, 2000. [1112] T. Yamaguchi and K. Itoh, “An algebric solution to independent analysis,” Optics Communications, , no. 178, pp. 59–64, 2000. [1113] H. H. Yang and S. I. Amari, “Adaptive on-line learning algorithms for blind separation - maximum entropy and minimum mutual information,” Neural Computation, vol. 9, pp. 1457–1482, 1997. [1114] H. H. Yang, S. I. Amari, and A. Cichocki, “Information-theoritic approach to blind separation of sources in non-linear mixture,” Signal Processing, vol. 64, pp. 291–300, 1998. [1115] H. H. Yang, “On-line blind equalization via on-line blind separation,” Signal Processing, vol. 68, pp. 271–281, 1998. [1116] J. F. Yang and M. Kaveh, “Adaptive eigensubspace algorithms for direction or frequency estimation and tracking,” IEEE Trans. on Acoustics, Speech and Signal Processing, vol. ASSP-36, no. 2, pp. 241–251, February 1988. [1117] J. F. Yang, “Serial updating rule for blind separation derived from the method of scoring,” IEEE Trans. on Signal Processing, vol. 47, no. 8, pp. 2279–2285, August 1999.

[1118] Y. Yang and S. S. Soliman, “An improved moment-based algorithm for signal classification,” Signal Processing, vol. 43, pp. 231–244, 1995. [1119] D. Yellin and E. Weinstein, “Criteria for multichannel signal separation,” IEEE Trans. on Signal Processing, vol. 42, no. 8, pp. 2158–2167, August 1994. [1120] D. Yellin and E. Weinstein, “Multichannel signal separation: Methods and analysis,” IEEE Trans. on Signal Processing, vol. 44, no. 1, pp. 106–118, January 1996. [1121] A. Yeredor, “Blind source separation via the second characteristic function,” Signal Processing, vol. 80, no. 5, pp. 897–902, May 2000. [1122] A. Yeredor, “Blind source separation using the second derivative of the characteristic function,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3136–3139. [1123] A. Yeredor, “Blind separation of gaussian sources via second-order statistics with asymptotically optimal weighting,” IEEE Signal Processing Letters, vol. 7, no. 7, pp. 197–200, Jully 2000. [1124] A. Yeredor, “Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation,” IEEE Trans. on Signal Processing, vol. 50, no. 7, pp. 1545–1553, July 2002. [1125] A. Yeredor, “TV-SOBI: An expansion of SOBI for linearly time-varying mixtures,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 903–908. [1126] N. Yousef and A. H. Sayed, “Ability of adaptive filters to track carrier offsets and channel nonstationarities,” IEEE Trans. on Signal Processing, vol. 50, no. 7, pp. 1533–1544, July 2002. [1127] A. Ypma and P. Pajunen, “Rotating machine vibration analysis with second-order independent component analysis,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 37–42. [1128] A. Ypma, A. Leshem, and R. P. W. Duin, “Blind separation of rotating machine sources: bilinear forms and convolutive mixtures,” Neuroomputing, p. To appear, 2002. [1129] V. Zarzoso and A. k. Nandi, “Blind separation od independent sources for virtually any source probability density function,” IEEE Trans. on Signal Processing, vol. 47, no. 9, pp. 2419–2432, September 1999. [1130] S. Zazo, Y. Blanco-Archilla, and J. M. P´ aez-Borrallo, “Order statistics: A new approach to the problem of blind sources separation,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 413–418. [1131] O. Zeitouni, J. Ziv, and N. Merhav, “When is the generalized likelihood ratio test optimal?,” IEEE Trans. on Information Theory, vol. 38, no. 5, pp. 1597–1602, September 1992. [1132] I. Zeldovitch and A. Mychkis, Eléments de mathématiques appliquées, Mir, Moscou, 1974. [1133] H. H. zeng and L. Tong, “Blind channel estimation using the second-order statistics: Algorithms,” IEEE Trans. on Signal Processing, vol. 45, no. 8, pp. 1919–1930, August 1997. [1134] H. H. zeng and L. Tong, “Blind channel estimation using the second-order statistics: Asymptotic performance and limitations,” IEEE Trans. on Signal Processing, vol. 45, no. 8, pp. 2060–2071, August 1997. [1135] H. S. Zhang, X. J. Liu, and T. Y Chai, “A new method for optimal deconvolution,” IEEE Trans. on Signal Processing, vol. 45, no. 10, pp. 2596–2599, October 1997. [1136] L. Q. Zhang, S. I. Amari, and A. Cichocki, “Natural gradient approach to blind separation of over- and under-complete mixtures,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 455–460. [1137] L. Q. Zhang, S. I. Amari, and A. Cichocki, “Natural gradient algorithm for blind separation of overdetermined mixture with additive noise,” IEEE Signal Processing Letters, vol. 6, no. 11, pp. 293–295, November 1999. [1138] L. Zhang and A. Cichocki, “Natrural gradient approach to blind deconvolution of dynamical systems,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 27–32. [1139] L. Zhang and M. Amin, “Blind separation of sources based on their time-frequency signatures,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2000, Istanbul, Turkey, Jun 2000, pp. 3128–3131. [1140] L. Zhang and W. Wei, “Blind adaptive multiuser detection based kalman filtering,” IEEE Trans. on Signal Processing, vol. 50, no. 1, pp. 87–95, January 2002. [1141] R. Zhang and M. Tsatsanis, “Over-complete blind source separation by applying sparse decomposition and information theoretic based probabilistic approach,” in Proceedings of International Conference on Acoustics Speech and Signal Processing 2001, ICASSP 2001, Salt Lake City, Utah, USA, May 7-11 2001. [1142] Y. Zhang, W. Mu, and M. G. Amin, “subspace analysis of spatial time-frequency distribution matrices,” IEEE Trans. on Signal Processing, vol. 49, no. 4, pp. 747–758, April 2001. [1143] Y. Zhang, M. G. Amin, and A. R. Lindsey, “Improved blind separations of nonstationary sources based on spatial time-frequency distributions,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 651–656.

[1144] Y. Zhang and S. A. Kassam, “Blind separation and equalization using fractional sampling of digital communications signals,” Signal Processing, vol. 81, pp. 2591–2608, 2001. [1145] Q. Zhao and L. Tong, “Adaptive blind channel estimation by least squares smoothing,” IEEE Trans. on Signal Processing, vol. 47, no. 11, pp. 3000–3012, November 1999. [1146] D. Zheng, J. Li, S. L. Miller, and E. G. Strom, “An efficient code-timing estimator for DS-CDMA signals,” IEEE Trans. on Signal Processing, vol. 45, no. 1, pp. 82–89, January 1997. [1147] S. Zhenghao and F. M. Fairman, “Harmonic retrieval via state space and fourth-order cumulants,” IEEE Trans. on Signal Processing, vol. 42, no. 5, pp. 1109–1119, 1994. [1148] J. Zhu, X. R. Cao, and Z. Ding, “An algebraic principle for the blind separation of white non-gaussian sources,” Signal Processing, vol. 76, pp. 105–115, 1999. [1149] M. Zibulevsky and B. Pearlmutter, “Blind separation of sources with sparse representations in a given signal dictionary,” in International Workshop on Independent Component Analysis and blind Signal Separation, Helsinki, Finland, 19-22 June 2000, pp. 181–186. [1150] M. Zibulevsky and Y. Y. Zeevi, “Extraction of a source from multichannel data using sparce decomposition,” NeuroComputing, , no. 49, pp. 163–173, 2002. [1151] M. Zibulevsky, “Blind source separation with relative newton method,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 897–902. [1152] C. Ziegaus and E. W. Lang, “Independent componenet extraction of natural images baesd on fourth-order cumulants,” in First International Workshop on Independent Component Analysis and signal Separation (ICA99), J. F. Cardoso, Ch. Jutten, and Ph. loubaton, Eds., Aussois, France, 11-15 January 1999, pp. 115–120. [1153] A. Ziehe, M. Kawanabe, S. Harmeling, and K.-R. Mueller, “Blind separation of post-nonlinear mixtures using gaussianizing transformations and temporal decorrelation,” in 4th International Workshop on Independent Component Analysis and blind Signal Separation, ICA2003, Nara, Japan, 1-4 April 2003, pp. 269–274. ˘ [1154] V. Zivojnovi´ c, “Moment contrained Shannon and Fisher information: Analysis and application to blind identification,” in Proc. 3rd Workshop on Higher Order Statistics, Edinburgh, Scotland, September 1994. ˘ [1155] V. Zivojnovi´ c, “Higher-order statistics and huber’s robustness,” in Proc. IEEE-ATHOS Workshop on Higher-Order Statistics (HOS’95), Girona-Spain, 12-14 June 1995, pp. 236–240. [1156] J. P. Zubelli, R. G. F. T´ avora, M. A. Grivet Mattoso Maia, and E. L. Pinto, “An algorithm for deinterleaving pulse train using the fast wavelet packet transform,” in Prov. of the Brasilian Symposium of Telecommunications, Recife, Brasil, 1997.

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