BLIND SEPARATION OF CONVOLUTIVE MIXTURES A CONTRAST-BASED JOINT DIAGONALIZATION APPROACH

Blind Separation of convolutive mixtures and Blind Equalization of Multiple-Input Multiple-Output (MIMO) channels are two different ways of naming the same problem, which we address here. The numerical algorithm, subsequently presented in detail, is based on theoretical results on contrasts recently published by the authors [1]. This algorithm consists of Partial Approximate Joint Diagonalization (PAJOD) of several matrices, containing some values of output cumulant multi-correlations.

[1]  C.B. Papadias,et al.  A multi-user Kurtosis algorithm for blind source separation , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[2]  Jitendra K. Tugnait,et al.  Identification and deconvolution of multichannel linear non-Gaussian processes using higher order statistics and inverse filter criteria , 1997, IEEE Trans. Signal Process..

[3]  Ehud Weinstein,et al.  Criteria for multichannel signal separation , 1994, IEEE Trans. Signal Process..

[4]  Eric Moreau,et al.  A generalization of joint-diagonalization criteria for source separation , 2001, IEEE Trans. Signal Process..

[5]  Ehud Weinstein,et al.  New criteria for blind deconvolution of nonminimum phase systems (channels) , 1990, IEEE Trans. Inf. Theory.

[6]  D. Donoho.  ON MINIMUM ENTROPY DECONVOLUTION , 1981 .

[7]  P. Comon,et al.  Contrasts for multichannel blind deconvolution , 1996, IEEE Signal Processing Letters.

[8]  Nathalie Delfosse,et al.  Adaptive blind separation of independent sources: A deflation approach , 1995, Signal Process..

[9]  Inbar Fijalkow,et al.  Fractionally spaced equalization using CMA: robustness to channel noise and lack of disparity , 1997, IEEE Trans. Signal Process..

[10]  Ananthram Swami,et al.  Multichannel ARMA processes , 1994, IEEE Trans. Signal Process..

[11]  Pierre Comon,et al.  Blind MIMO equalization and joint-diagonalization criteria , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Antoine Souloumiac,et al.  Jacobi Angles for Simultaneous Diagonalization , 1996, SIAM J. Matrix Anal. Appl..

[13]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[14]  P. Comon.  Independent Component Analysis , 1992 .

[15]  O. Grellier,et al.  Analytical blind identification of a SISO communication channel , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).

[16]  Pierre Comon,et al.  Tensor Decompositions, State of the Art and Applications , 2002 .

[17]  C. Jutten,et al.  Blind source separation of convolutive mixtures by maximization of fourth-order cumulants: the non i.i.d. case , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).

[18]  Arogyaswami Paulraj,et al.  An analytical constant modulus algorithm , 1996, IEEE Trans. Signal Process..

[19]  Gene H. Golub,et al.  Matrix computations , 1983 .

[20]  Philippe Loubaton,et al.  Prediction error method for second-order blind identification , 1997, IEEE Trans. Signal Process..

[21]  E. Moreau,et al.  New criteria for blind signal separation , 2000, Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496).