An algebraic non orthogonal joint block diagonalization algorithm for blind separation of convolutive mixtures of sources

Authors:
Hicham Ghennioui;El Mostafa Fadaili;Nadège Thirion-Moreau;Abdellah Adib;Eric Moreau
Affiliations:
STD, ISITV, La Valette du Var Cedex, France and GSCM-LRIT, FSR, Rabat, Maroc;IBISC, CNRS FRE , F-91020 Evry-Courcouronnes, France;STD, ISITV, La Valette du Var Cedex, France;GSCM-LRIT, FSR, Rabat, Maroc and DPG, IS, Rabat, Maroc;STD, ISITV, La Valette du Var Cedex, France
Venue:
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Year:
2007

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Abstract

This paper deals with the problem of the blind separation of convolutive mixtures of sources. We present a novel method based on a new non orthogonal joint block diagonalization algorithm (NO - JBD) of a given set of matrices. The main advantages of the proposed method are that it is more general and a preliminary whitening stage is no more compulsorily required. The proposed joint block diagonalization algorithm is based on the algebraic optimization of a least mean squares criterion. Computer simulations are provided in order to illustrate the effectiveness of the proposed approach in three cases: when exact block-diagonal matrices are considered, then when they are progressively perturbed by an additive Gaussian noise and finally when estimated correlation matrices are used. A comparison with a classical orthogonal joint block-diagonalization algorithm is also performed, emphasizing the good performances of the method.