Abstract : We consider the blind source separation (BSS) problem in the noisy context. We propose a new methodology in order to enhance separation performances in terms of efficiency and robustness. Our approach consists in denoising the observed signals through the minimization of their total variation, and then minimizing divergence separation criteria combined with the total variation of the estimated source signals. We show by the way that the method leads to some projection problems that are solved by means of projected gradient algorithms. The efficiency and robustness of the proposed algorithm using Hellinger divergence are illustrated and compared with the classical mutual information approach through numerical simulations.
https://hal-enpc.archives-ouvertes.fr/hal-01811756
Contributeur : Mohammed El Rhabi
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Soumis le : lundi 11 juin 2018 - 12:17:57
Dernière modification le : samedi 9 mars 2019 - 01:23:37
Document(s) archivé(s) le : mercredi 12 septembre 2018 - 12:42:08
M. El Rhabi, H. Fenniri, A. Keziou, E. Moreau. A robust algorithm for convolutive blind source separation in presence of noise. Signal Processing, Elsevier, 2013, 93 (4), pp.818 - 827. ⟨10.1016/j.sigpro.2012.09.026⟩. ⟨hal-01811756⟩
