A robust algorithm for convolutive blind source separation in presence of noise - École des Ponts ParisTech Access content directly
Journal Articles Signal Processing Year : 2013

A robust algorithm for convolutive blind source separation in presence of noise

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.
Fichier principal
Vignette du fichier
elsarticle-EFKM_Oct2011_revised.pdf (319.24 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01811756 , version 1 (11-06-2018)

Identifiers

Cite

M. El Rhabi, H. Fenniri, A. Keziou, E. Moreau. A robust algorithm for convolutive blind source separation in presence of noise. Signal Processing, 2013, 93 (4), pp.818 - 827. ⟨10.1016/j.sigpro.2012.09.026⟩. ⟨hal-01811756⟩
249 View
216 Download

Altmetric

Share

Gmail Facebook X LinkedIn More