Under-determined source separation: comparison of two approaches based on sparse decompositions - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2006

Under-determined source separation: comparison of two approaches based on sparse decompositions

Abstract

This paper focuses on under-determined source separation when the mixing parameters are known. The approach is based on a sparse decomposition of the mixture. In the proposed method, the mixture is decomposed with Matching Pursuit by introducing a new class of multi-channel dictionaries, where the atoms are given by a spatial direction and a waveform. The knowledge of the mixing matrix is directly integrated in the decomposition. Compared to the separation by multi-channel Matching Pursuit followed by a clustering, the new algorithm introduces less artifacts whereas the level of residual interferences is about the same. These two methods are compared to Bofill & Zibulevsky's separation algorithm and DUET method. We also study the effect of smoothing the decompositions and the importance of the quality of the estimation of the mixing matrix.
Fichier principal
Vignette du fichier
2006_ICA_LesageEtAl.pdf (93.01 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00544929 , version 1 (08-02-2011)

Identifiers

Cite

Sylvain Lesage, Sacha Krstulovic, Rémi Gribonval. Under-determined source separation: comparison of two approaches based on sparse decompositions. Proc. of the Int'l. Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2006), Mar 2006, Charleston, South Carolina, United States. pp.633--640, ⟨10.1007/11679363_79⟩. ⟨inria-00544929⟩
142 View
231 Download

Altmetric

Share

Gmail Facebook X LinkedIn More