Well-posedness of the permutation problem in sparse filter estimation with lp minimization
Combinatorics
2011-11-14 v1
Abstract
Convolutive source separation is often done in two stages: 1) estimation of the mixing filters and 2) estimation of the sources. Traditional approaches suffer from the ambiguities of arbitrary permutations and scaling in each frequency bin of the estimated filters and/or the sources, and they are usually corrected by taking into account some special properties of the filters/sources. This paper focusses on the filter permutation problem in the absence of scaling, investigating the possible use of the temporal sparsity of the filters as a property enabling permutation correction. Theoretical and experimental results highlight the potential as well as the limits of sparsity as an hypothesis to obtain a well-posed permutation problem.
Cite
@article{arxiv.1111.2848,
title = {Well-posedness of the permutation problem in sparse filter estimation with lp minimization},
author = {Alexis Benichoux and Prasad Sudhakar and Frédéric Bimbot and Rémi Gribonval},
journal= {arXiv preprint arXiv:1111.2848},
year = {2011}
}