A new approach to underdetermined blind source separation using sparse representation

Authors:
Hai-Lin Liu;Jia-Xun Hou
Affiliations:
Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou, China;Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou, China
Venue:
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Year:
2007

Citing 4
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Underdetermined blind source separation based on sparse representation

IEEE Transactions on Signal Processing

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Abstract

This paper presents a new approach to blind separation of sources using sparse representation in an underdetermined mixture. Firstly, we transform the observations into the new ones within the generalized spherical coordinates, through which the estimation of the mixing matrix is formulated as the estimation of the cluster centers. Secondly, we identify the cluster centers by a new classification algorithm, whereby the mixing matrix is estimated. The simulation results have shown the efficacy of the proposed algorithm.