Sparse source separation with unknown source number

Authors:
Yujie Zhang;Hongwei Li;Rui Qi
Affiliations:
School of mathematics and Physics China University of Geosciences, Wuhan;School of mathematics and Physics China University of Geosciences, Wuhan;School of sciences Naval University of Engineering Wuhan, China
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Year:
2010

Citing 5
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Abstract

Sparse Blind Source Separation (BSS) problems have recently received some attention. And some of them have been proposed for the unknown number of sources. However, they only consider the overdetermined case (i.e. with more sources than sensors). In the practical BSS, there are not prior assumptions on the number of sources. In this paper, we use cluster and Principal Component Analysis (PCA) to estimate the number of the sources and the separation matrix, and then make the estimation of sources. Experiments with speech signals demonstrate the validity of the proposed method.