FIR convolutive BSS based on sparse representation

Authors:
Zhaoshui He;Shengli Xie;Yuli Fu
Affiliations:
School of Electronics & Information Engineering, South China University of Technology, Guangzhou, China;School of Electronics & Information Engineering, South China University of Technology, Guangzhou, China;School of Electronics & Information Engineering, South China University of Technology, Guangzhou, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

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Abstract

Based on sparse representation, this paper discusses convolutive BSS of sparse sources and presents a FIR convolutive BSS algorithm that works in the frequency domain. This algorithm does not require that source signals be i.i.d or stationary, but require that source signals be sufficiently sparse in frequency domain. Furthermore, our algorithm can overcome permutation problem of frequency convolutive BSS method. For short-order FIR convolution, simulation shows good performance of our algorithm.