Overdetermined blind source separation by gaussian mixture model

Authors:
Yujia Wang;Yunfeng Xue
Affiliations:
Department of Automation, Shanghai University of Engineering Science, Shanghai, PR China;School of Electronic and Electrical Engineering, Shanghai Second Polytechnic University, Shanghai, PR China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

Citing 5
Cited 0

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Abstract

The blind separation of overdetermined mixtures, i.e., the case where more sensors than sources are available is considered in this paper. The contrast function for overdetermined blind source separation problem is presented, together with its gradient. An iterative method is proposed to solve the overdetermined blind source separation problem, where Gaussian mixture model is used to estimate the density of the unknown sources. The result of simulation demonstrates the efficiency of the proposed algorithm.