A Novel Method to Estimate the Unknown Mixing-Matrix for Blind Source Separation

Ning Chen; Hong Yi Zhang

doi:10.4028/www.scientific.net/AMR.605-607.2206

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 605-607A Novel Method to Estimate the Unknown...

A Novel Method to Estimate the Unknown Mixing-Matrix for Blind Source Separation

Abstract:

The blind source separation (BSS) using a two-stage sparse representation approach is discussed in this paper. We presented the algorithm based on linear membership function to estimate the unknown mixing matrix precisely, and then, the optimization algorithm based on integral to get the max value of the function is proposed. Another contribution described in this paper is the discussion of the impact of noise on the estimating the mixing matrix. Given the impact of noise, we set weights to put more emphasis on the more reliable data. Several experiments involving speech signals show the effectiveness and efficiency of this method.

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Periodical:

Advanced Materials Research (Volumes 605-607)

Pages:

2206-2210

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.605-607.2206

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Online since:

December 2012

Authors:

Ning Chen, Hong Yi Zhang

Keywords:

Blind Source Separation, Membership Function, Optimization Algorithm Based on Integral, Sparse Analysis

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