A New Method Based on a Multi-Stage Algorithm for Blind Source Separation of Convolutive Mixtures

Xu Xian-feng; Feng Da-zheng

doi:10.3724/SP.J.1146.2008.01427

Volume 31 Issue 10

Dec. 2010

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Xu Xian-feng, Feng Da-zheng. A New Method Based on a Multi-Stage Algorithm for Blind Source Separation of Convolutive Mixtures[J]. Journal of Electronics & Information Technology, 2009, 31(10): 2455-2459. doi: 10.3724/SP.J.1146.2008.01427

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Xu Xian-feng, Feng Da-zheng. A New Method Based on a Multi-Stage Algorithm for Blind Source Separation of Convolutive Mixtures[J]. Journal of Electronics & Information Technology, 2009, 31(10): 2455-2459. doi: 10.3724/SP.J.1146.2008.01427

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A New Method Based on a Multi-Stage Algorithm for Blind Source Separation of Convolutive Mixtures

doi: 10.3724/SP.J.1146.2008.01427

Received Date: 2008-11-03
Rev Recd Date: 2009-03-23
Publish Date: 2009-10-19

Abstract

Abstract

A time-domain Multi-Stage Algorithm (MSA) based on the second order statistics for blind source separation of convolutive mixtures is proposed. Whitening procedure is adopted to transform the mixing matrix into a unitary matrix. The unitary matrix is expressed as a column-block matrix according to the block-diagonalization structure in autocorrelation matrices of source signals at different time delays. A novel least square tri-quadratic cost function with respect to a certain column block of the unitary matrix is proposed utilizing the orthogonality between each two different column blocks. Furthermore, a regular Triply Iterative Algorithm (TIA) following the gradient descent idea is used to seek the minimum point of the tri-quadratic cost function by alternately estimating one of the three independent variables parameter subsets, obtaining a column block of the unitary matrix. With each column block being got by using the systemic multi-stage algorithm, the unitary matrix can be estimated and then the source signals can be retrieved. Simulations results illustrate that, the new method outperforms the classic SUB method and the recently proposed JBD-NonU method, and can be efficiently applied to the blind source separation of convolutive mixtures.

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References

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