Blind Separation of Instantaneous Mixed Gaussian Sources via Parallel Genetic Algorithms  

Oleh:

Tongcheng, Guo ; Chundi, Mu

Jenis: Article from Article
Dalam koleksi: Final Program and Book of Abstracts: The 4th Asian Control Conference, September 25-27, 2002 (Sep. 2002), page 2014-2019.
Topik: Blind Separation; Mixed Gaussian Sources; via Parallel; Genetic Algorithms
Fulltext: AC021689.PDF (129.32KB)

Isi artikel

A method for blind source separation (BSS) of instantaneous mixture of colored sources is proposed. It is based on minimizing a Gaussian mutual information criterion, leading to a second-order procedure, which amounts to jointly reducing a set of forward prediction error. Separation is shown to be achievable (up to a scaling and a permutation). Efficient real number genetic algorithms for the joint minimization of mean-squared prediction error are described. Furthermore, the efficiency and quality of optimization are improved by coarse-grained parallel computation. Some simulations are carried out to show good performance can be attained by a relative small prediction order.

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