Presentation 2000/6/15
NLP2000-26 / NC2000-20 Blind source separation based on higher-order statistics with a genetic algorithm
Xiang-Yan Zeng, Yen-Wei Chen, Zensho Nakao,
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Abstract(in English) In this paper, we propose a genetic algorithm for blind source separation(BSS). BSS is the problem to obtain the independent original sources from mixed signals by independent component analysis(ICA). Many neural learning algorithms have been proposed for ICA. The effectiveness of these algorithms, however, is affected by the neuron activation functions that depend on the probability distribution of the signals. Our method does not need activation functions and works on evolutionary mechanism. The kurtosis that is a simple and original criterion for independence is used in the fitness function of GA. The applicability of the proposed method for blind source separation is demonstrated by the simulation results.
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Keyword(in English) Blind source separation / Independent component analysis / Genetic algorithm / Kurtosis
Paper # NLP2000-26,NC2000-20
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Committee NLP
Conference Date 2000/6/15(1days)
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Registration To Nonlinear Problems (NLP)
Language ENG
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Title (in English) NLP2000-26 / NC2000-20 Blind source separation based on higher-order statistics with a genetic algorithm
Sub Title (in English)
Keyword(1) Blind source separation
Keyword(2) Independent component analysis
Keyword(3) Genetic algorithm
Keyword(4) Kurtosis
1st Author's Name Xiang-Yan Zeng
1st Author's Affiliation Department of Electrical & Electronics Engineering, Faculty of Engineering, University of the Ryukyus()
2nd Author's Name Yen-Wei Chen
2nd Author's Affiliation Department of Electrical & Electronics Engineering, Faculty of Engineering, University of the Ryukyus
3rd Author's Name Zensho Nakao
3rd Author's Affiliation Department of Electrical & Electronics Engineering, Faculty of Engineering, University of the Ryukyus
Date 2000/6/15
Paper # NLP2000-26,NC2000-20
Volume (vol) vol.100
Number (no) 124
Page pp.pp.-
#Pages 7
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