NDLI: A blind source separation method based on diagonalization of correlation matrices and genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Peng Zheng Yulin Liu Li Tian Yuqiang Cao
Copyright Year	2004
Description	Author affiliation: DSP Lab., Chongqing Commun. Inst., China (Peng Zheng; Yulin Liu; Li Tian; Yuqiang Cao)
Abstract	A new cost function based on diagonalization of the correlation matrices is proposed to measure the independency of output signals in this paper. In order to expand the search space and decrease the cross-correlation among the sub-sources, we propose to perform nonlinear transformation for the cost function. The real coded genetic algorithm is also proposed to search the optimum solution, which can overcome the drawbacks of traditional gradient search technique being likely tend to fall into local minimums. This novel method can be applicable to instantaneous or convolutive mixture models with stationary or non-stationary input signals. Simulation results demonstrate the algorithm not only has fast convergence performance and high accuracy, but also can improve the output SNR greatly.
Sponsorship	Zhejian Univ. Nat. Lab. of Ind. Control Technol. IEEE Robotics and Automation Soc. Nat. Natural Sci. Found. of China Chinese Assoc. of Automation
Starting Page	2127
Ending Page	2131
File Size	347611
Page Count	5
File Format	PDF
ISBN	0780382730
DOI	10.1109/WCICA.2004.1341961
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blind source separation Genetic algorithms Source separation Cost function Signal processing algorithms Statistics Decorrelation Covariance matrix Independent component analysis Biomedical signal processing
Content Type	Text
Resource Type	Article

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