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A blind source separation algorithm based on nonlinear function and simple particle swarm optimization
Received date: 2013-07-10
Revised date: 2013-10-17
Online published: 2014-07-15
A new blind source separation algorithm based on nonlinear function and simple particle swarm optimization was proposed, contraposing limitation problems for the source signal types and gaussian signal numbers. Nonlinear function was used as objective function based on source signal types, and then the simple particle swarm optimization was uesd to optimize the function. Simulation results show that the algorithm achieves the efficient separation for the blind source having various types of source signals and containing two gaussian signals. Compared with other algorithms, the proposed algorithm has fast convergence speed and high separation accuracy.
JIA Zhicheng , WANG Nana , CHEN Lei , ZHANG Yan . A blind source separation algorithm based on nonlinear function and simple particle swarm optimization[J]. Journal of University of Chinese Academy of Sciences, 2014 , 31(4) : 530 -536 . DOI: 10.7523/j.issn.2095-6134.2014.04.013
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