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›› 2014, Vol. 31 ›› Issue (4): 530-536.DOI: 10.7523/j.issn.2095-6134.2014.04.013

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A blind source separation algorithm based on nonlinear function and simple particle swarm optimization

JIA Zhicheng1, WANG Nana1, CHEN Lei2, ZHANG Yan1   

  1. 1. School of Information Engineering, Hebei University of Technology, Tianjin 300401, China;
    2. School of Information Engineering, Tianjin University of Commerce,Tianjin 300134, China
  • Received:2013-07-10 Revised:2013-10-17 Online:2014-07-15

Abstract:

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.

Key words: various types of source signal, nonlinear function, simple particle swarm optimization, blind source separation

CLC Number: