Summary
2011 International Symposium on Nonlinear Theory and Its Applications
2011
Session Number:B4L-D
Session:
Number:B4L-D2
A Blind Signal Separation Method Using Particle Swarm Optimization
Masanori KIMOTO, Dai YAMANAKA, Kenya JIN’NO,
pp.560-563
Publication Date:2011/9/4
Online ISSN:2188-5079
Summary:
In this paper, we propose a novel blind signal separation (BSS) algorithm based on particle swarm optimization (PSO). PSO is a stochastic optimization technique inspired by social behavior of bird frocking or fish schooling. It can search for the optimum solution of a given evaluation function by comparatively rapid. In the proposed method, each element of separation matrix in BSS are estimated by PSO. The evaluation function are used by "Distribution error between the source signal and the separation signal" and "Cross-correlation value between separation signals". We will show that the effectiveness of the proposed method by using numerical example of simulation.