计算机应用与软件2013，Vol.30Issue(4)：211-213,216,4.DOI:10.3969/j.issn.1000-386x.2013.04.060
混沌粒子群算法的盲源信号分离仿真研究
RESEARCH ON SIMULATING BLIND SOURCE SEPARATION BASED CHAOTIC PARTICLE SWARM OPTIMISATION
摘要
Abstract
Because traditional blind source separation algorithms have the defects of slow convergence, easily to fall into local optimum and so on, in this paper we propose a blind source separation algorithm based on chaos particle swarm optimisation. The kurtosis value of the signal is used as the objective function of the blind source signal separation, and then the chaos particle algorithm is used to solve the objective function, and the particle swarm is executed the chaos disturbance to keep the diversity of the particle swarm, finally the optimal solution is used to separate the blind source signal. Results show that the proposed algorithm improves the separation speed of blind source signal with higher separation accuracy.关键词
粒子群算法/盲源分离/独立分量分析/混沌Key words
Particle swarm optimisation/ Blind source separation/ Independent component analysis (ICA)/ Chaos分类
信息技术与安全科学引用本文复制引用
谢春明,肖露欣..混沌粒子群算法的盲源信号分离仿真研究[J].计算机应用与软件,2013,30(4):211-213,216,4.
