郑州大学学报（工学版）2011，Vol.32Issue(1)：112-115,4.
基于负熵粒子群算法的盲信号分离研究
Blind Signal Separation Research Based on Negative Entropy Particle Swarm Optimization Algorithm
李希字 1叶苗 2邵明省1
作者信息
- 1. 鹤壁职业技术学院,电子信息工程系,河南,鹤壁,458030
- 2. 黄淮学院,电子科学与工程系,河南,驻马店,463000
- 折叠
摘要
Abstract
Aiming at the precocity in Particle Swarm Optimization (PSO) Algorithm, proposes the negative entropy PSO Algorithm. First the information negative entropy maximization as the objective function of PSO, without the other non-Gauss measure judgment, avoids distinguishing the aliasing matrix; Then carries on the centralization and albinism processing to the observation signal, causes between each signal component with the separation matrix adjustment the independence, the great weight makes the overall situation search, the small weight makes the partial search, the aliasing matrix completes the separation to all row element array; Finally it given the Algorithm . The MATLAB simulation result showed this Algorithm can complete the blind signal separation and the main parameter extraction effectively.关键词
负熵/粒子群/盲分离/最大化/惯性权重分类
信息技术与安全科学引用本文复制引用
李希字,叶苗,邵明省..基于负熵粒子群算法的盲信号分离研究[J].郑州大学学报（工学版）,2011,32(1):112-115,4.
