Blind source separation based on genetic algorithm

被引：2

作者：

College of Software, Hunan University, Changsha 410082, China ^{[1
]}

不详 ^{[2
]}

不详 ^{[3
]}

机构：

[1] College of Software, Hunan University

[2] College of Mathematics and Econometrics, Hunan University

[3] College of Computer and Communication, Hunan University

来源：

Jisuanji Yanjiu yu Fazhan | 2006年 / 2卷 / 244-252期

关键词：

Blind source separation; Genetic algorithm; Independent component analysis; Joint diagonalization;

D O I：

10.1360/crad20060209

中图分类号：

学科分类号：

摘要：

Recovering the unobserved source signals from their mixtures is a typical problem in array processing and data analysis. Independent component analysis (ICA) is a new and powerful method to solve this problem. JADE (joint approximate decomposition of eigen matrices) based on 4th-order cumulants is a common approach for ICA. However, it can only get approximate solution when k>2 and the results are not accurate. In this paper, a blind source separation based on genetic algorithm is proposed. The analysis and simulations suggest that the scheme is feasible and effective.

引用

页码：244 / 252

页数：8

共 16 条

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