Blind Source Separation Based on Chaotic Immune Genetic Algorithm with High-order Cumulate

Author

Wang, Kun ; Zhang, Wei

Author_Institution

Xi´´an Aerotech. Coll., Xi´´an

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

139

Lastpage

143

Abstract

A blind source separation method based on chaotic immune genetic algorithm (CIGA) is proposed. The first step performs pretreatment of mixed signal, which mainly finishes whitening and centering by eigenvalue decomposition. The second step performs separation of sources and estimate of separate matrix. The separate matrix is updated by CIGA and high order statistics, where object function is based on the transformation of high order statistics of Kurtosis. The applicability of proposed method for blind source separation is demonstrated by simulation.

Keywords

blind source separation; eigenvalues and eigenfunctions; genetic algorithms; matrix algebra; statistical analysis; blind source separation; chaotic immune genetic algorithm; eigenvalue decomposition; high order statistics; separate matrix; Blind source separation; Chaos; Chaotic communication; Eigenvalues and eigenfunctions; Erbium; Genetic algorithms; Signal processing; Signal processing algorithms; Source separation; Statistics; Blind source separation; Chaotic immune genetic algorithm (CIGA); Eigenvalue decomposition; Kurtosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Electronics and Safety, 2006. ICVES 2006. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

1-4244-0759-1

Electronic_ISBN

1-4244-0759-1

Type

conf

DOI

10.1109/ICVES.2006.371570

Filename

4234006