DocumentCode
381213
Title
Blind separation of sources based on genetic algorithm
Author
Yue, Yufang ; Mao, Jianqin
Author_Institution
Seventh Res. Div., Beijing Univ. of Aeronaut. & Astronaut., China
Volume
3
fYear
2002
fDate
2002
Firstpage
2099
Abstract
Based on a genetic algorithm and variance normalization of output signals, this paper proposes two new methods for blind separation of sources. Simulation results illustrate that the method using a hybrid genetic algorithm not only keeps unsupervised, adaptive learning and the robust advantages of the known improved Herault-Jutten (H-J) (Jutten and Herault, 1991) algorithm, but also guarantees global convergence and less training time.
Keywords
convergence; genetic algorithms; signal processing; unsupervised learning; H-J algorithm; blind source separation; genetic algorithm; global convergence; output signal variance normalization; simulation; training time; unsupervised adaptive learning; Algorithm design and analysis; Automation; Convergence; Genetic algorithms; Independent component analysis; Intelligent control; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN
0-7803-7268-9
Type
conf
DOI
10.1109/WCICA.2002.1021455
Filename
1021455
Link To Document