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
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;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1021455
