DocumentCode
2630883
Title
Blind signal separation by an evolutionary neural network with higher-order statistics
Author
Chen, Yen-wei ; Zeng, Xiang-Yan ; Nakao, Zensho
Author_Institution
Fac. of Eng., Ryukyus Univ., Okinawa, Japan
Volume
2
fYear
2000
fDate
2000
Firstpage
566
Abstract
The authors propose an evolutionary neural network for blind source separation (BSS). In the proposed method, the separating matrix is used as connection weights of the network, which are updated by a genetic algorithm (GA). A higher-order statistics of kurtosis, which is a simple and original criterion for independence, is used as a fitness function. The applicability of the proposed method for blind source separation is demonstrated by simulations
Keywords
genetic algorithms; higher order statistics; neural nets; signal processing; BSS; GA; blind signal separation; blind source separation; connection weights; evolutionary neural network; fitness function; genetic algorithm; higher-order statistics; kurtosis; separating matrix; Blind source separation; Data models; Entropy; Genetic algorithms; Higher order statistics; Independent component analysis; Mutual information; Neural networks; Signal processing algorithms; Source separation;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on
Conference_Location
Brighton
Print_ISBN
0-7803-6400-7
Type
conf
DOI
10.1109/KES.2000.884112
Filename
884112
Link To Document