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
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;
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
DOI :
10.1109/KES.2000.884112
