DocumentCode :
496676
Title :
A novel adaptive Independent Component Analysis algorithm
Author :
Xiaofei Shi ; Jidong Suo ; Li Li
Author_Institution :
Information Engineering College, Dalian Maritime University, 116026, Liaoning, China
fYear :
2006
fDate :
6-9 Nov. 2006
Firstpage :
1
Lastpage :
4
Abstract :
A novel adaptive Independent Component Analysis (NAICA) algorithm is proposed which can separate the mixture of super- and sub-Gaussian sources. Two novel models are proposed to estimate the probability density function of super- and sub-Gaussian sources respectively. In the framework of natural gradient, the parameters of two models are adaptively manipulated by online kurtosis learning. Applied to the mixture of images and speeches, experiments give good performance of NAICA algorithm.
Keywords :
ICA; adaptive; sub-Gaussian; super-Gaussian;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Wireless, Mobile and Multimedia Networks, 2006 IET International Conference on
Conference_Location :
hangzhou, China
ISSN :
0537-9989
Print_ISBN :
0-86341-644-6
Type :
conf
Filename :
5195628
Link To Document :
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