DocumentCode :
1856011
Title :
Novel dependence measure for dependent component analysis
Author :
Shaoquan Yu ; Shizhong Zhang ; Fasong Wang ; Hongwei Li
Author_Institution :
Sch. of Math. & Phys., China Univ. of Geosci., Wuhan, China
Volume :
3
fYear :
2012
fDate :
21-25 Oct. 2012
Firstpage :
2313
Lastpage :
2317
Abstract :
The purpose of this paper is to develop nonparametric blind signal separation (BSS) algorithm for linear dependent source signals, which is proposed under the framework of contrast method as in independent component analysis (ICA). The contrast function is derived from the Schweizer-Wolff measure of pairwise dependence between the variables. Simulation results show that the proposed algorithm is able to separate the dependent signals and yield ideal performance.
Keywords :
blind source separation; independent component analysis; BSS algorithm; ICA; Schweizer-Wolff measure; contrast function; dependent component analysis; independent component analysis; linear dependent source signals; nonparametric blind signal separation algorithm; pairwise dependence; Schweizer-Wolff measure; dependent component analysis (DCA); independent component analysis (ICA); mutual information (MI);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location :
Beijing
ISSN :
2164-5221
Print_ISBN :
978-1-4673-2196-9
Type :
conf
DOI :
10.1109/ICoSP.2012.6492043
Filename :
6492043
Link To Document :
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