DocumentCode :
1808959
Title :
Temporal Bayesian Ying-Yang dependence reduction, blind source separation and principal independent components
Author :
Xu, Lei
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Volume :
2
fYear :
1999
fDate :
36342
Firstpage :
1071
Abstract :
A general recursive temporal BYY dependence reduction system, previously proposed by the author (1998), has been further re-elaborated systematically. Three new developments have been also made. A temporal independent component analysis (ICA) algorithm is proposed for separating blind sources from observations without sensor noise. The other two studies are for solving blind source separation problems with sensor noise of binary and real temporal sources, respectively. Moreover, the problem of how to determine principal independent components is addressed with criteria provided
Keywords :
Bayes methods; neural nets; noise; principal component analysis; signal resolution; temporal reasoning; ICA; TBYY dependence reduction; binary temporal sources; blind source separation; principal independent components; real temporal sources; recursive temporal BYY dependence reduction system; sensor noise; temporal Bayesian ying-yang dependence reduction; temporal independent component analysis; Algorithm design and analysis; Bayesian methods; Blind source separation; Computer science; Independent component analysis; Neural networks; Principal component analysis; Signal processing; Signal processing algorithms; Source separation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.831104
Filename :
831104
Link To Document :
بازگشت