DocumentCode
1896775
Title
A generalized least squares approach to blind separation of sources which have variance dependencies
Author
Shimizu, Shogo ; Hyvarinen, Aapo ; Kano, Yusuke
fYear
2005
fDate
17-20 July 2005
Firstpage
1080
Lastpage
1083
Abstract
We discuss the blind source separation problem where the sources are not independent but are dependent only through their variances. Some estimation methods have been proposed on this line. However, most of them require some additional assumptions, a parametric model for their dependencies or a temporal structure of the sources, for example. In this article, we propose a generalized least squares approach to the blind source separation problem in the general case where those additional assumptions do not hold
Keywords
blind source separation; least squares approximations; matrix algebra; blind source separation; generalized least squares approach; temporal structure; Autocorrelation; Blind source separation; Educational products; Independent component analysis; Information technology; Least squares methods; Maximum likelihood estimation; Parametric statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location
Novosibirsk
Print_ISBN
0-7803-9403-8
Type
conf
DOI
10.1109/SSP.2005.1628756
Filename
1628756
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