Title :
A generalized least squares approach to blind separation of sources which have variance dependencies
Author :
Shimizu, Shogo ; Hyvarinen, Aapo ; Kano, Yusuke
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;
Conference_Titel :
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location :
Novosibirsk
Print_ISBN :
0-7803-9403-8
DOI :
10.1109/SSP.2005.1628756