DocumentCode
2332421
Title
The Maximum Likelihood Approach to Complex ICA
Author
Cardoso, Jean-François ; Adali, Tulay
Author_Institution
ENST/TSI, Paris, France
Volume
5
fYear
2006
fDate
14-19 May 2006
Abstract
We derive the form of the best non-linear functions for performing independent component analysis (ICA) by maximum likelihood estimation. We show that both the form of nonlinearity and the relative gradient update equations for likelihood maximization naturally generalize to the complex case, and that they coincide with the real case. We discuss several special cases for the score function as well as adaptive scores.
Keywords
blind source separation; gradient methods; independent component analysis; matrix algebra; maximum likelihood estimation; complex ICA; independent component analysis; maximum likelihood estimation; nonlinear functions; relative gradient update equations; Argon; Higher order statistics; Independent component analysis; Matrix decomposition; Maximum likelihood estimation; Mutual information; Nonlinear equations; Probability density function; Random variables; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location
Toulouse
ISSN
1520-6149
Print_ISBN
1-4244-0469-X
Type
conf
DOI
10.1109/ICASSP.2006.1661365
Filename
1661365
Link To Document