DocumentCode :
2169047
Title :
An extension of the ICA model using latent variables
Author :
Rafi, Selwa ; Castella, Marc ; Pieczynski, Wojciech
Author_Institution :
Institut Telecom; Telecom SudParis, Département CITI; UMR-CNRS 5157, 9 rue Charles Fourier, 91011 Evry Cedex, France
fYear :
2011
fDate :
22-27 May 2011
Firstpage :
3712
Lastpage :
3715
Abstract :
The Independent Component Analysis (ICA) model is extended to the case where the components are not necessarily independent: depending on the value a hidden latent process at the same time, the unknown components of the linear mixture are assumed either mutually independent or dependent. We propose for this model a separation method which combines: (i) a classical ICA separation performed using the set of samples whose components are conditionally independent, and (ii) a method for estimation of the latent process. The latter task is performed by Iterative Conditional Estimation (ICE). It is an estimation technique in the case of incomplete data, which is particularly appealing because it requires only weak conditions. Finally, simulations validate our method and show that the separation quality is improved for sources generated according to our model.
Keywords :
Data models; Estimation; Ice; Independent component analysis; Markov processes; Mathematical model; Source separation; Independent Component Analysis (ICA); Iterative Conditional Estimation (ICE); blind source separation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague, Czech Republic
ISSN :
1520-6149
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2011.5947157
Filename :
5947157
Link To Document :
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