DocumentCode :
1897050
Title :
Generalized contrast functions for blind separation of overdetermined linear mixtures with unknown numbers of sources
Author :
Sahmoudi, M.
Author_Institution :
TSI, Telecom Paris
fYear :
2005
fDate :
17-20 July 2005
Firstpage :
1138
Lastpage :
1143
Abstract :
In this paper, we address the problem of blind separation of m independent sources from their n linear mixtures in the overdetermined systems (n ges m) with unknown number of sources. After generalizing the definition of classical and nonsymmetrical contrast functions, we exhibit a wide class of generalized contrast functions using some superadditive functional and concave functions. Two practical generalized contrasts based on the support Lebesgue measure (SLM) and the mutual information (MI) criteria are proposed and discussed. Finally, computer simulations illustrate the results and demonstrate all the interest we can find in considering a generalized contrast function
Keywords :
blind source separation; matrix algebra; blind separation; concave functions; generalized contrast function; mutual information; nonsymmetrical contrast functions; overdetermined linear mixtures; superadditive functional; support Lebesgue measure; Biomedical signal processing; Blind source separation; Computer simulation; Data communication; Data mining; Independent component analysis; Mutual information; Signal processing algorithms; Source separation; Telecommunications;
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.2005.1628766
Filename :
1628766
Link To Document :
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