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
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