• 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