• DocumentCode
    1896775
  • Title

    A generalized least squares approach to blind separation of sources which have variance dependencies

  • Author

    Shimizu, Shogo ; Hyvarinen, Aapo ; Kano, Yusuke

  • fYear
    2005
  • fDate
    17-20 July 2005
  • Firstpage
    1080
  • Lastpage
    1083
  • Abstract
    We discuss the blind source separation problem where the sources are not independent but are dependent only through their variances. Some estimation methods have been proposed on this line. However, most of them require some additional assumptions, a parametric model for their dependencies or a temporal structure of the sources, for example. In this article, we propose a generalized least squares approach to the blind source separation problem in the general case where those additional assumptions do not hold
  • Keywords
    blind source separation; least squares approximations; matrix algebra; blind source separation; generalized least squares approach; temporal structure; Autocorrelation; Blind source separation; Educational products; Independent component analysis; Information technology; Least squares methods; Maximum likelihood estimation; Parametric statistics;
  • 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.2005.1628756
  • Filename
    1628756