• DocumentCode
    929816
  • Title

    Robust rank-EASI algorithm for blind source separation

  • Author

    Zhang, Y. ; Kassam, S.A.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA
  • Volume
    151
  • Issue
    1
  • fYear
    2004
  • fDate
    2/1/2004 12:00:00 AM
  • Firstpage
    15
  • Lastpage
    19
  • Abstract
    Robustness against deviations from nominal source pdf assumptions is very desirable in blind source separation (BSS) algorithms. In the paper, a new approach for robust BSS is proposed. The EASI (equivariant adaptive separation by independence) algorithm (Cardoso and Laheld, 1996) is modified to use ranks of observed signals. The modified EASI algorithm can be applied to both real-valued and complex-valued data. Design guidelines are discussed for the nonlinear rank weighting functions in the modified EASI algorithm. Simulation results for two examples are given, showing very good performance.
  • Keywords
    adaptive signal processing; blind source separation; independent component analysis; probability; blind source separation; complex-valued data; equivariant adaptive separation by independence algorithm; nominal source PDF assumption; nonlinear rank weighting function; probability density function; real-valued data; robust rank algorithm;
  • fLanguage
    English
  • Journal_Title
    Communications, IEE Proceedings-
  • Publisher
    iet
  • ISSN
    1350-2425
  • Type

    jour

  • DOI
    10.1049/ip-com:20040276
  • Filename
    1275394