• DocumentCode
    2200050
  • Title

    Simple algorithms for decorrelation-based blind source separation

  • Author

    Douglas, Scott C.

  • Author_Institution
    Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    545
  • Lastpage
    554
  • Abstract
    We present simple adaptive algorithms that perform blind source separation for spatially-independent and temporally-correlated source signals. The proposed algorithms are modified versions of a well-known natural gradient prewhitening scheme, and the simplest version has almost the same complexity as this prewhitening method. We provide a stationary point analysis of our schemes, proving that the only locally-stable stationary point results in separated sources with unit variances and a guaranteed output ordering. We also show how to modify the approaches so that joint subspace analysis and decorrelation-based source separation are performed. Simulations verify the separation capabilities of the schemes.
  • Keywords
    adaptive signal processing; blind source separation; computational complexity; decorrelation; gradient methods; statistical analysis; adaptive algorithms; blind source separation; decorrelation; joint subspace analysis; natural gradient prewhitening scheme; spatially-independent source signals; stationary point analysis; temporally-correlated source signals; Adaptive algorithm; Algorithm design and analysis; Analysis of variance; Blind source separation; Decorrelation; Gradient methods; Iterative algorithms; Performance analysis; Source separation; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on
  • Print_ISBN
    0-7803-7616-1
  • Type

    conf

  • DOI
    10.1109/NNSP.2002.1030066
  • Filename
    1030066