• DocumentCode
    1171238
  • Title

    Consistent independent component analysis and prewhitening

  • Author

    Chen, Aiyou ; Bickel, Peter J.

  • Author_Institution
    Bell Labs., Lucent Technol., Murray Hill, NJ, USA
  • Volume
    53
  • Issue
    10
  • fYear
    2005
  • Firstpage
    3625
  • Lastpage
    3632
  • Abstract
    We study the statistical merits of two techniques used in the literature of independent component analysis (ICA). First, we analyze the characteristic-function based ICA method (CHFICA) and study its statistical properties such as consistency, √n-consistency, and robustness against small additive noise. Second, we study the validity of prewhitening: a preprocessing technique used by many ICA algorithms, as applied to the CHFICA method. In particular, we establish the surprising effectiveness of this technique even when some components have heavy tails and others do not. A fast new algorithm implementing the prewhitened CHFICA method is also provided.
  • Keywords
    independent component analysis; signal processing; ICA; additive noise; asymptotic normality; characteristic-function based method; consistency; incomplete Cholesky decomposition; independent component analysis; preprocessing technique; prewhitening; signal processing; statistical properties; Additive noise; Blind source separation; Independent component analysis; Machine learning algorithms; Noise robustness; Parametric statistics; Signal analysis; Signal processing algorithms; Source separation; Tail; Asymptotic normality; characteristic function; consistency; incomplete Cholesky decomposition; independent component analysis; prewhitening;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2005.855098
  • Filename
    1510972