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Blind Separation of Nonstationary Sources by Spectral Decorrelation

  • Shahram Hosseini
  • Yannick Deville
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3195)

Abstract

This paper demonstrates and exploits some interesting frequency-domain properties of nonstationary signals. Considering these properties, two new methods for blind separation of linear instantaneous mixtures of mutually uncorrelated, nonstationary sources are proposed. These methods are based on spectral decorrelation of the sources. The second method is particularly important because it allows the existing time-domain algorithms developed for stationary, temporally correlated sources to be applied to nonstationary, temporally uncorrelated sources just by mapping the mixtures in the frequency domain. Moreover, it sets no constraint on the variance profile, unlike previously reported methods.

Keywords

Spectral Function Independent Component Analysis Source Separation Blind Source Separation Nonstationary Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Shahram Hosseini
    • 1
  • Yannick Deville
    • 1
  1. 1.Laboratoire d’Acoustique, Métrologie, InstrumentationUniversité Paul SabatierToulouse CedexFrance

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