• DocumentCode
    771606
  • Title

    Mutual information approach to blind separation of stationary sources

  • Author

    Pham, Dinh Tuan

  • Author_Institution
    Lab. of Modeling & Comput., CNRS, Grenoble, France
  • Volume
    48
  • Issue
    7
  • fYear
    2002
  • fDate
    7/1/2002 12:00:00 AM
  • Firstpage
    1935
  • Lastpage
    1946
  • Abstract
    This paper presents a unified approach to the problem of blind separation of sources, based on the concept of mutual information. This concept is applied to the whole source sequences as stationary processes and thus provides a universal contrast applicable to both the instantaneous and convolutive mixture cases. For practical implementation, we introduce several degraded forms of this contrast, computable from a finite-dimensional distribution of the reconstructed source processes only. From them, we derive several sets of estimating equations, generalizing those considered earlier
  • Keywords
    Gaussian processes; Markov processes; convolution; entropy; signal reconstruction; Gaussian processes; Markovian processes; blind separation; convolutive mixture; entropy; estimating equations; finite-dimensional distribution; instantaneous mixture; mutual information; reconstructed source processes; source sequences; stationary processes; stationary sources; Computational modeling; Convolution; Degradation; Distributed computing; Entropy; Equations; Image reconstruction; Independent component analysis; Mutual information; Proposals;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2002.1013134
  • Filename
    1013134