• DocumentCode
    3347751
  • Title

    A Bayesian method for positive source separation

  • Author

    Moussaoui, Said ; Brie, David ; Caspary, Olivier ; Mohammad-Djafari, Ali

  • Author_Institution
    CRAN CNRS UMR 7039, Nancy, France
  • Volume
    5
  • fYear
    2004
  • fDate
    17-21 May 2004
  • Abstract
    The paper considers the problem of source separation in the particular case where both the sources and the mixing coefficients are positive. The proposed method addresses the problem in a Bayesian framework. We assume a gamma distribution for the spectra and the mixing coefficients. This prior distribution enforces the non-negativity. This leads to an original method for positive source separation. A simulation example is presented to illustrate the effectiveness of the method.
  • Keywords
    Bayes methods; gamma distribution; source separation; spectral analysis; spectrochemical analysis; Bayes method; Bayesian framework; analytical chemistry; gamma distribution; mixing coefficients; positive source separation; qualitative analysis; quantitative analysis; sample analysis; spectral data; Bayesian methods; Chemistry; Constraint optimization; Data analysis; Frequency; Independent component analysis; Iterative algorithms; Source separation; Spectral analysis; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-8484-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2004.1327153
  • Filename
    1327153