• DocumentCode
    2519491
  • Title

    DESPRIT - histogram based blind source separation of more sources than sensors using subspace methods

  • Author

    Rickard, Scott ; Melia, Thomas ; Fearon, Conor

  • Author_Institution
    Deigital Signal Process. Res. Group, Dublin Coll. Univ.
  • fYear
    2005
  • fDate
    16-16 Oct. 2005
  • Firstpage
    5
  • Lastpage
    8
  • Abstract
    A blind source separation (BSS) technique is presented which combines the subspace processing and associated DOA capability of ESPRIT with the weighted histogram of DUET. The method allows for a weakened version of the disjoint signal assumption of DUET and can be seen as a natural extension of DUET to more than two mixtures. Instead of only allowing at most one source be active at any time-frequency point, up to M-1 sources can be active where M is the number of anechoic mixtures. The combination of these techniques creates a DUET-ESPRIT (DESPRIT) blind source separation algorithm which can demix an arbitrary number of sources N, even when N > M
  • Keywords
    blind source separation; matrix algebra; parameter estimation; anechoic mixtures; disjoint signal assumption; estimation of signal parameter via rotational invariance techniques; histogram based blind source separation; subspace methods; Array signal processing; Blind source separation; Delay estimation; Digital signal processing; Direction of arrival estimation; Histograms; Microphone arrays; Signal processing algorithms; Source separation; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Signal Processing to Audio and Acoustics, 2005. IEEE Workshop on
  • Conference_Location
    New Paltz, NY
  • Print_ISBN
    0-7803-9154-3
  • Type

    conf

  • DOI
    10.1109/ASPAA.2005.1540154
  • Filename
    1540154