• DocumentCode
    1502172
  • Title

    Blind signal separation using overcomplete subband representation

  • Author

    Grbic, Nedelko ; Tao, Xiao-Jiao ; Nordholm, S.E. ; Claesson, Ingvar

  • Author_Institution
    Dept. of Telecommun. & Signal Processing, Blekinge Inst. of Technol., Ronneby, Sweden
  • Volume
    9
  • Issue
    5
  • fYear
    2001
  • fDate
    7/1/2001 12:00:00 AM
  • Firstpage
    524
  • Lastpage
    533
  • Abstract
    This paper discusses a multirate filterbank-based extended infomax algorithm for real-world signal separation, i.e., convolved mixtures separation. Since convolution in the time domain corresponds to instantaneous mixing in the frequency domain, polyphase subband projection naturally becomes an efficient alternative to the Fourier transform based frequency domain approach. The online implementation proposed is featured by a simultaneous inverse channel identification in the frequency domain and signal filtering in the time domain. It is shown that an over-representation structure reduces aliasing between different bands and results in more accurate inverse channel estimates. Therefore, it provides better performance than the Fourier transform based structure in the measures of both separation and distortion. The performance limitation of the method is also evaluated in terms of the Wiener solution
  • Keywords
    FIR filters; channel bank filters; convolution; finite difference time-domain analysis; speech enhancement; Wiener solution; aliasing; blind signal separation; convolution; convolved mixtures separation; distortion; frequency domain; instantaneous mixing; inverse channel estimates; inverse channel identification; multirate filterbank-based extended infomax algorithm; online implementation; over-representation structure; overcomplete subband representation; polyphase subband projection; real-world signal separation; signal filtering; time domain; Blind source separation; Convolution; Filtering; Finite impulse response filter; Fourier transforms; Frequency domain analysis; Mathematical model; Signal processing; Signal processing algorithms; Source separation;
  • fLanguage
    English
  • Journal_Title
    Speech and Audio Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6676
  • Type

    jour

  • DOI
    10.1109/89.928917
  • Filename
    928917