• DocumentCode
    1342009
  • Title

    Weighted least squares implementation of Cohen-Posch time-frequency distributions

  • Author

    Loughlin, P.J.

  • Volume
    46
  • Issue
    3
  • fYear
    1998
  • fDate
    3/1/1998 12:00:00 AM
  • Firstpage
    753
  • Lastpage
    757
  • Abstract
    We present an improvement of the least-squares method of Sang et al. (see Proc. IEEE-SP Int. Symp. Time-Freq./Time-Scale Anal., p.165-8, 1996) for constructing nonnegative joint time-frequency distributions (TFDs) satisfying the time and frequency marginals (i.e., Cohen-Posch (1985) distributions). The proposed technique is a positivity constrained iterative weighted least-squares (WLS) algorithm used to modify an initial TFD (e.g., any bilinear TFD) to obtain a Cohen-Posch TFD. The new algorithm solves the “leakage” problem of the least-squares approach and is computationaly faster. Examples illustrating the performance of the new algorithm are presented. The results for the WLS method compare favorably with the minimum cross-entropy method previously developed by Loughlin et al. (1992)
  • Keywords
    iterative methods; least squares approximations; signal processing; statistical analysis; time-frequency analysis; Cohen-Posch time-frequency distributions; WLS method; bilinear TFD; frequency marginal; iterative weighted least-squares; leakage problem; least-squares method; minimum cross-entropy method; nonnegative joint time-frequency distributions; performance; positivity constrained algorithm; time marginal; Distributed computing; Hilbert space; Iterative algorithms; Iterative methods; Least squares methods; Network synthesis; Signal processing; Signal processing algorithms; Signal synthesis; Time frequency analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.661340
  • Filename
    661340