• DocumentCode
    1544611
  • Title

    Linear redundancy of information carried by the discrete Wigner distribution

  • Author

    Richard, Cédric

  • Author_Institution
    Lab. de Modelisation et Surete des Syst., Univ. de Technol. de Troyes, France
  • Volume
    49
  • Issue
    11
  • fYear
    2001
  • fDate
    11/1/2001 12:00:00 AM
  • Firstpage
    2536
  • Lastpage
    2544
  • Abstract
    The discrete Wigner distribution (WD) encodes information in a redundant fashion since it derives N by N representations from N-sample signals. The increased amount of data often prohibits its effective use in applications such as signal detection, parameter estimation, and pattern recognition. As a consequence, it is of great interest to study the redundancy of information it carries. Richard and Lengelle (see Proc. IEEE Int.Conf. Acost., Speech, Signal Process., Istanbul, Turkey, p.85-8, 2000) have shown that linear relations connect the time-frequency samples of the discrete WD. However, up until now, such a redundancy has still not been algebraically characterized. In this paper, the problem of the redundancy of information carried by the discrete cross WD of complex-valued signals is addressed. We show that every discrete WD can be fully recovered from a small number of its samples via a linear map. The analytical expression of this linear map is derived. Special cases of the auto WD of complex-valued signals and real-valued signals are considered. The results are illustrated by means of computer simulations, and some extensions are pointed out
  • Keywords
    Wigner distribution; signal sampling; time-frequency analysis; auto WD; complex-valued signals; computer simulations; discrete Wigner distribution; discrete cross WD; information encoding; information redundancy; linear map; linear redundancy; linear relations; parameter estimation; pattern recognition; real-valued signals; signal detection; signal representation; signal samples; time-frequency samples; Computer simulation; Discrete Fourier transforms; Distributed computing; Helium; Parameter estimation; Pattern recognition; Signal analysis; Signal detection; Signal processing; Spectral analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.960400
  • Filename
    960400