• DocumentCode
    67237
  • Title

    From the STFT to the Wigner Distribution [Lecture Notes]

  • Author

    Stankovic, Lina ; Stankovic, Stevan ; Dakovic, Milos

  • Volume
    31
  • Issue
    3
  • fYear
    2014
  • fDate
    May-14
  • Firstpage
    163
  • Lastpage
    174
  • Abstract
    The analysis, processing, and parameters estimation of signals whose spectral content changes in time are of crucial interest in many applications, including radar, acoustics, biomedicine, communications, multimedia, seismic, and the car industry [1]-[11]. Various signal representations have been introduced to deal with this kind of signals within the area known as time-frequency (TF) signal analysis. The oldest analysis tool in this area is the short-time Fourier transform (STFT), as a direct extension of the classical Fourier analysis. The other key tool is the Wigner distribution (WD), introduced in signal analysis from quantum mechanics. The aim of this lecture note is to present and relate these two of the most important tools in the TF signal analysis, the STFT and the WD (introduced by two Nobel prize winners, D. Gabor and E. Wigner, respectively). This relation is a basis for the S-method (SM), an efficient and simple TF signal analysis tool providing a gradual transition between these two representations.
  • Keywords
    Fourier transforms; Wigner distribution; signal representation; time-frequency analysis; Fourier analysis; S-method; SM; STFT; TF signal analysis tool; WD; Wigner distribution; quantum mechanics; short-time Fourier transform; signal parameter estimation; signal processing; signal representations; time-frequency signal analysis; Discrete Fourier transforms; Parameter estimation; Signal analysis; Signal resolution; Spectral analysis; Time-frequency analysis; Wigner distribution;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2014.2301791
  • Filename
    6784080