• DocumentCode
    1133351
  • Title

    Sinusoidal Polynomial Parameter Estimation Using the Distribution Derivative

  • Author

    Betser, Michaël

  • Author_Institution
    Dept. of Signal Process., Tampere Univ. of Technol., Tampere, Finland
  • Volume
    57
  • Issue
    12
  • fYear
    2009
  • Firstpage
    4633
  • Lastpage
    4645
  • Abstract
    In this paper, we present a method to estimate the parameters of a generalized sinusoidal model. A generalized sinusoid x is defined as a polynomial in the log domain, with complex coefficients alphai : x(t)=exp(Sigmai alphai t i), where i=0...Q. The method is based on the distribution derivative of the signal and operates in the transform domain. The method is very general and can use any linear transform such as the Fourier transform or the wavelet transform, or even combinations of linear transforms. Examples with the Fourier transform are given. The Fourier-based estimation methods are evaluated using synthetic signals and have performance very close to the theoretical bound.
  • Keywords
    Fourier transforms; parameter estimation; polynomials; signal processing; Fourier transform; Fourier-based estimation methods; distribution derivative; generalized sinusoidal model; linear transform; log domain polynomial; parameter estimation; synthetic signal; wavelet transform; Derivative method; parameter estimation; reassignment; sinusoidal model;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2009.2027401
  • Filename
    5164904