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
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