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
Link To Document :
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