Stationary points of the recursive generalized least squares algorithm for adaptive notch filtering

Author

DragoSeviC, Manna V.

Author_Institution

Comput. Syst. Design Lab., Inst. of Nucl. Sci. ´´Vinca´´, Belgrade, Yugoslavia

Volume

41

Issue

4

fYear

1993

fDate

4/1/1993 12:00:00 AM

Firstpage

1672

Lastpage

1675

Abstract

Possible convergence points of the generalized least squares adaptive notch filtering algorithm are analytically derived for the multiple sinusoid case, showing explicitly the dependence of the asymptotic bias on the pole contraction factor, signal-to-noise ratio, and the true model parameters. The results for symmetric and nonsymmetric parameterization are compared

Keywords

adaptive filters; convergence of numerical methods; filtering and prediction theory; least squares approximations; notch filters; adaptive notch filtering; asymptotic bias; convergence points; multiple sinusoid case; nonsymmetric parameterization; pole contraction factor; recursive generalized least squares algorithm; signal-to-noise ratio; stationary points; symmetric parameterization; Adaptive filters; Adaptive signal processing; Filtering algorithms; Least squares approximation; Least squares methods; Recursive estimation; Signal processing; Signal processing algorithms; Source separation; Speech processing;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.212740

Filename

212740