Degradation of the tracking performance of adaptive filtering algorithms with data correlation

Author

Eweda, Eweda

Author_Institution

Mil. Tech. Coll., Cairo, Egypt

Volume

47

Issue

6

fYear

2000

fDate

6/1/2000 12:00:00 AM

Firstpage

559

Lastpage

561

Abstract

Degradation of the tracking performance of adaptive filtering algorithms with data correlation is analyzed. The analysis is done in the context of the identification of a randomly time varying plant. Five algorithms are considered. They are least mean square, recursive least squares, sign, signed regressor, and sign-sign algorithms. The analysis is done in terms of the steady-state excess mean-square error and the steady-state mean-square weight misalignment. The degradation measure adopted is the ratio of the performance index for correlated data to that for white data

Keywords

adaptive filters; adaptive signal processing; correlation methods; filtering theory; identification; least mean squares methods; least squares approximations; performance index; tracking filters; adaptive filtering algorithms; data correlation; identification; least mean square; performance index; randomly time varying plant; recursive least squares; sign algorithm; sign-sign algorithm; signed regressor algorithm; steady-state excess mean-square error; steady-state mean-square weight misalignment; tracking performance degradation; Adaptive filters; Degradation; Filtering algorithms; Finite impulse response filter; Least squares approximation; Least squares methods; Performance analysis; Resonance light scattering; Signal processing algorithms; Steady-state;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.847074

Filename

847074