On the effect of input signal correlation on weight misadjustment in the RLS algorithm

Author

Adali, Tulay ; Ardalan, Sasan H.

Author_Institution

Dept. of Electr. Eng., Maryland Univ., Baltimore, MD, USA

Volume

43

Issue

4

fYear

1995

fDate

4/1/1995 12:00:00 AM

Firstpage

988

Lastpage

991

Abstract

New expressions are derived for the mean weight misadjustment in the recursive least squares (RLS) algorithm for first-order Markov channel estimation. The expressions derived are general in that they take into account the correlation in the input. It is shown that the additive system noise is amplified by a correlation amplification factor that is defined as a function of the input autocorrelation matrix eigenvalues. However, input correlation has almost no effect on the misadjustment due to time-varying system weights. These results are checked by simulations demonstrating excellent agreement with the theory

Keywords

Gaussian noise; Markov processes; adaptive filters; adaptive signal processing; correlation methods; eigenvalues and eigenfunctions; filtering theory; identification; least squares approximations; recursive estimation; telecommunication channels; white noise; RLS algorithm; adaptive filter; additive system noise; correlation amplification factor; eigenvalues; first-order Markov channel estimation; input autocorrelation matrix; input signal correlation; mean weight misadjustment; recursive least squares; simulations; time-varying system weights; white Gaussian noise; Adaptive filters; Additive noise; Algorithm design and analysis; Channel estimation; Gaussian noise; Least squares approximation; Performance analysis; Resonance light scattering; System identification; Time varying systems;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.376851

Filename

376851