Convergence performance of adaptive lattice filters with nonlinear parameter updates

Author

Kumura, T. ; Liguni, Y. ; Maeda, H.

Author_Institution

Dept. of Commun. Eng., Osaka Univ., Japan

Volume

147

Issue

3

fYear

2000

fDate

6/1/2000 12:00:00 AM

Firstpage

238

Lastpage

246

Abstract

The convergence properties of adaptive lattice filters with nonlinear parameter updates have been analysed. The theoretical expressions for the convergence rate and the asymptotic error variance of the PARCOR coefficient are derived. Using these expressions, the convergence performance in the absence of impulsive noise is investigated and compared with those of the linear-type and sign-type adaptive lattice filters. Furthermore, the mean parameter variation caused by an impulsive noise and the parameter recovery time are evaluated to comprehensively compare the convergence performances in the presence of impulsive noise

Keywords

adaptive filters; adaptive signal processing; convergence of numerical methods; correlation methods; error analysis; filtering theory; impulse noise; lattice filters; network parameters; LMS algorithm; PARCOR coefficient; asymptotic error variance; convergence performance; convergence properties; convergence rate; impulsive noise; least mean square algorithm; linear-type adaptive lattice filters; mean parameter variation; nonlinear parameter updates; parameter recovery time; partial correlation; sign-type adaptive lattice filters; transversal filter structure;

fLanguage

English

Journal_Title

Vision, Image and Signal Processing, IEE Proceedings -

Publisher

iet

ISSN

1350-245X

Type

jour

DOI

10.1049/ip-vis:20000332

Filename

852305