RLS-Laguerre lattice adaptive filtering: error-feedback, normalized, and array-based algorithms

Author

Merched, Ricardo ; Sayed, Ali H.

Author_Institution

Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA

Volume

49

Issue

11

fYear

2001

fDate

11/1/2001 12:00:00 AM

Firstpage

2565

Lastpage

2576

Abstract

This paper develops several lattice structures for RLS-Laguerre adaptive filtering including a posteriori and a priori based lattice filters with error-feedback, array-based lattice filters, and normalized lattice filters. All structures are efficient in that their computational cost is proportional to the number of taps, albeit some structures require more multiplications or divisions than others. The performance of all filters, however, can differ under practical considerations, such as finite-precision effects and regularization. Simulations are included to illustrate these facts

Keywords

adaptive filters; adaptive signal processing; circuit feedback; filtering theory; lattice filters; least squares approximations; recursive filters; RLS-Laguerre lattice adaptive filtering; a posteriori based lattice filter; a priori based lattice filter; array-based algorithm; array-based lattice filter; computational cost; error-feedback algorithm; error-feedback lattice filter; filter performance; filter taps; finite-precision effects; lattice structures; normalized algorithm; normalized lattice filters; regularization; simulations; Adaptive arrays; Adaptive filters; Computational efficiency; Computational modeling; Feedback; Filtering algorithms; Finite impulse response filter; Lattices; Resonance light scattering; Signal processing algorithms;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.960404

Filename

960404