Adaptive filtering using modified conjugate gradient

Author

Chang, Pi Sheng ; Willson, Alan N., Jr.

Author_Institution

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

Volume

1

fYear

1995

fDate

13-16 Aug 1995

Firstpage

243

Abstract

An adaptive filtering algorithm is described that uses the modified Conjugate Gradient (CG) algorithm. It has the ability to perform sample-by-sample updating of the filter coefficients more efficiently than previously described CG methods. Its performance can be comparable to the RLS and LMS-Newton algorithms, giving fast convergence for highly correlated input signals, while maintaining low misadjustment. Simulations demonstrating its performance and the influence of various parameter choices are shown. A convergence criterion is also derived

Keywords

adaptive filters; conjugate gradient methods; convergence of numerical methods; correlation methods; adaptive filtering; convergence criterion; data windowing; fast convergence; filter coefficients; highly correlated input signals; low misadjustment; modified conjugate gradient algorithm; sample-by-sample updating; simulations; Adaptive filters; Character generation; Convergence; Cost function; Electronic mail; Equations; Filtering algorithms; Iterative algorithms; Resonance light scattering; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1995., Proceedings., Proceedings of the 38th Midwest Symposium on

Conference_Location

Rio de Janeiro

Print_ISBN

0-7803-2972-4

Type

conf

DOI

10.1109/MWSCAS.1995.504423

Filename

504423