Title :
Constrained LMS adaptive algorithm
Author :
Segalen, A. ; Demoment, G.
Author_Institution :
CNRS/ESE, Laboratoire des Signaux et Systÿmes, Gif-sur-Yvette, France
Abstract :
A new least-mean-squares (LMS) adaptive algorithm is developed in the letter. This new algorithm solves a specific variance problem that occurs in LMS algorithms in the presence of high noise levels and when the input signal is bandlimited. Quantitative results in terms of an accuracy measure of a finite impulse response (FIR) system identification are presented.
Keywords :
filtering and prediction theory; identification; least squares approximations; FIR identification system; least-mean-square adaptive algorithm;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19820154
