By Topic

Looping LMS versus fast least squares algorithms: who gets there first?

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
M. -L. Alberi ; ETIS, Cergy-Pontoise, France ; R. A. Casas ; I. Fijalkow ; C. R. Johnson

This paper analytically compares, in terms of the convergence time, fast least squares estimation algorithms for channel identification and equalization to looping LMS (LLMS), a scheme which repeatedly applies the least mean squares algorithm to a block of received data. In this study, the convergence time is defined as the actual time (in seconds) taken by an algorithm to reach a desired performance. The old theme on LMS and fast least squares algorithms convergence is revisited from a novel perspective: the comparison is made from a complexity viewpoint, which not only takes into account the statistical properties of studied algorithms but also the number of floating point operations

Published in:

Signal Processing Advances in Wireless Communications, 1999. SPAWC '99. 1999 2nd IEEE Workshop on

Date of Conference: