Cart (Loading....) | Create Account
Close category search window

Channel Equalization Using a Robust Recursive Least-Squares Adaptive-Filtering Algorithm

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
$31 $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

1 Author(s)
Yang Wang ; Sch. of Aeronaut. & Astronaut., UESTC, Chengdu, China

Aimed at the existing shortcomings that robustness cannot be guaranteed for input-signals or desired-signals corrupted by impulsive noise and sudden system changes also cannot be successfully tracked in channel equalization using conventional algorithms, a new robust recursive least-squares (RLS) adaptive-filtering algorithm that uses a priori error-dependent weights is proposed. Robustness against impulsive noise is achieved by choosing the weights on the basis of the L1 norms of the cross-correlation vector and the input-signal autocorrelation matrix. Simulation results show that the proposed algorithm offers improved robustness as well as better tracking compared to the conventional RLS and the QN adaptation algorithms.

Published in:

Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on

Date of Conference:

27-29 Oct. 2012

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.