Improving the performance of the LMS and RLS algorithms for adaptive equalizer

Ye, Hua, Zhou, Wanlei, Yu, Shui and Lan, Mingjun 2003, Improving the performance of the LMS and RLS algorithms for adaptive equalizer, in Active media technology : proceedings of the Second International Conference on Active Media Technology, Chongqing, PR China, 29-31 May, 2003, World Scientific, New York, N.Y, pp. 457-462.

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Title Improving the performance of the LMS and RLS algorithms for adaptive equalizer
Author(s) Ye, Hua
Zhou, Wanlei
Yu, Shui
Lan, Mingjun
Conference name International Conference on Active Media Technology (ICAMT2003) (2nd : 2003 : Chongqing, China)
Conference location Chongqing, China
Conference dates 29-31 May 2003
Title of proceedings Active media technology : proceedings of the Second International Conference on Active Media Technology, Chongqing, PR China, 29-31 May, 2003
Editor(s) Li, Jian Ping
Liu, Jiming
Zhong, Ning
Yen, John
Zhao, Jing
Publication date 2003
Start page 457
End page 462
Publisher World Scientific
Place of publication New York, N.Y
Summary In this paper, we present the experiment results of three adaptive equalization algorithms: least-mean-square (LMS) algorithm, discrete cosine transform-least mean square (DCT-LMS) algorithm, and recursive least square (RLS) algorithm. Based on the experiments, we obtained that the convergence rate of LMS is slow; the convergence rate of RLS is great faster while the computational price is expensive; the performance of that two parameters of DCT-LMS are between the previous two algorithms, but still not good enough. Therefore we will propose an algorithm based on H2 in a coming paper to solve the problems.
ISBN 9812383433
9789812383433
Language eng
Field of Research 080699 Information Systems not elsewhere classified
Socio Economic Objective 890299 Computer Software and Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30005184

Document type: Conference Paper
Collection: School of Information Technology
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