Improving the performance of the LMS and RLS algorithms for adaptive equalizer
Contribuinte(s) |
Li, Jian Ping Liu, Jiming Zhong, Ning Yen, John Zhao, Jing |
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Data(s) |
01/01/2003
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Resumo |
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.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
World Scientific |
Relação |
http://dro.deakin.edu.au/eserv/DU:30005184/zhou-improvingtheperformance-2003.pdf |
Tipo |
Conference Paper |