Open AccessAdaptive neural Legendre orthogonal polynomial nonlinear channel equalization for chaos-based communications systems
Author(s) -
Shaohui Lv,
Jiashu Zhang,
Xianlin Zeng
Publication year - 2007
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
ISSN - 1000-3290
DOI - 10.7498/aps.56.1975
Subject(s) - legendre polynomials , nonlinear system , computer science , chaotic , channel (broadcasting) , artificial neural network , equalization (audio) , adaptive equalizer , control theory (sociology) , polynomial , communications system , blind equalization , algorithm , topology (electrical circuits) , mathematics , telecommunications , mathematical analysis , artificial intelligence , physics , control (management) , quantum mechanics , combinatorics
The performance of chaos-based communications systems is greatly affected by many sorts of nonlinear distortions. If nonlinear distortions in the channel can be removed, the performance of chaos-based communications systems can be improved. According to analysis of Volterra filter, a novel structure of neural network Legendre orthogonal polynomial equalizer is proposed based on the theory of chaotic signal reconstruction. Combining the characteristic of single layer neural network and structure of Legendre orthogonal polynomial, the equalizer is designed and realized after the analysis of a few parameter nonlinear filters, and adaptive algorithm is deduced using the normalized least mean square algorithm. To support the analysis, simulation results for nonlinear chaos-based communication channel are provided.