Adaptive neural Legendre orthogonal polynomial nonlinear channel equalization for chaos-based communications systems | Zendy

Haiquan Zhao | Zendy; Jiashu Zhang | Zendy; Zeng Xiang-ping | Zendy

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Adaptive neural Legendre orthogonal polynomial nonlinear channel equalization for chaos-based communications systems

Author(s) -

Haiquan Zhao,

Jiashu Zhang,

Zeng Xiang-ping

Publication year - 2007

Publication title -

acta physica sinica

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.

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