%0 Journal Article
%T Adaptive neural Legendre orthogonal polynomial nonlinear channel equalization for chaos-based communications systems<br>混沌通信系统中非线性信道的自适应神经Legendre正交多项式均衡
%A Zhao Hai-Quan
%A Zhang Jia-Shu
%A Zeng Xiang-Ping
%A <br>赵海全
%A 张家树
%A 曾祥萍
%J 物理学报
%D 2007
%I 
%X 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.
%K Legendre orthogonal polynomial
%K channel equalization
%K chaotic attractor
%K neural network<br>Legendre正交多项式
%K 信道均衡
%K 混沌吸引子
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=A544647EB5358F9A&yid=A732AF04DDA03BB3&vid=014B591DF029732F&iid=E158A972A605785F&sid=AB65A134F4ED2A2E&eid=3F3D540C9B7906DE&journal_id=1000-3290&journal_name=物理学报&referenced_num=2&reference_num=21