%0 Journal Article
%T Synchronization of an uncertain chaotic system via recurrent neural networks<br>不确定混沌系统的回归神经网络同步
%A Tan Wen
%A Wang Yao-Nan
%A <br>谭文
%A 王耀南
%J 中国物理 B
%D 2005
%I 
%X Incorporating distributed recurrent networks with high-order connections between neurons, the identification and synchronization problem of an unknown chaotic system in the presence of unmodelled dynamics is investigated. Based on the Lyapunov stability theory, the weights learning algorithm for the recurrent high-order neural network model is presented.Also, analytical results concerning the stability properties of the scheme are obtained. Then adaptive control law for eliminating synchronization error of uncertain chaotic plant is developed via Lyapunov methodology. The proposed scheme is applied to model and synchronize an unknown Rossler system.
%K chaos
%K recurrent neural networks
%K adaptive control
%K synchronization
%K nonlinear system<br>回归神经网络
%K 自适应控制
%K 同步
%K 非线性系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=CD8D6A6897B9334F09D8D1648C376FB4&aid=93197BFA4B407E772FF83DB37EF97B14&yid=2DD7160C83D0ACED&vid=F3583C8E78166B9E&iid=CA4FD0336C81A37A&sid=AA76E167F386B6B3&eid=228A710F49B6CE58&journal_id=1009-1963&journal_name=中国物理&referenced_num=0&reference_num=8