%0 Journal Article
%T Chaotic diagonal recurrent neural network<br>
%A Wang Xing-Yuan
%A Zhang Yi
%A <br>
%J 中国物理 B
%D 2012
%I 
%X We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks.
%K diagonal recurrent neural network
%K chaos
%K cubic symmetry map<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=CD8D6A6897B9334F09D8D1648C376FB4&aid=8DDEB85749F7F52981BF9533A1226B26&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=38B194292C032A66&sid=0E5F2176C0C1A355&journal_id=1009-1963&journal_name=中国物理&referenced_num=0&reference_num=18