Chaotic diagonal recurrent neural network

doi:10.1088/1674-1056/21/3/038703

Abstract 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.

Keywords: diagonal recurrent neural network chaos cubic symmetry map

Received: 06 May 2011
Revised: 08 November 2011
Accepted manuscript online:

PACS:	87.19.lj	(Neuronal network dynamics)
	05.45.Gg	(Control of chaos, applications of chaos)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61173183, 60973152, and 60573172), the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014), and the Natural Science Foundation of Liaoning Province, China (Grant No. 20082165).

Corresponding Authors: Zhang Yi,zoey0313@sina.com
E-mail: zoey0313@sina.com

Cite this article:

Wang Xing-Yuan(王兴元) and Zhang Yi(张诣) Chaotic diagonal recurrent neural network 2012 Chin. Phys. B 21 038703

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