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Advances in Artificial Neural Systems
Volume 2011 (2011), Article ID 249136, 7 pages
http://dx.doi.org/10.1155/2011/249136
Research Article

The Generalized Dahlquist Constant with Applications in Synchronization Analysis of Typical Neural Networks via General Intermittent Control

Department of Mathematics, Heze University, Heze 274015, Shandong, China

Received 11 January 2011; Revised 8 May 2011; Accepted 7 June 2011

Academic Editor: Tomasz G. Smolinski

Copyright © 2011 Zhang Qunli. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A novel and effective approach to synchronization analysis of neural networks is investigated by using the nonlinear operator named the generalized Dahlquist constant and the general intermittent control. The proposed approach offers a design procedure for synchronization of a large class of neural networks. The numerical simulations whose theoretical results are applied to typical neural networks with and without delayed item demonstrate the effectiveness and feasibility of the proposed technique.