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