Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 831695, 22 pages
doi:10.1155/2011/831695
Research Article

Synchronization for an Array of Coupled Cohen-Grossberg Neural Networks with Time-Varying Delay

1Key Laboratory of Measurement and Control of CSE, School of Automation, Southeast University, Ministry of Education, Nanjing 210096, China
2School of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 2010016, China

Received 23 November 2010; Accepted 9 March 2011

Academic Editor: Bin Liu

Copyright © 2011 Haitao Zhang et al. 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

This paper makes some great attempts to investigate the global exponential synchronization for arrays of coupled delayed Cohen-Grossberg neural networks with both delayed coupling and one single delayed one. By resorting to free-weighting matrix and Kronecker product techniques, two novel synchronization criteria via linear matrix inequalities (LMIs) are presented based on convex combination, in which these conditions are heavily dependent on the bounds of both the delay and its derivative. Owing to that the addressed system can include some famous neural network models as the special cases, the proposed methods can extend and improve those earlier reported ones. The efficiency and applicability of the presented conditions can be demonstrated by two numerical examples with simulations.