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Journal of Applied Mathematics
Volume 2012, Article ID 523812, 12 pages
Research Article

LMI Approach to Stability Analysis of Cohen-Grossberg Neural Networks with -Laplace Diffusion

1Department of Mathematics, Yibin University, Yibin 644007, China
2Institute of Mathematics, Yibin University, Yibin 644007, China
3College of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054, China

Received 1 August 2012; Revised 24 October 2012; Accepted 12 November 2012

Academic Editor: Zhilong L. Huang

Copyright © 2012 Xiongrui Wang 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.


The nonlinear -Laplace diffusion () was considered in the Cohen-Grossberg neural network (CGNN), and a new linear matrix inequalities (LMI) criterion is obtained, which ensures the equilibrium of CGNN is stochastically exponentially stable. Note that, if , -Laplace diffusion is just the conventional Laplace diffusion in many previous literatures. And it is worth mentioning that even if , the new criterion improves some recent ones due to computational efficiency. In addition, the resulting criterion has advantages over some previous ones in that both the impulsive assumption and diffusion simulation are more natural than those of some recent literatures.