Global Exponential Stability of Cohen-Grossberg Neural Networks with Reaction-Diffusion and Dirichlet Boundary Conditions

Authors:
Chaojin Fu;Chongjun Zhu
Affiliations:
Department of Mathematics, Hubei Normal University, Huangshi, Hubei, 435002, China and Hubei Province Key Laboratory of Bioanalytical Technique, Hubei Normal University, Huangshi, Hubei, 435002, C ...;Department of Mathematics, Hubei Normal University, Huangshi, Hubei, 435002, China
Venue:
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Year:
2009

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Abstract

In this paper, global exponential stability of Cohen-Grossberg neural networks with reaction-diffusion and Dirichlet boundary conditions is considered by using an approach based on the delay differential inequality and the fixed-point theorem. Some sufficient conditions are obtained to guarantee that the reaction-diffusion Cohen-Grossberg neural networks are globally exponentially stable. The results presented in this paper are the improvement and extension of the existed ones in some existing works.