Global Exponential Stability of Reaction-Diffusion Delayed BAM Neural Networks with Dirichlet Boundary Conditions

Authors:
Chaojin Fu;Ailong Wu
Affiliations:
Department of Mathematics, Hubei Normal University, Huangshi, China 435002;Department of Mathematics, Hubei Normal University, Huangshi, China 435002
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

Citing 6
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Abstract

In this paper, the global exponential stability for a class of reaction-diffusion delayed bidirectional associate memory (BAM) neural networks with Dirichlet boundary conditions is addressed by using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium point of such networks are established. Finally, an example is given to show the effectiveness of the obtained result.