Exponential Stability of Impulsive Hopfield Neural Networks with Time Delays

Authors:
Tingyan Xing;Muyao Shi;Wenjie Jiang;Nan Zhang;Tuo Wang
Affiliations:
School of Information Engineering, China University of Geosciences, Beijing, China 100083;School of Information Engineering, China University of Geosciences, Beijing, China 100083;School of Information Engineering, China University of Geosciences, Beijing, China 100083;School of Information Engineering, China University of Geosciences, Beijing, China 100083;School of Information Engineering, China University of Geosciences, Beijing, China 100083
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

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Abstract

This paper considers the problems of global exponential stability and exponential convergence rate for impulsive Hopfield neural networks with time delays. By using the method of Lyapunov functions, M-matrix theory and inequality technique, some sufficient conditions for ensuring global exponential stability of these networks are derived, and the estimation for exponential convergence rate index is also obtained. As an illustration, an numerical example is worked out to show the effectiveness of the obtained results.