Global exponential stability of impulsive high-order Hopfield type neural networks with delays

Authors:
Bingji Xu;Xiang Liu;Kok Lay Teo
Affiliations:
School of Information Engineering, China University of Geosciences, 100083, Beijing, China;Institute of Education Research, Huazhong University of Science and Technology, 430074, Wuhan, China;Department of Mathematics and Statistics, Curtin University of Technology, Perth, W.A., 6845, Australia
Venue:
Computers & Mathematics with Applications
Year:
2009

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Abstract

In this paper, we investigate the global exponential stability of impulsive high-order Hopfield type neural networks with delays. By establishing the impulsive delay differential inequalities and using the Lyapunov method, two sufficient conditions that guarantee global exponential stability of these networks are given, and the exponential convergence rate is also obtained. A numerical example is given to demonstrate the validity of the results.