Asymptotic stability of impulsive high-order Hopfield type neural networks |
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| Authors: | Bingji Xu Xiang Liu Kok Lay Teo |
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| Affiliation: | aSchool of Information Engineering, China University of Geosciences, 100083, Beijing, China;bInstitute of Education Research, Huazhong University of Science and Technology, 430074, Wuhan, China;cDepartment of Mathematics and Statistics, Curtin University of Technology, Perth, W.A., 6845, Australia |
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| Abstract: | In this paper, we discuss impulsive high-order Hopfield type neural networks. Investigating their global asymptotic stability, by using Lyapunov function method, sufficient conditions that guarantee global asymptotic stability of networks are given. These criteria can be used to analyse the dynamics of biological neural systems or to design globally stable artificial neural networks. Two numerical examples are given to illustrate the effectiveness of the proposed method. |
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| Keywords: | Impulsive high-order Hopfield type neural networks Asymptotic stability Lyapunov function |
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