A graph-theoretic approach to exponential stability of BAM neural networks with delays and reaction-diffusion |
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| Authors: | Huan Su Zhifang He Yuwei Zhao Xiaohua Ding |
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| Institution: | 1. Department of Mathematics, Harbin Institute of Technology at Weihai, Weihai, Shandong, 264209P.R. China.suhuantg@hitwh.edu.cn;3. Department of Mathematics, Harbin Institute of Technology at Weihai, Weihai, Shandong, 264209P.R. China. |
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| Abstract: | This paper deals with the problem of global exponential stability for bidirectional associate memory (BAM) neural networks with time-varying delays and reaction-diffusion terms. By using some inequality techniques, graph theory as well as Lyapunov stability theory, a systematic method of constructing a global Lyapunov function for BAM neural networks with time-varying delays and reaction-diffusion terms is provided. Furthermore, two different kinds of sufficient principles are derived to guarantee the exponential stability of BAM neural networks. Finally, a numerical example is carried out to demonstrate the effectiveness and applicability of the theoretical results. |
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| Keywords: | BAM neural networks time-varying delays reaction-diffusion exponential stability graph theory |
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