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Ultimate boundedness of stochastic Hopfield neural networks with time-varying delays |
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| Authors: | Li WanAuthor Vitae Qinghua ZhouAuthor Vitae |
| Affiliation: | a School of Mathematics and Physics, Wuhan Textile University, Wuhan 430073, China b Department of Mathematics, Zhaoqing University, Zhaoqing 526061, China c School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China |
| Abstract: | By employing Lyapunov functional theory as well as linear matrix inequalities, ultimate boundedness of stochastic Hopfield neural networks (HNN) with time-varying delays is investigated. Sufficient criteria on ultimate boundedness of stochastic HNN are firstly obtained, which fills up a gap and includes deterministic systems as our special case. Finally, numerical simulations are presented to illustrate the correctness and effectiveness of our theoretical results. |
| Keywords: | Stochastic Hopfield neural networks Time-varying delays Ultimate boundedness |
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