Ultimate boundedness and an attractor for stochastic Hopfield neural networks with time-varying delays |
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| Authors: | Li Wan Qinghua Zhou |
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| Affiliation: | a School of Mathematics and Computer Science, Wuhan Textile University, Wuhan 430073, PR Chinab Department of Mathematics, Zhaoqing University, Zhaoqing 526061, PR Chinac School of Mathematics and Statistics, Wuhan University, Wuhan 430072, PR Chinad School of Management, Wuhan Textile University, Wuhan 430073, PR China |
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| Abstract: | This paper investigates ultimate boundedness and a weak attractor for stochastic Hopfield neural networks (HNN) with time-varying delays. By employing the Lyapunov method and the matrix technique, some novel results and criteria on ultimate boundedness and an attractor for stochastic HNN with time-varying delays are derived. Finally, a numerical example is given to illustrate the correctness and effectiveness of our theoretical results. |
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| Keywords: | Hopfield neural networks Delays Ultimate boundedness Weak attractor |
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