Mean square asymptotic behavior of stochastic neural networks with infinitely distributed delays |
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Authors: | Bing Daoyi |
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Affiliation: | aCollege of Science, Chongqing Jiaotong University, Chongqing 400074, China;bYangtze Center of Mathematics, Sichuan University, Chengdu 610064, China |
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Abstract: | In this paper, according to classic -matrix method, integral–differential inequality technique and Ito formula, we study asymptotic behavior in mean square sense of stochastic neural networks with infinitely distributed delays by establishing a generalized Halanay inequality. This is a new means for investigating asymptotic behavior of stochastic differential equation. Some useful results are derived. Especially, our methods can be extended to research p-moment asymptotic behavior easily. At last, example and simulations demonstrate the power of our methods. |
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Keywords: | Ultimate boundedness Exponential stability Ito formula Halanay inequality Neural networks |
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