| 带马氏切换的时滞脉冲神经网络稳定性分析 |
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| 引用本文： | 席福宝,徐畅.带马氏切换的时滞脉冲神经网络稳定性分析[J].北京理工大学学报,2020,40(10):1133-1137. |
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| 作者姓名： | 席福宝 徐畅 |
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| 作者单位： | 北京理工大学 数学与统计学院, 北京 100081 |
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| 基金项目： | 国家自然科学基金资助项目（11671034） |
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| 摘 要： | 为研究带马氏切换的时滞脉冲随机神经网络的均方指数稳定性，构造了合适的Lyapunov函数，并利用伊藤公式、矩阵知识、泛函理论及神经网络自身的特性，对脉冲时刻及非脉冲时刻的系统状态进行分析，得到了该神经网络具有均方指数稳定性的判别准则，该准则应用广泛，简单好用.最后通过数值例子及仿真模拟，说明了该准则的正确性.
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| 关 键 词： | 时滞脉冲神经网络 均方指数稳定性 马氏切换 |
| 收稿时间： | 2019/6/25 0:00:00 |
The Stability of Impulsive Stochastic Delay Neural Networks with Markovian Switching |
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| XI Fu-bao,XU Chang.The Stability of Impulsive Stochastic Delay Neural Networks with Markovian Switching[J].Journal of Beijing Institute of Technology(Natural Science Edition),2020,40(10):1133-1137. |
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| Authors: | XI Fu-bao XU Chang |
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| Institution: | School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | In order to study the mean square exponential stability of impulse stochastic delay neural networks with Markovian switching, a suitable Lyapunov function was established. Based on Itô formula, functional theory, the characteristics of neural networks and the knowledge of matrix, the state of system at impulsive time and non-impulsive time was analyzed, getting the rules to distinguish the mean square exponential stability of the stochastic neural network. The numerical example analysis and simulation results show that the rules are efficient, simple and validity. |
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| Keywords: | delayed neural networks with impulses mean square exponential stability Markovian switching |
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