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首页 > 过刊浏览>2017年第9卷第3期 >326-331. DOI:10.13878/j.cnki.jnuist.2017.03.011
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基于马氏切换的时滞脉冲随机Cohen-Grossberg神经网络模型的均方指数稳定性分析
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中央高校基本科研业务费自由探索项目（A）（2015B19814）


Mean-square exponential stability of the impulsive stochastic Cohen-Grossberg Neural networks with Markovian switching
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    摘要:

    通过向量Lyapunov函数，给随机CGNNs以均方估计，研究基于马氏切换的脉冲时滞随机Cohen-Grossberg神经网络模型的均方指数稳定性，并利用数值例子对结论加以证明.

    Abstract:

    Focused on Cohen-Grossberg neural networks,this paper investigates the mean-square exponential stability by means of the vector Lyapunov function.This method ensures that the impulsive stochastic Cohen-Grossberg neural network is exponentially stable.Finally,an example is used to illustrate the conclusions.

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李蕾,何秀丽.基于马氏切换的时滞脉冲随机Cohen-Grossberg神经网络模型的均方指数稳定性分析[J].南京信息工程大学学报(自然科学版),2017,9(3):326-331
LI Lei, HE Xiuli. Mean-square exponential stability of the impulsive stochastic Cohen-Grossberg Neural networks with Markovian switching[J]. Journal of Nanjing University of Information Science & Technology, 2017,9(3):326-331

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历史
  • 收稿日期:2017-04-11
  • 在线发布日期: 2017-06-03

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