Further results on mean square exponential stability of uncertain stochastic delayed neural networks

Further results on mean square exponential stability of uncertain stochastic delayed neural networks
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不确定随机延迟神经网络均方指数稳定性的进一步结果

DOI:
10.1109/ccdc.2010.5498709
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发表时间:
2010-05
影响因子:
3.9
通讯作者:
Shumin Fei
Shumin Fei
中科院分区:
数学2区
文献类型:
--
作者:
Jianjiang Yu;Kanjian Zhang;Shumin Fei

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本文研究了一类具有时变时滞的不确定随机神经网络的均方指数稳定性问题。激活函数既非单调的,也非可微的。利用构造的Lyapunov-Krasovskii泛函和新技术,导出了时滞相关的稳定性判据。最后通过一个算例说明了该方法的有效性和改进。
This letter is concerned with the mean square exponential stability problem for a class of uncertain stochastic neural networks with time-varying delay. The activation functions are assumed to be neither monotonic, nor differentiable. The proposed delay-dependent stability criterion is derived by utilizing the constructed Lyapunov-Krasovskii functional and the novel technique. A numerical example is presented to show the effectiveness and improvement of the proposed method.
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不确定随机延迟神经网络均方指数稳定性的进一步结果
DOI: 10.1109/ccdc.2010.5498709
发表时间: 2010-05
影响因子: 3.9
作者:
Jianjiang Yu;Kanjian Zhang;Shumin Fei
通讯作者: Shumin Fei
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