Mean square exponential stability of uncertain stochastic neural networks with time-varying delay

Mean square exponential stability of uncertain stochastic neural networks with time-varying delay
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时变时滞不确定随机神经网络的均方指数稳定性

DOI:
10.1016/j.neucom.2008.12.001
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发表时间:
2009-06
期刊:
影响因子:
6
通讯作者:
Wu, Yuqiang
Wu, Yuqiang
中科院分区:
计算机科学2区
文献类型:
--
作者:
Wu, Yuanyuan;Chen, Yonggang;Wu, Yuqiang

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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。利用一种新的引理和李雅普诺夫泛函方法,以线性矩阵不等式(LMI)的形式给出了系统的保守性较弱的指数稳定性判据。同时,可以估计指数收敛速度。两个数值算例表明了该方法的有效性和改进。
In this paper, the mean square exponential stability problem is considered for a class of uncertain stochastic neural networks with time-varying delay. By applying a novel Lemma and Lyapunov functional method, the less conservative exponential stability criteria are derived in terms of linear matrix inequalities (LMIs). Meanwhile, the exponential convergence rate can be estimated. Two numerical examples are presented to show the effectiveness and improvement of the proposed method.
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