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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DOI：
10.1016/j.cnsns.2008.04.009
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发表时间：
2009-04
影响因子：
3.9
通讯作者：
Jianjiang Yu;Kanjian Zhang;S. Fei
中科院分区：
文献类型：
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作者：
Jianjiang Yu;Kanjian Zhang;S. Fei
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。通过引入一种新的Lyapunov-Krasovskii函数，利用线性矩阵不等式建立了改进的时滞相关稳定性判据.最后给出了两个数值例子，结果表明，我们的结果是更少的保守性和更有效的比现有的稳定性准则。
In this paper, the mean square exponential stability problem is deal with for a class of uncertain stochastic neural networks with time-varying delays. By introducing a new Lyapunov–Krasovskii function, improved delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). Finally, two numerical examples are given to show that our results are less conservative and more efficiency than the existing stability criteria.