Stability analysis of periodic solutions for stochastic reaction-diffusion high-order Cohen-Grossberg-type BAM neural networks with delays
Stability analysis of periodic solutions for stochastic reaction-diffusion high-order Cohen-Grossberg-type BAM neural networks with delays
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发表时间：
2011-09
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通讯作者：
Yunquan Ke;Chunfang Miao
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作者：
Yunquan Ke;Chunfang Miao
研究了具有时滞的随机反应扩散高阶Cohen-Grossberg型BAM神经网络周期解的均方指数稳定性。通过构造适当的Lyapunov函数，应用Ito公式和Poincare映射，给出了保证周期解均方指数稳定的一些充分条件。最后给出了一个算例，说明了本文结果的有效性。
In this paper, the mean square exponential stability of the periodic solution for stochastic reaction-diffusion high-order Cohen-Grossberg-Type BAM neural networks with time delays is investigated. By constructing suitable Lyapunov function, applying Ito formula and Poincare mapping, we give some sufficient conditions to guarantee the mean square exponential stability of the periodic solution. An illustrative example are also given in the end to show the effectiveness of our results.