Global Asymptotic Stability of Reaction–Diffusion Cohen–Grossberg Neural Networks With Continuously Distributed Delays
Global Asymptotic Stability of Reaction–Diffusion Cohen–Grossberg Neural Networks With Continuously Distributed Delays
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DOI：
10.1109/tnn.2009.2033910
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发表时间：
2010
影响因子：
--
通讯作者：
Zhanshan Wang;Huaguang Zhang
中科院分区：
文献类型：
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作者：
Zhanshan Wang;Huaguang Zhang
研究了一类具有连续分布时滞的反应扩散Cohen-Grossberg神经网络的全局渐近稳定性。在适当的假设下，利用矩阵分解方法，利用线性矩阵不等式（LMI）方法，给出了一类具有连续分布时滞的反应扩散Cohen-Grossberg神经网络的稳定性充分条件.所得结果易于检验，并改进了已有的稳定性结果.给出了一些说明，以显示所得结果的优点比以前的结果。最后给出了一个例子来说明所得结果的有效性。
This paper is concerned with the global asymptotic stability of a class of reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays. Under some suitable assumptions and using a matrix decomposition method, we apply the linear matrix inequality (LMI) method to propose some new sufficient stability conditions for the reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays. The obtained results are easy to check and improve upon the existing stability results. Some remarks are given to show the advantages of the obtained results over the previous results. An example is also given to demonstrate the effectiveness of the obtained results.