4.1 Article

Stability analysis of Markovian jumping stochastic Cohen-Grossberg neural networks with mixed time delays

期刊

IEEE TRANSACTIONS ON NEURAL NETWORKS
卷 19, 期 2, 页码 366-370

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2007.910738

关键词

Cohen-Grossberg neural networks (CGNNs); delay-dependent criteria; linear matrix inequality (LMI); Markovian jumping; mixed delay

向作者/读者索取更多资源

In this letter, the global asymptotical stability analysis problem is considered for a class of Markovian jumping stochastic Cohen-Grossberg neural networks (CGNNs) with mixed delays including discrete delays and distributed delays. An alternative delay-dependent stability analysis result is established based on the linear matrix inequality (LMI) technique, which can easily be checked by utilizing the numerically efficient Matlab LMI toolbox. Neither system transformation nor free-weight matrix via Newton-Leibniz formula is required. Two numerical examples are included to show the effectiveness of the result.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.1
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据