4.1 Article

Improved Delay-Dependent Asymptotic Stability Criteria for Delayed Neural Networks

期刊

IEEE TRANSACTIONS ON NEURAL NETWORKS
卷 19, 期 12, 页码 2154-2161

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2008.2006904

关键词

Asymptotic stability; delay-dependent criteria; linear matrix inequality (LMI); neural networks; uncertain delay

资金

  1. National Natural Science Foundation of China [60864002]
  2. Australian Research Council

向作者/读者索取更多资源

This brief is concerned with asymptotic stability of neural networks with uncertain delays. Two types of uncertain delays are considered: one is constant while the other is time varying. The discretized Lyapunov-Krasovskii functional (LKF) method is integrated with the technique of introducing the free-weighting matrix between the terms of the Leibniz-Newton formula. The integrated method leads to the establishment of new delay-dependent sufficient conditions in form of linear matrix inequalities for asymptotic stability of delayed neural networks (DNNs). A numerical simulation study is conducted to demonstrate the obtained theoretical results, which shows their less conservatism than the existing stability criteria.

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