Robust Adaptive Convergence of Uncertain CGNNs with Mixed Delays

摘要：

In this paper, the problem of robust adaptive convergence for uncertain Cohen-Grossberg neural networks(CGNNs) with mixed delays is investigated Using the Lyapunov method and employing a novel lemma, some delay-independent conditions are derived to ensure the state variables of the discussed robust system to converge, globally, uniforymly, exponentially to a ball in the state space with a pre-specified convergence rate. The effectiveness and usefulness of the results has been verified by a numerical example with graphical illustrations.

作者: Xiaohong Wang Minghui Jiang

作者单位: College of Science,China Three Gorges University,Yichang,Hubei,443002,China

会议类型: 国际会议

会议名称: 2008 IEEE International Symposium on IT in Medicine and Education(2008信息技术在医学和教育中的应用国际研讨会)(ITME 2008)

会议地点: 厦门

会议语种:英文

页码: 1094-1097

在线出版日期: 2008-12-12（万方平台首次上网日期，不代表论文的发表时间）