Global asymptotically robust stability of cellular neural networks with time-varying delay

摘要：

Time-delay is frequently encountered in neural networks, and it is often a source of instability and oscillations in a system. It is very important to research the stability of delayed neural network, especially for global asymptotically robust stability of the neural network with time-varying delay. In the letter, a novel method is proposed in this note for global asymptotically robust stability of cellular neural networks with time-varying delay. New delay-dependent global asymptotically robust stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). Finally, numerical examples are given to demonstrate the effect of the proposed method.

关键词： delayed cellular neural networks (DCNNs) Lyapunov functional LMI global asymptotically robust stability

作者: Xue-Li Wu Zhantong Zhou Wen-Xia Du Yang Li

作者单位: Hebei University of Science and Technology, Shijiazhuang, 050054 Engineering Technology Research Cen Hebei University of Science and Technology, Shijiazhuang, 050054 Engineering Technology Research Cen YanShan University Qinhuangdao 066004 Hebei Normal University, Shijiazhuang 050031

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3249-3254

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）