Novel Criteria on Global Ezponential Stability of Fuzzy Cohen-Grossberg Neural Networks with Time-varying Delay

摘要：

Global exponential stability problem of the fuzzy Cohen-Grossberg neural networks (FCGNNs) with timevarying delay is considered in this paper. By using the Lyapunov-Krasovskii method, the novel sufficient conditions are obtained to guarantee the global exponential stability of the considered system. These conditions are expressed in the terms of linear matrix inequalities (LMIs), and can be checked by resorting to the Matlab LMI Toolbox. Finally, a numerical example is given to show the effectiveness of the obtained results.

关键词： Fuzzy Cohen-Grossberg neural networks Time-varying Delay Delay-dependent Global ezponential stability Linear matriz inequality (LMI)

作者: Yongsu Kim Huaguang Zhang Xin Zhang Lili Cui

作者单位: Information Science and Engineering, Northeastern University, Shenyang 110004,China

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: 2986-2991

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）