Exponential stability of the neural networks with time-varying discrete and distributed delays

摘要：

For a class of generalized neural networks(NNs) with discrete and distributed time-varying delays, this paper is concerned with the problems of determining the global exponential stability and estimating the exponential convergence rate. By introducing a novel Lyapunov-Krasovskii functional and some appropriate free-weighting matrices, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). Finally, a numerical examples is given to show the superiority of the obtained results.

关键词： Neural networks Time-varying delay Exponential stability linear matrix inequalities

作者: Qingbo Li Shujuan Wang Yuanyuan Wu

作者单位: Department of Mathematics and Information Science, Zhengzhou University of Light Industry, Zhengzhou School of Automation, Southeast University, Nanjing 210096

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 2453-2458

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）