New Global Stability Criteria for Interval Delayed Neural Networks

摘要：

This paper is concerned with the problem of global robust exponential stability for a class of interval cellular neural networks with time-constant delays. By introducing a novel Lyapunov-Krasovslii functional combining with the idea of delay fractioning, some delay-dependent conditions are derived in terms of the linear matrix inequality, which guarantee the considered interval delayed cellular neural networks to be global exponentially stable. Moreover, the conservatism can be notably reduced as the the fractioning goes thinner. A numerical example is provided to demonstrate the advantage of the proposed result.

作者: Xiaojie Su Yunkai Feng Ligang Wu Gaoliang Peng

作者单位: Space Control and Inertial Technology Research Center Harbin Institute of Technology Harbin,150001,P School of Mechanics and Electronics Harbin Institute of Technology Harbin,150001,P.R.China

会议类型: 国际会议

会议名称: The 3rd International Symposium on Systems and Control in Aeronautics and Astronautics(第三届航空航天系统与控制国际会议 ISSCAA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 982-986

在线出版日期: 2010-01-08（万方平台首次上网日期，不代表论文的发表时间）