New Global Exponential Stability Resultsfor Impulsive Discrete-Time Cellular Neural Networks with Time-Varying Delays

摘要：

This paper studies the problem of global exponential stability and exponential convergence rate for a class of impulsive discrete-time cellular neural networks with time-varying delays. By means of the Lyapunov stability theory, some inequality analysis techniques and a discrete-time Halanay-type inequality technique, several stability criteria for ensuring global exponential stability of discrete-time cellular neural networks are derived, and the estimated exponential convergence rate is provided as well. Finally, numerical examples are provided to illustrate the effectiveness and usefulness of the obtained criteria.

关键词： Impulsive discrete-time cellular neural networks global exponential stability exponential convergence rate Halanay inequality

作者: Yuanqiang Chen Honglei Xu

作者单位: Department of Mathematics,National Minoritces College of Guizhou Guiyang, China School of Information Science and Engineering,Central South University Changsha, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 442-445

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）