New Global Exponential Stability Resultsfor Impulsive Discrete-Time Cellular Neural Networks with Time-Varying Delays
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.
Impulsive discrete-time cellular neural networks global exponential stability exponential convergence rate Halanay inequality
Yuanqiang Chen Honglei Xu
Department of Mathematics,National Minoritces College of Guizhou Guiyang, China School of Information Science and Engineering,Central South University Changsha, China
国际会议
成都
英文
442-445
2010-12-17(万方平台首次上网日期,不代表论文的发表时间)