Exponential Stability for Delayed Cellular Neural Networks and Estimate of Exponential Convergence Rate  

作　　者：LIXiaoping JIAOLicheng 

机构地区：[1]SchoolofMechanical-ElectronicEngineering,XidianUniversity,Xi‘an710071,China [2]NationalKeyLaboratoryforRadarSignalProcessing,XidianUniversity,Xi’an710071,China

出　　处：《Chinese Journal of Electronics》2003年第3期385-387,共3页电子学报（英文版）

摘　　要：A new sufficient condition for global ex-ponential stability and lower bounds on the rate of ex-ponential convergence of delayed cellular neural networks (DCNNs) is obtained by means of a method based on delay differential inequality. The method which does not make use of any Lyapunov functionals, is simple and effective for the stability analysis of neural networks with delay. Some previously established results in the literature are shown to be special cases of the presented result.

关 键 词：全局指数稳定性 指数收敛速率 时延细胞神经网络 LYAPUNOV函数 移动图象 目标识别 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TN95[自动化与计算机技术—控制科学与工程]