时滞无关的CNN稳定性分析及保密通信应用  

Stability Analysis of Delay-independent Cellular Neural Network and Its Application in Secret Communication

作　　者：张小红[1] 李德音[1] 

机构地区：[1]江西理工大学信息工程学院,江西赣州341000

出　　处：《计算机工程》2013年第1期168-174,共7页Computer Engineering

基　　金：国家自然科学基金资助项目(11062002);江西省自然科学基金资助项目(2010GZS0083);江西省教育厅科技计划基金资助项目(GJJ11470)

摘　　要：针对存在延时情况下的细胞神经网络系统稳定性判定问题,构造新型Lyapunov-Krasovskii泛函并结合Lyapunov稳定性理论及线性矩阵不等式,得到用于判定时滞细胞神经网络具有唯一平衡点和全局渐近稳定性的一组充分条件。数值仿真实验结果证明,该判定条件具有较好的可验证性和可实现性,且与时滞无关,适用于保密通信。Determining stability problems of Cellular Neural Network（CNN） with delays is researched and a set of sufficient conditions which is used to judge whether cellular neural networks with delays has a unique equilibrium and global asymptotic stability is received.A new Lyapunov-Krasovskii functional is constructed and methods including Lyapunov stability theory and linear matrix inequalities is adopted.The digital simulation results prove effectiveness with feasibility and delay-independent property of the judgment condition.Examples are given to illustrate the good application of the conclusion in secure communication.

关 键 词：细胞神经网络 全局渐近稳定性 时滞无关 LYAPUNOV-KRASOVSKII泛函 线性矩阵不等式 保密通信 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]