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

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.