脉冲时滞Hopfield神经网络的全局指数稳定性

Global Exponential Stability of Hopfield Neural Networks with Delays and Impulses

研究一类具有脉冲控制的时滞Hopfield神经网络的全局指数稳定性,通过Lyapunov-Krasovskii稳定性理论和Halanay不等式等方法,构造合适的Lyapunov泛函,利用不等式技巧得到了确保时滞神经网络在脉冲控制下全局指数稳定的一个充分条件,保证了Hofield神经网络在脉冲控制下的全局指数稳定,并估计了系统的指数收敛率。为了便于计算和验证结论的有效性,给出一个简化的充分条件。最后通过数值实例的实验仿真证实了结论的有效性、可行性。

In this paper, a model of Hopfield neural networks with delays and impulses is considered. By using the Lyapunov- Krasovskii stability theory and Halanay inequality with Lyapunov function and inequality skill, a new sufficient condition for global exponential stability of impulsive delay model are obtained, ensure the stability of Hopfield Neural Network with impulses, and estimated the rate of convergence. A simply sufficient condition is given for the calculation and verification. An example is given to illustrate the validity of theory.