基于马氏切换的时滞脉冲随机Cohen-Grossberg神经网络模型的均方指数稳定性分析

摘要

Focused on Cohen-Grossberg neural networks,this paper investigates the mean-square exponential stability by means of the vector Lyapunov function.This method ensures that the impulsive stochastic Cohen-Grossberg neural network is exponentially stable.Finally,an example is used to illustrate the conclusions.%通过向量Lyapunov函数,给随机CGNNs以均方估计,研究基于马氏切换的脉冲时滞随机Cohen-Grossberg神经网络模型的均方指数稳定性,并利用数值例子对结论加以证明.