随机区间时滞Hopfield神经网络的指数稳定性

Exponential stability of stochastic interval Hopfield Neural Networks with variable-delays

讨论了一类带有可变时滞的随机区间Hopfield神经网络的指数稳定性 ,利用李雅普罗夫函数和Razuminkhin 定理 ,得到了一些关于该系统均方指数稳定与几乎必然稳定的时滞无关和时滞相关的充分性判据 。

A type of stochastic interval Hopfield Neural Network w ith time-varying delayed was studied. Using Lyapunov function and Razumikhin th eorem, some new delay-dependent and delay-independent sufficient criteria of i ts mean square global exponential stability or almost surely global exponential stability were given. All the results were generalizations of some recent result s reported in the literature for stochastic Neural Networks with constant delays or some certain cases with variable-delays.