Stochastic Stability Analysis of Delayed Hopfield Neural Networks with Impulse Effects

This paper studies the global exponential stability of the delayed Hopfield neural networks with both stochastic perturbations and impulse effects. By means of the Ito formula, Lyapunov-Razumikhin theorems and certain inequality techniques, some sufficient criteria are obtained which guarantee the global exponential stability of the delayed Hopfield neural networks with stochastic perturbations and impulse effects. The results characterize the intricate effects of the impulses and then can be used to estimate the feasible upper bounds of impulses. Furthermore, a numerical simulation is given to illustrate the validity of our results.

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