A Novel Delay-Dependent Global Stability Criterion of Delayed Hopfield Neural Networks

This paper analyzes the global asymptotic stability of delayed Hopfield neural networks by utilizing Lyapunov functional method and a generalized inequality technique. A new sufficient condition ensuring global asymptotic stability of the unique equilibrium point of delayed Hopfield neural networks is obtained. The result is related to the size of delays. The obtained conditions show to be less conservative and restrictive than that reported in the literature. A numerical simulation is given to illustrate the efficiency of our result.