Delay-dependent global stability condition for delayed Hopfield neural networks

In this paper, by utilizing the Lyapunov functional method and combining with the linear matrix inequality approach, we analyze the global asymptotic stability of delayed Hopfield neural networks (HNNs). A new sufficient condition ensuring the global stability of the unique equilibrium point of delayed HNNs is obtained, which is dependent on the size of delays. This condition is less restrictive and conservative than that given in the earlier references. In addition, an example is also provided to illustrate the applicability of the result.