A New Criterion of Global Exponential Robust Stability of Periodic Solution for the Static Neural Network with Time-Delays

摘要

The dynamics of the local field neural networks have been studied extensively, and many good results have been obtained. It should be pointed out that, the global robust stability for the static neural networks with time-delays received very little attention despite its practical importance. Based on the fixed point theory, Lyapunov functional and differential inequality technique, a new criterion of global exponential robust stability of periodic solution for the static neural networks with time delays is derived. An example is exploited to show the usefulness of the derived global exponential robust stability conditions.