Stability analysis of Hopfield neural networks with uncertainty

This paper investigates stability properties of Hopfield neural networks with uncertainty. Sufficient conditions are established which ensure the existence of a globally asymptotically stable equilibrium point. The importance of these results lies in the fact that they take into account a shift in the equilibrium which may occur when the network interconnection weights are subject to a bounded uncertainty. Some examples are also given to illustrate the theorems.