Global stability of steady steady state of delay differential equations in neural network model

We prove that a strong attractor of a discrete map implies global stability of a corresponding system of delay differential equations. We apply this result to a delayed Hopfield's model. We prove also that every attractor one-dimentional map is a strong attractor and we present an example that this is not true in dimension higher than one.