On the global stability of delayed neural networks

Lyapunov functional methods, combining with some inequality techniques, are employed to study the global asymptotic stability of delayed neural networks. Without assuming Lipschitz conditions on the activation functions, a new sufficient condition is established. Such criteria allows us to include non-Lipschitzian activation functions in the design of delayed neural networks. The result presented here is also discussed from the point of view of its relationship to some previous results.