Further stability analysis for neural networks with time-varying interval delay

Abstract

This paper provides improved results on stability condition for a class of neural networks (NNs) with time-varying interval delay. The activation functions of the NNs are assumed to be more general. Based on a new augmented Lyapunov-Krasovskii functional, the improved delay-dependent stability criterion for delay NNs is obtained in terms of linear matrix inequalities (LMIs). It is shown that the new criterion can provide less conservative results than some existing ones. A numerical example is given to demonstrate the effectiveness and the benefits of the proposed method. © 2009 Springer Berlin Heidelberg.