Global Exponential Stability Analysis for Recurrent Neural Networks with Time-varying Delay

This letter deals with the exponential stability problem for static recurrent neural networks (RNNs) with time-varying delay. By Lyapunov functional method and linear matrix inequality technique, some novel delay-dependent criteria are established to ensure the exponential stability of the considered neural network. The proposed exponential stability criteria are expressed in terms of linear matrix inequalities, and can be checked using the recently developed algorithms. A numerical example is given to show that the obtained criteria can provide less conservative results than some existing ones.