Global robust exponential stability analysis for delayed recurrent neural networks

This paper provides a new sufficient condition for the global robust exponential stability of a delayed recurrent neural network. The conditions are expressed in terms of LMIs, which can be easily checked by various recently developed algorithms in solving convex optimization problems. Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition.