Global asymptotic stability for a class of nonlinear neural networks with multiple delays

This paper investigates the global asymptotic stability (GAS) for a class of nonlinear neural networks with multiple delays. Based on Lyapunov stability theory and the linear matrix inequality (LMI) technique, a less conservative delay-dependent stability criterion is derived. The present result is shown to be less conservative than those given in the literature.