Abstract

This paper considers the global exponential stability and stabilization for a class of neural networks with mixed interval time-varying delays. The time delay is assumed to be a continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a set of new Lyapunov-Krasovskii functionals combined with Newton-Leibniz formula, new delay-dependent criteria for exponential stability and stabilization of the system are established in terms of linear matrix inequalities (LMIs), which allows to compute simultaneously the two bounds that characterize the exponential stability of the solution. Numerical examples are included to illustrate the effectiveness of the results.