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 as-
sumed 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.

Tải file New criteria for stability and stabilization of neural networks with mixed interval time-varying delays tại đây