H∞ control and delay-dependent stabilization for neural networks with discrete and distributed time-varying delays using a new integral inequality approach

This paper is focused on the problem of delay-dependent stabilization for neural networks (NNs) with discrete and distributed time-varying delays. The main objective of this work is to design a H_∞ control law to ensure the asymptotical stability of the closed-loop system. Besides, the less conservative stability criterion is derived in terms of linear matrix inequalities (LMIs) by constructing an appropriate Lyapunov-Krasovskii functionals and some effective mathematical technique. Furthermore, by using a new integral inequality which is showed to have a great potential efficient in practice, an improved sufficient condition is presented for the existence of the H_∞ control problem. At last, two numerical examples are given to demonstrate the effectiveness and the advantage of the proposed method.