Finite-time synchronization of memristive neural networks with time-varying delays via two control methods

In this paper, on the basis of the Lyapunov stability theory and finite-time stability lemma, the finite-time synchronization problem for memristive neural networks with time-varying delays is studied by two control methods. First, the discontinuous state-feedback control rule containing integral part for square sum of the synchronization error and the discontinuous adaptive control rule are designed for realizing synchronization of drive-response memristive neural networks in finite time, respectively. Then, by using some important inequalities and defining suitable Lyapunov functions, some algebraic sufficient criteria guaranteeing finite-time synchronization are deduced for drive-response memristive neural networks in finite time. Furthermore, we give the estimation of the upper bounds of the settling time of finite-time synchronization. Lastly, the effectiveness of the obtained sufficient criteria guaranteeing finite-time synchronization is validated by simulation.