Finite-time synchronization of inertial memristive neural networks with time-varying delays via sampled-date control

In this paper, the finite-time synchronization issues for inertial memristive neural networks with time-varying delay using hybrid feedback controller with sampled-date term are investigated. Firstly, by constructing a proper variable substitution,the original system is transformed into the first order differential system. Next, constructing a useful Lyapunov function, a suitable controller and using inequality techniques, some new testable algebraic criterion are obtained for ensuring the finite-time synchronization goal. Moreover, we discussed deeply on the relation between the parameter ξi and estimated value of settling time in the different cases, and we can obtain the minimum estimated value of settling time. Finally, the effectiveness of the theoretical results have been illustrated via two numerical examples.