Adaptive Finite-Time Synchronization Of Inertial Neural Networks With Time-Varying Delays Via Intermittent Control

In this paper, the adaptive finite-time synchronization is investigated for inertial neural networks with time-varying delays. The second-order inertial systems can be transformed into two first-order differential systems by selecting the appropriate variable substitution. Using the adaptive periodically intermittent controllers, the slave system can realize synchronization with the master system in finite time. By the several differential inequalities and finite-time stability theory, some simple finite-time synchronization criteria for an array of inertial neural networks are derived. A numerical example is finally provided to illustrate the effectiveness of the obtained theoretical results.