Global h-Synchronization for High-Order Delayed Inertial Neural Networks via Direct SORS Strategy

This work studies the issue of global h-synchronization about high-order delayed inertial neural networks via a second-order response system (SORS) approach. Note that the h-synchronization is a flexible definition which can generalize different special synchronization types by choosing different regulation function$\hbar $. By constructing a regulation function-dependent Lyapunov–Krasovskii functional (RFD–LKF), a novel delay-dependent global h-synchronization criterion is obtained. Furthermore, an adaptive control algorithm is designed to estimate control gains online, which is useful to guarantee global h-synchronization performance as well as to decrease the control cost. And finally, the superiority of the method is verified via three numerical examples.