Global h-synchronization of stochastic delayed high-order inertial neural networks subject to Markovian jump parameters - Wang, Junlan; Zhang, Xian; Wang, Xin; Yang, Xiaona (Journal of the Franklin Institute, 2023)
As a first exploration, this paper proposed the second-order response system (SORS) method to study the global h-synchronization (SGhS) for high-order stochastic delayed inertial neural networks subject to Markovian jumping parameters. Different from previous studies, this paper avoids reducing the order of the original drive system via substitution of variables, and directly gives the corresponding SORS. In the following, under the framework of the SORS method, a regulation function dependent Lyapunov–Krasovskii functional (RFD–LKF) is designed to realize that the considered dynamics are globally mean square h-synchronous. Particularly worth mentioning is that the method proposed in this paper can greatly reduce the amount of calculation and control cost. Ultimately, via a typical example, the superiority and validity of the derived h-synchronous criterion can be well demonstrated.