Adaptive quantitative control for robust H8 synchronization between multiplex neural networks under stochastic cyber attacks

In this paper, to resist stochastic cyber attacks and suppress the influence of the exogenous disturbance in synchronization of multiplex neural networks, an adaptive quantization control strategy is proposed. To overcome uncertainties and represent constraints in communication, an adaptive quantitative controller is designed, which is used to arrive outer synchronized behavior with an H-infinity, performance between the multiplex neural networks under stochastic cyber attacks and exogenous disturbance. The node of the multiplex networks is neural networks which is named neural sub-networks. It is assumed that the neural sub-networks in the multiplex networks with delay topology are coupled by nonlinear functions. Based on Lyapunov stability method, the conditions for the multiplex networks to achieve synchronization with an H-infinity, performance are presented. Finally, numerical example illustrates the effective of the theoretical framework. (C)& nbsp;2022 Published by Elsevier B.V.

Automated summary

An adaptive quantization control strategy is proposed in this paper to resist stochastic cyber attacks and suppress the influence of exogenous disturbance in the synchronization of multiplex neural networks. By designing an adaptive quantitative controller, the outer synchronized behavior with H-infinity performance between the multiplex neural networks under stochastic cyber attacks and exogenous disturbance is achieved.