Resilient fixed-time synchronization of delayed fuzzy memristive reaction-diffusion neural networks under DoS attacks

Abstract

This work focuses on the resilient fixed-time synchronization of delayed fuzzy memristive reaction-diffusion neural networks under denial-of-service (DoS) attacks. To efficaciously tolerate the aperiodic DoS attacks, a new appropriate controller is designed to ensure the fixed-time resilient synchronization of the systems. Moreover, two mild sufficient conditions are first proposed and the constrained techniques of attacking intervals are employed to overcome the challenge of estimating the upper bound of the settling time under aperiodic DoS attacks. Lastly, an example is utilized to illustrate the effectiveness and feasibility of the theoretical result.