This paper deals with the anti-synchronization issue for stochastic delayed reaction–diffusion neural networks subject to semi-Markov jump parameters. A resilient fault-tolerant controller is utilized to ensure the anti-synchronization in the presence of actuator failures as well as gain perturbations, simultaneously. Firstly, by means of the Lyapunov functional and stochastic analysis methods, a mean-square exponential stability criterion is derived for the resulting error system. It is shown the obtained criterion improves a previously reported result. Then, based on the present analysis result and using several decoupling techniques, a strategy for designing the desired resilient fault-tolerant controller is proposed. At last, two numerical examples are given to illustrate the superiority of the present stability analysis method and the applicability of the proposed resilient fault-tolerant anti-synchronization control strategy, respectively.

本文研究了具有半马尔可夫跳跃参数的随机时滞反应扩散神经网络的反同步问题。弹性的容错控制器用于在执行器故障以及增益扰动的同时确保反同步。首先，通过Lyapunov函数和随机分析方法，得出了所得误差系统的均方指数稳定准则。显示所获得的标准改善了先前报道的结果。然后，基于当前的分析结果并使用几种解耦技术，提出了一种设计期望的弹性容错控制器的策略。最后，