This article is devoted to discussing the problem of global Mittag-Leffler synchronization (GMLS) for the Caputo-type fractional-order fuzzy delayed inertial neural networks (FOFINNs). First of all, both inertial and fuzzy terms are taken into account in the system. For the sake of reducing the influence caused by the inertia term, the order reduction is achieved by the measure of variable substitution. The introduction of fuzzy terms can evade fuzziness or uncertainty as much as possible. Subsequently, a nonlinear delayed controller is designed to achieve GMLS. Utilizing the inequality techniques, Lyapunov’s direct method for functions and Razumikhin theorem, the criteria for interpreting the GMLS of FOFINNs are established. Particularly, two inferences are presented in two special cases. Additionally, the availability of the acquired results are further confirmed by simulations.

本文致力于讨论 Caputo 型分数阶模糊延迟惯性神经网络 (FOFINN) 的全局 Mittag-Leffler 同步 (GMLS) 问题。首先，系统中同时考虑了惯性和模糊项。为了减小惯性项带来的影响，通过变量替换的措施实现降阶。模糊术语的引入可以尽可能地规避模糊性或不确定性。随后，设计了一个非线性延迟控制器来实现 GMLS。利用不等式技术、Lyapunov 直接函数法和 Razumikhin 定理，建立了解释 FOFINN 的 GMLS 的标准。特别地，在两个特殊情况下提出了两个推论。此外，