王晨,张红梅,张玮玮,张海

• 1:安庆师范大学数理学院

摘要(Abstract)：

本文研究了Riemann-Liouville型分数阶时滞惯性复值神经网络的全局渐近同步问题。先引入了分数阶时滞惯性复值神经网络模型，在Riemann-Liouville型分数阶导数复合性质基础上，通过变量代换的方法将惯性系统转化为常规系统。然后，基于全局渐近同步理论和不等式技巧，得出了在新的反馈控制器下分数阶时滞惯性复值神经网络全局渐近同步的充分条件。

关键词(KeyWords)： Riemann-Liouville型神经网络;时滞;全局渐近同步;复值神经网络;惯性

Abstract:

Keywords:

基金项目(Foundation): 安徽省自然科学基金项目（1908085MA01）;; 安徽省高校自然科学研究重点项目（KJ2019A0573）;; 安徽省高校优秀青年人才支持计划项目（gxyq2019048）;; 安庆师范大学数理学院研究生学术创新项目（Y201003026）

作者(Author): 王晨,张红梅,张玮玮,张海

DOI: 10.13757/j.cnki.cn34-1328/n.2022.04.010

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