求解逆拟变分不等式的时滞神经网络  

Time-delay Neural Networksfor Solving Inverse Quasi-variational Inequalities

作　　者：张欢 郭正洁 冯世强[1] ZHANG Huan;GUO Zheng-jie;FENG Shi-qiang(School of Mathematics&Information,China West Normal University,Nanchong Sichuan 637009,China)

机构地区：[1]西华师范大学数学与信息学院,四川南充637009

出　　处：《西华师范大学学报（自然科学版）》2025年第1期36-41,共6页Journal of China West Normal University(Natural Sciences)

基　　金：国家自然科学基金项目(11871059);四川省自然科学基金项目(2022NSFSC0558);西华师大研究生教育改革研究项目(2022XM24)。

摘　　要：文章主要研究求解欧氏空间中逆拟变分不等式问题的一种时滞神经网络。首先,在余强制和Lipschitz连续性的条件下,利用不动点原理得到逆拟变分不等式问题解的存在性和唯一性。进一步考虑求解逆拟变分不等式问题的一种时滞神经网络,并且在强单调和Lipschitz连续性的条件下证明该时滞神经网络的全局指数稳定性。In this paper,a delay neural network for solving inverse quasi-variational inequalities in Euclidean space was studied.Firstly,under the conditions of cocoercion and Lipschitz continuity,we obtained the existence and uniqueness of the solution of the inverse quasi-variational inequality problem by using the fixed point principle.Furthermore,we considered a delayed neural network for solving the inverse quasi-variational inequality problem,and proved the global exponential stability of the delayed neural network under the conditions of strongly monotone and Lipschitz continuity.

关 键 词：余强制 LIPSCHITZ连续性 强单调 逆拟变分不等式 时滞神经网络 全局指数稳定 

分 类 号：O221[理学—运筹学与控制论]