一类具有时变时滞的复值忆阻神经网络的全局一致渐近稳定性
Global Uniform Asymptotic Stability of a Class of Complex-valued Memristive Neural Networks with Time-varying Delays
王继禹 1贾秀玲 1段誉2
作者信息
- 1. 郑州工商学院基础教学部,河南 郑州 451400
- 2. 贵州工程应用技术学院理学院,贵州 毕节 551700
- 折叠
摘要
利用Yang不等式以及构造Lyapuonv函数等技巧,给出了 一类具有时变时滞的复值忆阻神经网络平衡点的全局一致渐近稳定性的新结果.最后,通过实例验证了所得结果的有效性和可行性.
Abstract
In this paper,by utilizing the Lyapunov functional method,applying Young inequality technique and some analysis techniques,some new results is obtained for the global uniform asymptotic stability of a class of complex-valued memristive neural networks with time-varying delays.Finally,the validity and feasibility of our results are demonstrated by an example.
关键词
复值忆阻神经网络/Yang不等式/全局一致渐近稳定性Key words
Complex-valued Memristive Neural Networks/Young Inequality/Global Uniform Asymptotic Stability引用本文复制引用
基金项目
郑州工商学院第二届科研创新重点项目(2022-KYZD-06)
毕节市科学技术项目(毕科联合[2023]28号)
出版年
2024
NETL
NSTL
万方数据