天津师范大学学报（自然科学版）2025，Vol.45Issue(1)：1-6,6.DOI:10.19638/j.issn1671-1114.20250101
一类比例时滞细胞神经网络ω-周期解的全局多项式稳定性
Global polynomial stability of ω-periodic solution for a class of proportional delayed cellular neural networks
摘要
Abstract
The global polynomial stability of ω-periodic solution for a class of proportional delayed cellular neural networks is studied.Firstly,the delay differential inequality is established by applying M-matrix theory and constructing of auxiliary func-tion.Then,by using the constructed delay differential inequality and contraction mapping theorem,the delay-independent and delay-dependent global polynomial stability criteria for ω-periodic solution of the studied system are obtained.When the exter-nal input is constant,the global polynomial stability criteria for equilibrium point of the corresponding system are obtained.Fi-nally,the correctness of the obtained results are verified by two numerical examples and simulations.关键词
比例时滞/细胞神经网络/周期解/全局多项式稳定性Key words
proportional delay/cellular neural networks/periodic solution/global polynomial stability分类
数学引用本文复制引用
韩佳澎,周立群..一类比例时滞细胞神经网络ω-周期解的全局多项式稳定性[J].天津师范大学学报（自然科学版）,2025,45(1):1-6,6.基金项目
天津市自然科学基金资助项目(18JCYBJC85800) （18JCYBJC85800）
天津师范大学研究生科研创新项目(2023KYCX053Z). （2023KYCX053Z）
