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 ofω-periodic solution for a class of proportional delayed cellular neural networks

作　　者：韩佳澎 周立群[1] HAN Jiapeng;ZHOU Liqun(School of Mathematical Sciences,Tianjin Normal University,Tianjin 300387,China)

机构地区：[1]天津师范大学数学科学学院,天津300387

出　　处：《天津师范大学学报(自然科学版)》2025年第1期1-6,共6页Journal of Tianjin Normal University:Natural Science Edition

基　　金：天津市自然科学基金资助项目(18JCYBJC85800);天津师范大学研究生科研创新项目(2023KYCX053Z).

摘　　要：研究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.首先通过M-矩阵理论并构造辅助函数建立微分不等式,然后利用该时滞微分不等式和压缩映射定理,得到了所研究系统ω-周期解的时滞独立和时滞依赖的全局多项式稳定的判定准则.当外部输入为常数时,得到了相应系统平衡点的全局多项式稳定的判定准则.最后通过2个数值算例及其仿真验证了所得结果的正确性.The global polynomial stability ofω-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 forω-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 

分 类 号：O175.13[理学—数学] TP183[理学—基础数学]