宿州学院学报2024，Vol.39Issue(12)：6-12,7.DOI:10.3969/j.issn.1673-2006.2024.12.002
脉冲时滞G-Hopfield神经网络的稳定性分析
Stability Analysis for G-Hopfield Neural Networks with Pulse Delay
摘要
Abstract
The stability problem of a class of G-Brownian motion driven pulse delayed random Hopfield neural net-works is studied.Under the framework of sublinear expectation,the conditions for mean square exponential stability of a stochastic neural network system are constructed based on the definition of mean square exponential input for state stability.Introducing a stochastic system driven by G-Brownian motion,applying the theory of G-stochastic a-nalysis,and utilizing the G-Itô formula,mathematical induction,and scaling techniques of some inequalities,a set of sufficient conditions for determining the stability of the system's trivial solution's mean square exponential input is obtained.Finally,the application of the test results were obtained through examples.关键词
G-布朗运动/随机Hopfield神经网络/均方指数输入对状态稳定Key words
G-Brownian motion/Random Hopfield neural network/Mean square index input for state stability分类
数理科学引用本文复制引用
高丽丽,潘玉荣,夏福全..脉冲时滞G-Hopfield神经网络的稳定性分析[J].宿州学院学报,2024,39(12):6-12,7.基金项目
蚌埠学院自然科学重点项目(2020ZR04zd) （2020ZR04zd）
蚌埠学院科研启动基金(BBXY2020KYQD05) （BBXY2020KYQD05）
蚌埠学院教学研究项目(2020SYKC5) （2020SYKC5）
安徽高校自然科学研究重点项目(KJ2021A1128). （KJ2021A1128）
