吉首大学学报（自然科学版）2025，Vol.46Issue(5)：19-28,10.DOI:10.13438/j.cnki.jdzk.2025.05.004
基于事件触发的不连续惯性神经网络有限时间同步
Finite-Time Synchronization of Discontinuous Inertial Neural Networks Based on Event-Triggered Mechanism
摘要
Abstract
The finite-time event-triggered control problem of a class of time-delay inertial neural net-works with discontinuous activation functions is studied.The second-order inertial neural network is transformed into the form of a first-order neural network through the variable substitution method.Based on the characteristics of discontinuous activation functions,the solution of the neural network is defined using the Filippov solution framework.A new event-triggered controller is designed in combina-tion with the finite-time stability theory,and the trigger interval is restricted to avoid the Zeno phenom-enon.On this basis,the discrimination criteria for the network to achieve finite-time synchronization are derived to ensure that this type of second-order inertial neural network achieves synchronization within a finite time.关键词
事件触发控制/惯性神经网络/有限时间同步/时滞Key words
event triggering mechanism/inertial neural network/finite time synchronization/time-lag分类
数理科学引用本文复制引用
曾智源,戴厚平,陈腾..基于事件触发的不连续惯性神经网络有限时间同步[J].吉首大学学报（自然科学版）,2025,46(5):19-28,10.基金项目
国家自然科学基金地区资助项目(12461047) （12461047）
