基于非周期间歇控制的复值惯性神经网络指数同步

惠姣姣; 于娟

doi:10.13568/j.cnki.651094.651316.2021.03.16.0003

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基于非周期间歇控制的复值惯性神经网络指数同步

数理科学 | 更新时间：2026-01-21

- 基于非周期间歇控制的复值惯性神经网络指数同步
- 基于非周期间歇控制的复值惯性神经网络指数同步
- 新疆大学学报（自然科学版中英文） 2022年39卷第2期页码：151-160
- 作者机构：
  
  新疆大学数学与系统科学学院
- 作者简介：
- 基金信息：
  
  新疆维吾尔自治区自然科学基金(2018D01C057)
- DOI：10.13568/j.cnki.651094.651316.2021.03.16.0003
  中图分类号： TP183
- 纸质出版：2022
- 稿件说明：
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[1]惠姣姣,于娟.基于非周期间歇控制的复值惯性神经网络指数同步[J].新疆大学学报(自然科学版)(中英文),2022,39(02):151-160.
[1]惠姣姣,于娟.基于非周期间歇控制的复值惯性神经网络指数同步[J].新疆大学学报(自然科学版)(中英文),2022,39(02):151-160. DOI： 10.13568/j.cnki.651094.651316.2021.03.16.0003.

DOI：10.13568/j.cnki.651094.651316.2021.03.16.0003.

摘要

本文主要研究具有混合时变时滞的惯性神经网络指数同步问题.首先

提出了一类具有离散时滞和有限分布时滞(混合时滞)的复值惯性神经网络模型；其次

通过直接对二阶惯性神经网络模型设计非周期间歇控制策略

利用Lyapunov泛函理论和不等式技巧

给出主从复值惯性神经网络的指数同步准则；最后

通过一个数值算例来验证理论结果的有效性.

Abstract

This paper mainly studies the exponential synchronization problem of inertial neural networks with mixed delays. Firstly

a type of complex-valued inertial neural networks model which is composed of discrete delays and finite distributed delays(called mixed delays) is introduced. Secondly

by directly designing aperiodic intermittent control for the second-order inertial neural models

the theory of Lyapunov functionals and inequality techniques are employed to establish the synchronization criteria of complex-valued inertial neural networks.Finally

the effectiveness of the theoretical results are verified via providing a numerical example.

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references

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基于非周期间歇控制的惯性神经网络同步/滞后同步（英文）