• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

具有混合时变延迟的耦合中立型神经网络的全局固定时间同步

Globally fixed-time synchronization of coupled neutral-type neural network with mixed time-varying delays.

作者信息

Zheng Mingwen, Li Lixiang, Peng Haipeng, Xiao Jinghua, Yang Yixian, Zhang Yanping, Zhao Hui

机构信息

School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China.

School of Mathematics and Statistics, Shandong University of Technology, Zibo 255000, China.

出版信息

PLoS One. 2018 Jan 25;13(1):e0191473. doi: 10.1371/journal.pone.0191473. eCollection 2018.

DOI:10.1371/journal.pone.0191473
PMID:29370248
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5784957/
Abstract

This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network model, the model in this paper is more general. A class of general discontinuous feedback controllers are designed. With the help of the definition of fixed-time synchronization, the upper right-hand derivative and a defined simple Lyapunov function, some easily verifiable and extensible synchronization criteria are derived to guarantee the fixed-time synchronization between the drive and response systems. Finally, two numerical simulations are given to verify the correctness of the results.

摘要

本文主要研究一类具有混合时变延迟的耦合中立型神经网络通过不连续反馈控制器实现全局固定时间同步。与传统中立型神经网络模型相比，本文中的模型更具一般性。设计了一类通用的不连续反馈控制器。借助固定时间同步的定义、右上导数和定义的一个简单李雅普诺夫函数，推导了一些易于验证且可扩展的同步准则，以保证驱动系统和响应系统之间的固定时间同步。最后，给出了两个数值模拟来验证结果的正确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/464c2e488437/pone.0191473.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/51d0548f0171/pone.0191473.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/5dca299068a7/pone.0191473.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/0402ddc15610/pone.0191473.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/84f8f3fa8385/pone.0191473.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/752ee6a49a3b/pone.0191473.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/382ddf025ea2/pone.0191473.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/ef8326703b5e/pone.0191473.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/17a5c032c4bd/pone.0191473.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/cb85fcc5b43b/pone.0191473.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/464c2e488437/pone.0191473.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/51d0548f0171/pone.0191473.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/5dca299068a7/pone.0191473.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/0402ddc15610/pone.0191473.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/84f8f3fa8385/pone.0191473.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/752ee6a49a3b/pone.0191473.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/382ddf025ea2/pone.0191473.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/ef8326703b5e/pone.0191473.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/17a5c032c4bd/pone.0191473.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/cb85fcc5b43b/pone.0191473.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64bc/5784957/464c2e488437/pone.0191473.g010.jpg

相似文献

1
Globally fixed-time synchronization of coupled neutral-type neural network with mixed time-varying delays.具有混合时变延迟的耦合中立型神经网络的全局固定时间同步
PLoS One. 2018 Jan 25;13(1):e0191473. doi: 10.1371/journal.pone.0191473. eCollection 2018.
2
New exponential synchronization criteria for time-varying delayed neural networks with discontinuous activations.具有不连续激活函数的时变延迟神经网络的新指数同步准则。
Neural Netw. 2015 May;65:105-14. doi: 10.1016/j.neunet.2015.02.001. Epub 2015 Feb 11.
3
Exponential synchronization of discontinuous neural networks with time-varying mixed delays via state feedback and impulsive control.基于状态反馈和脉冲控制的时变混合时滞不连续神经网络的指数同步。
Cogn Neurodyn. 2015 Apr;9(2):113-28. doi: 10.1007/s11571-014-9307-z. Epub 2014 Aug 26.
4
Fixed/prescribed-time synchronization of BAM memristive neural networks with time-varying delays via convex analysis.基于凸分析的变时滞 BAM 忆阻神经网络固定/规定时间同步。
Neural Netw. 2023 Jun;163:53-63. doi: 10.1016/j.neunet.2023.03.031. Epub 2023 Mar 27.
5
Synchronization of a Class of Switched Neural Networks with Time-Varying Delays via Nonlinear Feedback Control.通过非线性反馈控制实现时变时滞切换神经网络的同步。
IEEE Trans Cybern. 2016 Oct;46(10):2300-2310. doi: 10.1109/TCYB.2015.2475277. Epub 2015 Sep 15.
6
Global anti-synchronization of a class of chaotic memristive neural networks with time-varying delays.具有时变时滞的一类混沌忆阻神经网络的全局同步。
Neural Netw. 2013 Oct;46:1-8. doi: 10.1016/j.neunet.2013.04.001. Epub 2013 Apr 6.
7
Synchronization of Memristor-Based Coupling Recurrent Neural Networks With Time-Varying Delays and Impulses.基于忆阻器的耦合递归神经网络的时变时滞和脉冲同步。
IEEE Trans Neural Netw Learn Syst. 2015 Dec;26(12):3308-13. doi: 10.1109/TNNLS.2015.2435794. Epub 2015 Jun 3.
8
Anti-Synchronization in Fixed Time for Discontinuous Reaction-Diffusion Neural Networks With Time-Varying Coefficients and Time Delay.时变系数和时滞的不连续反应扩散神经网络的固定时间反同步。
IEEE Trans Cybern. 2020 Jun;50(6):2758-2769. doi: 10.1109/TCYB.2019.2913200. Epub 2019 May 16.
9
Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays.具有混合时滞的忆阻器型Cohen-Grossberg神经网络的有限时间同步
PLoS One. 2017 Sep 20;12(9):e0185007. doi: 10.1371/journal.pone.0185007. eCollection 2017.
10
Fixed-time synchronization of memristor-based BAM neural networks with time-varying discrete delay.基于忆阻器的 BAM 神经网络的时变离散时滞固定时间同步。
Neural Netw. 2017 Dec;96:47-54. doi: 10.1016/j.neunet.2017.08.012. Epub 2017 Sep 11.

本文引用的文献

1
The asymmetry of the entrainment range induced by the difference in intrinsic frequencies between two subgroups within the suprachiasmatic nucleus.视交叉上核内两个亚组之间固有频率差异所引起的同步范围不对称性。
Chaos. 2017 Jun;27(6):063115. doi: 10.1063/1.4989385.
2
Dynamics of oscillators globally coupled via two mean fields.通过两个平均场全局耦合的振荡器动力学。
Sci Rep. 2017 May 18;7(1):2104. doi: 10.1038/s41598-017-02283-1.
3
Entrainment range of the suprachiasmatic nucleus affected by the difference in the neuronal amplitudes between the light-sensitive and light-insensitive regions.
光敏感区与非光敏感区神经元振幅差异对视交叉上核的影响范围。
Phys Rev E. 2017 Apr;95(4-1):042409. doi: 10.1103/PhysRevE.95.042409. Epub 2017 Apr 25.
4
Dissociation between two subgroups of the suprachiasmatic nucleus affected by the number of damped oscillated neurons.两个亚群的视交叉上核分离，受阻尼振荡神经元数量的影响。
Phys Rev E. 2017 Mar;95(3-1):032302. doi: 10.1103/PhysRevE.95.032302. Epub 2017 Mar 1.
5
The effects of non-self-sustained oscillators on the en-trainment ability of the suprachiasmatic nucleus.非自维持振荡器对视交叉上核的驯化能力的影响。
Sci Rep. 2016 Nov 21;6:37661. doi: 10.1038/srep37661.
6
The synchronization of neuronal oscillators determined by the directed network structure of the suprachiasmatic nucleus under different photoperiods.不同光周期下视交叉上核有向网络结构决定的神经元振荡器同步。
Sci Rep. 2016 Jun 30;6:28878. doi: 10.1038/srep28878.
7
The circadian rhythm induced by the heterogeneous network structure of the suprachiasmatic nucleus.视交叉上核的异质网络结构所诱导的昼夜节律。
Chaos. 2016 May;26(5):053112. doi: 10.1063/1.4949012.
8
A note on finite-time and fixed-time stability.关于有限时间稳定性和固定时间稳定性的注记。
Neural Netw. 2016 Sep;81:11-5. doi: 10.1016/j.neunet.2016.04.011. Epub 2016 May 9.
9
Impact of dispersed coupling strength on the free running periods of circadian rhythms.分散耦合强度对昼夜节律自由运行周期的影响。
Phys Rev E. 2016 Mar;93(3):032414. doi: 10.1103/PhysRevE.93.032414. Epub 2016 Mar 23.
10
Complex Generalized Synchronization and Parameter Identification of Nonidentical Nonlinear Complex Systems.非相同非线性复杂系统的复杂广义同步与参数辨识
PLoS One. 2016 Mar 24;11(3):e0152099. doi: 10.1371/journal.pone.0152099. eCollection 2016.