• 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

具有四次非线性忆阻器的新型多涡卷神经网络在医学数字图像水印中的动态分析与应用

Dynamic analysis and application in medical digital image watermarking of a new multi-scroll neural network with quartic nonlinear memristor.

作者信息

Yu Fei, Chen Huifeng, Kong Xinxin, Yu Qiulin, Cai Shuo, Huang Yuanyuan, Du Sichun

机构信息

School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410114 China.

College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082 China.

出版信息

Eur Phys J Plus. 2022;137(4):434. doi: 10.1140/epjp/s13360-022-02652-4. Epub 2022 Apr 7.

DOI:10.1140/epjp/s13360-022-02652-4
PMID:35411291
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8988118/
Abstract

Memristor is widely used in various neural bionic models because of its excellent characteristics in biological neural activity simulation. In this paper, a piecewise nonlinear function is used to transform the quartic memristor, which is introduced into the ternary Hopfield neural network (HNN) with self-feedback, and a piecewise quartic memristive chaotic neural network model with multi-scroll is constructed. Through simulation analysis, the number of scroll layers changes with memristor parameters and has significant coexistence of multi-scroll attractors and high initial value sensitivity has been found. Using its excellent unpredictability, a digital watermarking algorithm based on wavelet transform is improved and used in the protection of personal medical data. The results show that it not only improves the confidentiality and convenience, but also ensures its robustness and has good encryption effect.

摘要

忆阻器因其在生物神经活动模拟方面的优异特性而被广泛应用于各种神经仿生模型中。本文采用分段非线性函数对四次忆阻器进行变换，将其引入具有自反馈的三元霍普菲尔德神经网络（HNN），构建了一种具有多涡卷的分段四次忆阻混沌神经网络模型。通过仿真分析发现，涡卷层数随忆阻器参数变化，存在多涡卷吸引子的显著共存现象，且具有较高的初值敏感性。利用其良好的不可预测性，对基于小波变换的数字水印算法进行改进，并将其应用于个人医疗数据保护。结果表明，该算法不仅提高了保密性和便利性，还保证了其鲁棒性，具有良好的加密效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/a4c9caeb6ba5/13360_2022_2652_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/59faf0558d00/13360_2022_2652_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/9c3243e0428d/13360_2022_2652_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/0db90e266faa/13360_2022_2652_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/ae31121fa282/13360_2022_2652_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/abdb0351a79d/13360_2022_2652_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/0df035717fff/13360_2022_2652_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/fb35a5cfed3c/13360_2022_2652_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/46c541b025e6/13360_2022_2652_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/d89314fa848d/13360_2022_2652_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/8bc50fa5aa35/13360_2022_2652_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/e390a353d9c4/13360_2022_2652_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/ac08891b1a6c/13360_2022_2652_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/e09d4e91179a/13360_2022_2652_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/daf16b99d82a/13360_2022_2652_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/c0ab5c479a16/13360_2022_2652_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/e240fa5eb638/13360_2022_2652_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/6e5cf1651d5b/13360_2022_2652_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/a4c9caeb6ba5/13360_2022_2652_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/59faf0558d00/13360_2022_2652_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/9c3243e0428d/13360_2022_2652_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/0db90e266faa/13360_2022_2652_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/ae31121fa282/13360_2022_2652_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/abdb0351a79d/13360_2022_2652_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/0df035717fff/13360_2022_2652_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/fb35a5cfed3c/13360_2022_2652_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/46c541b025e6/13360_2022_2652_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/d89314fa848d/13360_2022_2652_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/8bc50fa5aa35/13360_2022_2652_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/e390a353d9c4/13360_2022_2652_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/ac08891b1a6c/13360_2022_2652_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/e09d4e91179a/13360_2022_2652_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/daf16b99d82a/13360_2022_2652_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/c0ab5c479a16/13360_2022_2652_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/e240fa5eb638/13360_2022_2652_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/6e5cf1651d5b/13360_2022_2652_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/750a/8988118/a4c9caeb6ba5/13360_2022_2652_Fig18_HTML.jpg

相似文献

1
Dynamic analysis and application in medical digital image watermarking of a new multi-scroll neural network with quartic nonlinear memristor.具有四次非线性忆阻器的新型多涡卷神经网络在医学数字图像水印中的动态分析与应用
Eur Phys J Plus. 2022;137(4):434. doi: 10.1140/epjp/s13360-022-02652-4. Epub 2022 Apr 7.
2
Design and Analysis of Multiscroll Memristive Hopfield Neural Network With Adjustable Memductance and Application to Image Encryption.具有可调忆导的多涡卷忆阻霍普菲尔德神经网络的设计与分析及其在图像加密中的应用
IEEE Trans Neural Netw Learn Syst. 2023 Oct;34(10):7824-7837. doi: 10.1109/TNNLS.2022.3146570. Epub 2023 Oct 5.
3
Multi-piecewise quadratic nonlinearity memristor and its 2N-scroll and 2N + 1-scroll chaotic attractors system.多分段二次非线性忆阻器及其2N-scroll和2N + 1-scroll混沌吸引子系统
Chaos. 2017 Mar;27(3):033114. doi: 10.1063/1.4979039.
4
Star Memristive Neural Network: Dynamics Analysis, Circuit Implementation, and Application in a Color Cryptosystem.星型忆阻神经网络：动力学分析、电路实现及其在彩色密码系统中的应用
Entropy (Basel). 2023 Aug 25;25(9):1261. doi: 10.3390/e25091261.
5
Coexisting Behaviors of Asymmetric Attractors in Hyperbolic-Type Memristor based Hopfield Neural Network.基于双曲型忆阻器的霍普菲尔德神经网络中不对称吸引子的共存行为
Front Comput Neurosci. 2017 Aug 23;11:81. doi: 10.3389/fncom.2017.00081. eCollection 2017.
6
Dynamics of heterogeneous Hopfield neural network with adaptive activation function based on memristor.基于忆阻器的自适应激活函数的非均匀 Hopfield 神经网络动力学。
Neural Netw. 2024 Oct;178:106408. doi: 10.1016/j.neunet.2024.106408. Epub 2024 May 22.
7
Constructing Multiscroll Memristive Neural Network With Local Activity Memristor and Application in Image Encryption.基于局部活性忆阻器构建多涡卷忆阻神经网络及其在图像加密中的应用
IEEE Trans Cybern. 2024 Jul;54(7):4039-4048. doi: 10.1109/TCYB.2024.3377011. Epub 2024 Jul 11.
8
Multi-scroll attractor and its broken coexisting attractors in cyclic memristive neural network.循环忆阻神经网络中的多涡卷吸引子及其破碎的共存吸引子
Chaos. 2023 Aug 1;33(8). doi: 10.1063/5.0159391.
9
Four-scroll attractor on the dynamics of a novel Hopfield neural network based on bi-neurons without bias current.基于无偏置电流双神经元的新型霍普菲尔德神经网络动力学中的四-scroll吸引子
Heliyon. 2022 Oct 14;8(10):e11046. doi: 10.1016/j.heliyon.2022.e11046. eCollection 2022 Oct.
10
Extreme multistability in a memristor-based multi-scroll hyper-chaotic system.基于忆阻器的多涡卷超混沌系统中的极端多稳定性
Chaos. 2016 Jul;26(7):073107. doi: 10.1063/1.4958296.

引用本文的文献

1
A novel 4D chaotic system coupling with dual-memristors and application in image encryption.一种与双忆阻器耦合的新型四维混沌系统及其在图像加密中的应用。
Sci Rep. 2024 Nov 28;14(1):29615. doi: 10.1038/s41598-024-80445-8.
2
Dynamic Analysis and FPGA Implementation of a New Fractional-Order Hopfield Neural Network System under Electromagnetic Radiation.电磁辐射下新型分数阶霍普菲尔德神经网络系统的动态分析与现场可编程门阵列实现
Biomimetics (Basel). 2023 Nov 21;8(8):559. doi: 10.3390/biomimetics8080559.
3
Star Memristive Neural Network: Dynamics Analysis, Circuit Implementation, and Application in a Color Cryptosystem.

本文引用的文献

1
Electromagnetic induction effects on electrical activity within a memristive Wilson neuron model.电磁感应对忆阻型威尔逊神经元模型内电活动的影响。
Cogn Neurodyn. 2022 Oct;16(5):1221-1231. doi: 10.1007/s11571-021-09764-0. Epub 2022 Jan 20.
2
Multi-scroll hidden attractor in memristive HR neuron model under electromagnetic radiation and its applications.电磁辐射下忆阻 HR 神经元模型中的多-scroll 隐藏吸引子及其应用。
Chaos. 2021 Jan;31(1):011101. doi: 10.1063/5.0035595.
3
The missing memristor found.缺失的忆阻器被找到。
星型忆阻神经网络：动力学分析、电路实现及其在彩色密码系统中的应用
Entropy (Basel). 2023 Aug 25;25(9):1261. doi: 10.3390/e25091261.
4
Four-scroll attractor on the dynamics of a novel Hopfield neural network based on bi-neurons without bias current.基于无偏置电流双神经元的新型霍普菲尔德神经网络动力学中的四-scroll吸引子
Heliyon. 2022 Oct 14;8(10):e11046. doi: 10.1016/j.heliyon.2022.e11046. eCollection 2022 Oct.
5
A novel activation function based recurrent neural networks and their applications on sentiment classification and dynamic problems solving.一种基于新型激活函数的递归神经网络及其在情感分类和动态问题解决中的应用。
Front Neurorobot. 2022 Sep 23;16:1022887. doi: 10.3389/fnbot.2022.1022887. eCollection 2022.
6
Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme.基于事件触发控制策略的具有时变延迟的忆阻型Cohen-Grossberg神经网络的渐近同步
Micromachines (Basel). 2022 Apr 30;13(5):726. doi: 10.3390/mi13050726.
Nature. 2008 May 1;453(7191):80-3. doi: 10.1038/nature06932.
4
Secure spread spectrum watermarking for multimedia.多媒体安全扩频水印技术
IEEE Trans Image Process. 1997;6(12):1673-87. doi: 10.1109/83.650120.