Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

doi:10.1088/1674-1056/ad322b

中国物理B ›› 2024, Vol. 33 ›› Issue (5): 50503-050503.doi: 10.1088/1674-1056/ad322b

Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

Dawei Ding(丁大为), Yan Niu(牛炎), Hongwei Zhang(张红伟)†, Zongli Yang(杨宗立), Jin Wang(王金), Wei Wang(王威), and Mouyuan Wang(王谋媛)

School of Electronics and Information Engineering, Anhui University, Hefei 230601, China

收稿日期:2023-12-26 修回日期:2024-02-22 接受日期:2024-03-11 出版日期:2024-05-20 发布日期:2024-05-20
通讯作者: Hongwei Zhang E-mail:hwzhang@ahu.edu.cn
基金资助:
This study was funded by the National Natural Science Foundation of China (Grant No. 12302070) and the Ningxia Science and Technology Leading Talent Training Program (Grant No. 2022GKLRLX04).

Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

Dawei Ding(丁大为), Yan Niu(牛炎), Hongwei Zhang(张红伟)†, Zongli Yang(杨宗立), Jin Wang(王金), Wei Wang(王威), and Mouyuan Wang(王谋媛)

School of Electronics and Information Engineering, Anhui University, Hefei 230601, China

Received:2023-12-26 Revised:2024-02-22 Accepted:2024-03-11 Online:2024-05-20 Published:2024-05-20
Contact: Hongwei Zhang E-mail:hwzhang@ahu.edu.cn
Supported by:
This study was funded by the National Natural Science Foundation of China (Grant No. 12302070) and the Ningxia Science and Technology Leading Talent Training Program (Grant No. 2022GKLRLX04).

摘要/Abstract

摘要： This article proposes a novel fractional heterogeneous neural network by coupling a Rulkov neuron with a Hopfield neural network (FRHNN), utilizing memristors for emulating neural synapses. The study firstly demonstrates the coexistence of multiple firing patterns through phase diagrams, Lyapunov exponents (LEs), and bifurcation diagrams. Secondly, the parameter related firing behaviors are described through two-parameter bifurcation diagrams. Subsequently, local attraction basins reveal multi-stability phenomena related to initial values. Moreover, the proposed model is implemented on a microcomputer-based ARM platform, and the experimental results correspond to the numerical simulations. Finally, the article explores the application of digital watermarking for medical images, illustrating its features of excellent imperceptibility, extensive key space, and robustness against attacks including noise and cropping.

关键词: fractional order, memristors, Rulkov neuron, medical image watermarking

Abstract: This article proposes a novel fractional heterogeneous neural network by coupling a Rulkov neuron with a Hopfield neural network (FRHNN), utilizing memristors for emulating neural synapses. The study firstly demonstrates the coexistence of multiple firing patterns through phase diagrams, Lyapunov exponents (LEs), and bifurcation diagrams. Secondly, the parameter related firing behaviors are described through two-parameter bifurcation diagrams. Subsequently, local attraction basins reveal multi-stability phenomena related to initial values. Moreover, the proposed model is implemented on a microcomputer-based ARM platform, and the experimental results correspond to the numerical simulations. Finally, the article explores the application of digital watermarking for medical images, illustrating its features of excellent imperceptibility, extensive key space, and robustness against attacks including noise and cropping.

Key words: fractional order, memristors, Rulkov neuron, medical image watermarking

中图分类号: (Nonlinear dynamics and chaos)

05.45.-a

87.18.Sn (Neural networks and synaptic communication) 05.45.Vx (Communication using chaos)

Dawei Ding(丁大为), Yan Niu(牛炎), Hongwei Zhang(张红伟), Zongli Yang(杨宗立), Jin Wang(王金), Wei Wang(王威), and Mouyuan Wang(王谋媛). Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application[J]. 中国物理B, 2024, 33(5): 50503-050503.

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Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

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