首页|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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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 coexis-tence 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 at-traction 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 impercepti-bility,extensive key space,and robustness against attacks including noise and cropping.

fractional ordermemristorsRulkov neuronmedical image watermarking

丁大为、牛炎、张红伟、杨宗立、王金、王威、王谋媛

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

2024

中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子:0.995
ISSN:1674-1056
年,卷(期):2024.33(5)
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