首页|Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

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Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this paper.Here,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance.Then,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms.Subsequently,it is used toward secure communication application scenarios.Taking it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)model.Eventually,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

cellular neural networkmemristorhardware circuitcompressive sensingprivacy data protection

周新卫、蒋东华、Jean De Dieu Nkapkop、Musheer Ahmad、Jules Tagne Fossi、Nestor Tsafack、吴建华

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Department of Information Engineering,Gongqing College,Nanchang University,Jiujiang 332020,China

School of Computer Science and Engineering,Sun Yat-Sen University,Guangzhou 511400,China

Department of Electrical Engineering and Industrial Computing,University Institute of Technology,Douala,Cameroon

Department of Computer Engineering,Jamia Millia Islamia,New Delhi 110025,India

Department of Physics,Faculty of Science,University of Yaounde,Cameroon

Electrical Engineering Department and Industrial Computing of ISTAMA,University of Douala,Douala,Cameroon

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2024

10.1088/1674-1056/ad03dd

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(4)
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