摘要
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.
作者
周新卫
蒋东华
Jean De Dieu Nkapkop
Musheer Ahmad
Jules Tagne Fossi
Nestor Tsafack
吴建华
Xinwei Zhou;Donghua Jiang;Jean De Dieu Nkapkop;Musheer Ahmad;Jules Tagne Fossi;Nestor Tsafack;Jianhua Wu(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)
