https://doi.org/10.1140/epjb/s10051-024-00743-y
Regular Article - Statistical and Nonlinear Physics
Circuit design and image encryption of CNN chaotic system based on memristor
Northwest Normal University, Lanzhou, Gansu
Province, China
Received:
30
April
2024
Accepted:
1
July
2024
Published online:
14
July
2024
A new general-purpose voltage-controlled memristor with a fourth power term is designed in this paper. Based on this memristor, a new four-dimensional chaotic system, the memristor cell neural network (CNN) chaotic system, is constructed with complex dynamic characteristics, high spectral entropy complexity (SE), and wavelet entropy complexity (C0). Combination with analysis including phase portraits, equilibrium points, dissipativity, Lyapunov exponent spectrum, bifurcation diagrams, transient phenomena, spectral entropy complexity (SE), and wavelet entropy complexity (C0), the dynamic characteristics of the new system are thoroughly explored. Constructed analog circuits for the new memristor and new memristor CNN chaotic system, and a digital circuit is implemented using a field-programmable gate array. Combining the new memristor CNN chaotic system with DNA encoding operations for image encryption applications, its excellent encryption effectiveness and high security are discovered through analysis of key sensitivity, histogram, information entropy, correlation, keyspace, and robustness.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
