The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Brain-Like Initial-Boosted Hyperchaos and Application in Biomedical Image Encryption
Open accessAbstract
Neural networks have been widely and deeply studied in the field of computational neurodynamics. However, coupled neural networks and their brain-like chaotic dynamics have not been noticed yet. In this article, we focus on the coupled neural network-based brain-like initial boosting coexisting hyperchaos and its application in biomedical image encryption. We first construct a memristive-coupled neural network (MCNN) model based on two subneural networks and one multistable memristor synapse. Then we investigate its coupling strength-related dynamical behaviors, initial states-related dynamical behaviors, and initial-boosted coexisting hyperchaos using bifurcation diagrams, phase portraits, Lyapunov exponents, and attraction basins. The numerical results demonstrate that the proposed MCNN not only can generate hyperchaotic attractors with high complexity but also can boost the attractor positions by switching their initial states. This makes the MCNN more suitable for many chaos-based engineering applications. Moreover, we design a biomedical image encryption scheme to explore the application of the MCNN. Performance evaluations show that the designed cryptosystem has several advantages in the keyspace, information entropy, and key sensitivity. Finally, we develop a field-programmable gate array test platform to verify the practicability of the presented MCNN and the designed medical image cryptosystem.
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Cites
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Self-citationTwo-Dimensional Memristive Hyperchaotic Maps and Application in Secure Communication
Li, H., Hua, Z., Bao, H., Zhu, L., Chen, M., & Bao, B. (2021) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2020.3022539 · Cited by 287
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Cited by
Sun, J., Li, C., Wang, Z., & Wang, Y. (2024) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3312405 · Cited by 172
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Self-citationFibonacci Q-Matrix, Hyperchaos, and Galois Field (2⁸) for Augmented Medical Image Encryption
El-Damak, D., Alexan, W., Mamdouh, E., El-Aasser, M., Fathy, A., & Gabr, M. (2024) · IEEE Access · doi:10.1109/access.2024.3433499 · Cited by 75
Real time hybrid medical image encryption algorithm combining memristor-based chaos with DNA coding
Demirkol, A. S., Sahin, M. E., Karakaya, B., Ulutas, H., Ascoli, A., & Tetzlaff, R. (2024) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2024.114923 · Cited by 73
Dynamic rotation medical image encryption scheme based on improved Lorenz chaos
Man, Z., Gao, C., Dai, Y., & Meng, X. (2024) · Nonlinear Dynamics · doi:10.1007/s11071-024-09732-3 · Cited by 48
Metadata
- Authors
- Lin, H., Wang, C., Cui, L., Sun, Y., Xu, C., & Yu, F.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2022-12
- Volume
- 18
- Issue
- 12
- Pages
- 8839-8850
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W4214829631
- Cited by
- 291
- References
- 35
- FWCI
- 20.40
- Type
- journal article
- Language
- en
- Open access
- green
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