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- Title
Firing pattern transition of fractional-order memristor-coupled Hindmarsh–Rose neurons model and its medical image encryption for region of interest.
- Authors
Ding, Dawei; Chen, Siqi; Zhang, Hongwei; Yang, Zongli; Jin, Fan; Liu, Xiang
- Abstract
This paper proposes a fractional-order memristor-coupled Hindmarsh–Rose neurons model, which the number and stability of equilibrium points are related to the coupling strength. By Lyapunov exponent spectrum, local attraction basins, spectral entropy and so on, firing pattern transition of the system is revealed. In order to deeply expose information transmission in neural networks, the bifurcation behavior of different neuronal orders is studied by three dimensional two-parameter bifurcation diagram. Furthermore, when external stimulus is applied to a neuron, the system produces anti-monotonicity and bursting behavior. A microcontroller based on ARM is used to implement the system and verify various firing activities. Finally, we use the properties of the chaotic system to design a medical image encryption algorithm based on the region of interest. Numerical simulation results demonstrate that the proposed algorithm can improve the security of medical image transmission and resource utilization. It provides strong resistance against attacks to ensure privacy.
- Subjects
IMAGE encryption; DIAGNOSTIC imaging; NEURONS; MEDICAL imaging systems; NEURAL transmission; NEURAL circuitry
- Publication
Nonlinear Dynamics, 2024, Vol 112, Issue 12, p10529
- ISSN
0924-090X
- Publication type
Article
- DOI
10.1007/s11071-024-09593-w