Memristor-induced hyperchaos, multiscroll and extreme multistability in fractional-order HNN: Image encryption and FPGA implementation

Neural Networks, Journal Year: 2023, Volume and Issue: 171, P. 85 - 103

Published: Dec. 5, 2023

Language: Английский

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Privacy Protection of Medical Data Based on Multi-Scroll Memristive Hopfield Neural Network

IEEE Transactions on Network Science and Engineering, Journal Year: 2022, Volume and Issue: 10(2), P. 845 - 858

Published: Nov. 24, 2022

Memristive Hopfield neural network (MHNN) has complex dynamic behavior, which is suitable for encryption applications. In order to ensure the information security of medical data transmitted in Internet Things (IoT), we propose three new MHNN models by using a non-ideal flux-controlled memristor model with multi-piecewise nonlinearity. these models, there are dynamical behaviors such as coexisting attractors, multi-scroll attractors and grid attractors. terms hardware, proposed implemented field programmable gate array (FPGA). addition, provide complete set sharing solution, helpful referral patients receive timely treatment. The whole solution successfully verified on Raspberry Pi, encrypted Computed Tomography (CT) image safely under Message Queuing Telemetry Transport (MQTT) protocol, CT subjected basic analysis. results show that ciphertext histogram evenly distributed, correlation between adjacent pixels almost 0, entropy reaches 7.9977, values number change rate (NPCR) unified average intensity (UACI) 99.6078% 33.4875%. not only performs exchange data, but also protects privacy patients.

Language: Английский

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Firing pattern in a memristive Hodgkin–Huxley circuit: Numerical simulation and analog circuit validation

Chaos Solitons & Fractals, Journal Year: 2023, Volume and Issue: 172, P. 113627 - 113627

Published: June 7, 2023

Language: Английский

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Initial-offset-boosted coexisting hyperchaos in a 2D memristive Chialvo neuron map and its application in image encryption

Nonlinear Dynamics, Journal Year: 2023, Volume and Issue: 111(21), P. 20447 - 20463

Published: Oct. 5, 2023

Language: Английский

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A class of 2n+1 dimensional simplest Hamiltonian conservative chaotic systems and fast image encryption schemes

Applied Mathematical Modelling, Journal Year: 2023, Volume and Issue: 125, P. 351 - 374

Published: Oct. 6, 2023

Language: Английский

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Memristor-Based Neural Network Circuit of Associative Memory With Overshadowing and Emotion Congruent Effect

IEEE Transactions on Neural Networks and Learning Systems, Journal Year: 2024, Volume and Issue: 36(2), P. 3618 - 3630

Published: Jan. 9, 2024

Most memristor-based neural network circuits consider only a single pattern of overshadowing or emotion, but the relationship between and emotion is ignored. In this article, circuit associative memory with congruent effect designed, under multiple emotions taken into account. The designed mainly consists an module, inhibition feedback module. generation recovery different are realized by functions from achieved module Finally, blocking caused long-term implemented proposed can be applied to bionic emotional robots offers some references for brain-like systems.

Language: Английский

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Periodic and chaotic spiking behaviors in a simplified memristive Hodgkin-Huxley circuit

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 179, P. 114458 - 114458

Published: Jan. 12, 2024

Language: Английский

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Synchronization in scale-free neural networks under electromagnetic radiation

Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2024, Volume and Issue: 34(3)

Published: March 1, 2024

The functional networks of the human brain exhibit structural characteristics a scale-free topology, and these neural are exposed to electromagnetic environment. In this paper, we consider effects magnetic induction on synchronous activity in biological networks, effect is evaluated by four-stable discrete memristor. Based Rulkov neurons, network model established. Using initial value strength as control variables, numerical simulations carried out. research reveals that exhibits multiple coexisting behaviors, including resting state, period-1 bursting synchronization, asynchrony, chimera states, which dependent different values multi-stable addition, observe can either enhance or weaken synchronization when parameters neurons vary. This investigation significant importance understanding adaptability organisms their

Language: Английский

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Memristor-Based Operant Conditioning Neural Network With Blocking and Competition Effects

IEEE Transactions on Industrial Informatics, Journal Year: 2024, Volume and Issue: 20(8), P. 10209 - 10218

Published: May 7, 2024

Operant conditioning is an important learning mechanism for organisms, as well a basic theory reinforcement in artificial intelligence. Although there are already some memristive neural circuits operant conditioning, they can only process single stimulus and cannot handle multiple inputs simultaneously. This article proposes multi-input network that incorporates blocking competing effects. achieve the overshadowing effects presence of learn efficiently complex environments. In addition, it time differences between signals excitations, random exploration, feedback learning, experience memory, decision-making based on experience, adaptive low-reward Finally, feasibility proposed circuit function verified through PSPICE simulation. work provides implementation idea hardware

Language: Английский

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A memristive map neuron under noisy electric field

Chinese Journal of Physics, Journal Year: 2024, Volume and Issue: 91, P. 287 - 298

Published: July 25, 2024

Language: Английский

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