Chinese Journal of Physics, Год журнала: 2024, Номер 91, С. 966 - 976
Опубликована: Авг. 27, 2024
Язык: Английский
Chinese Journal of Physics, Год журнала: 2024, Номер 91, С. 966 - 976
Опубликована: Авг. 27, 2024
Язык: Английский
Neural Networks, Год журнала: 2023, Номер 171, С. 85 - 103
Опубликована: Дек. 5, 2023
Язык: Английский
Процитировано
140IEEE Transactions on Network Science and Engineering, Год журнала: 2022, Номер 10(2), С. 845 - 858
Опубликована: Ноя. 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.
Язык: Английский
Процитировано
136Chaos Solitons & Fractals, Год журнала: 2023, Номер 172, С. 113627 - 113627
Опубликована: Июнь 7, 2023
Язык: Английский
Процитировано
61Nonlinear Dynamics, Год журнала: 2023, Номер 111(21), С. 20447 - 20463
Опубликована: Окт. 5, 2023
Язык: Английский
Процитировано
50Applied Mathematical Modelling, Год журнала: 2023, Номер 125, С. 351 - 374
Опубликована: Окт. 6, 2023
Язык: Английский
Процитировано
50IEEE Transactions on Neural Networks and Learning Systems, Год журнала: 2024, Номер 36(2), С. 3618 - 3630
Опубликована: Янв. 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.
Язык: Английский
Процитировано
47Chaos Solitons & Fractals, Год журнала: 2024, Номер 179, С. 114458 - 114458
Опубликована: Янв. 12, 2024
Язык: Английский
Процитировано
27Chaos An Interdisciplinary Journal of Nonlinear Science, Год журнала: 2024, Номер 34(3)
Опубликована: Март 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
Язык: Английский
Процитировано
26IEEE Transactions on Industrial Informatics, Год журнала: 2024, Номер 20(8), С. 10209 - 10218
Опубликована: Май 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
Язык: Английский
Процитировано
22Chinese Journal of Physics, Год журнала: 2024, Номер 91, С. 287 - 298
Опубликована: Июль 25, 2024
Язык: Английский
Процитировано
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