Results 1 to 10 of about 13,015 (262)
Everything You Wish to Know About Memristors But Are Afraid to Ask [PDF]
Radioengineering, 2015 This paper classifies all memristors into three classes called Ideal, Generic, or Extended memristors. A subclass of Generic memristors is related to Ideal memristors via a one-to-one mathematical transformation, and is hence called Ideal Generic ...
L.Chua
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Nanoscale Insights into the Dynamics of Conductive Filament Growth/Dissolution in 2D Material‐Based Memristors [PDF]
Advanced Science2D materials have drawn widespread attention as promising candidates for electrochemical metallization (ECM) memristors. However, some critical questions related to the resistance switching (RS) behaviors of 2D material‐based ECM memristors, such as the ...
Chen Li +8 more
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Gallium Oxide Memristors: A Review of Resistive Switching Devices and Emerging Applications [PDF]
NanomaterialsGallium oxide (Ga2O3)-based memristors are gaining traction as promising candidates for next-generation electronic devices toward in-memory computing, leveraging the unique properties of Ga2O3, such as its wide bandgap, high thermodynamic stability, and ...
Alfred Moore, Yaonan Hou, Lijie Li
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Mechanical Properties Analysis of Flexible Memristors for Neuromorphic Computing [PDF]
Nano-Micro LettersHighlights This review systematically summarizes materials system, development history, device structure, stress simulation and applications of flexible memristors.
Zhenqian Zhu +3 more
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Efficient implementation of the Hodgkin-Huxley potassium channel via a single volatile memristor [PDF]
Frontiers in NeuroscienceIntroductionIn 2012, potassium and sodium ion channels in Hodgkin-Huxley-based brain models were shown to exhibit memristive behavior. This positioned memristors as strong candidates for implementing biologically accurate artificial neurons.
Lennart P. L. Landsmeer +12 more
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Nat CommunOptical memristors represent a monumental leap in the fusion of photonics and electronics, heralding a new era of applications from neuromorphic computing to artificial intelligence. However, current technologies are hindered by complex fabrication, limited endurance, high optical loss or low modulation depth.
Li C +15 more
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Perceptrons from memristors [PDF]
Neural Networks, 2020 Memristors, resistors with memory whose outputs depend on the history of their inputs, have been used with success in neuromorphic architectures, particularly as synapses and non-volatile memories. However, to the best of our knowledge, no model for a network in which both the synapses and the neurons are implemented using memristors has been proposed ...
Silva, Francisco +4 more
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Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2023 An ideal memristor that has been theoretically predicted almost a half-century ago is a nonlinear power dissipating circuit element. Nowadays, memristive systems such as thin films which are not ideal memristors are also called memristors.
Ertuğrul Karakulak +2 more
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Entangled quantum memristors [PDF]
Physical Review A, 2021 We propose the interaction of two quantum memristors via capacitive and inductive coupling in feasible superconducting circuit architectures. In this composed system the input gets correlated in time, which changes the dynamic response of each quantum memristor in terms of its pinched hysteresis curve and their nontrivial entanglement.
Kumar, Shubham +6 more
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Filament-free memristors for computing
Nano Convergence, 2023 Memristors have attracted increasing attention due to their tremendous potential to accelerate data-centric computing systems. The dynamic reconfiguration of memristive devices in response to external electrical stimuli can provide highly desirable novel
Sanghyeon Choi +3 more
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