Emulating long-term synaptic dynamics with memristive devices [PDF]
, 2016 The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS technology, the ...
Berdan, Radu +5 more
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How ligands affect resistive switching in solution-processed HfO2 nanoparticle assemblies [PDF]
, 2018 Advancement of resistive random access memory (ReRAM) requires fully understanding the various complex, defect-mediated transport mechanisms to further improve performance.
Wang, Jiaying +6 more
core +2 more sources
The Spectral Response of the Dual Microdisk Resonator Based on BaTiO3 Resistive Random Access Memory
Micromachines, 2022 With the resistive random access memory (ReRAM) devices based on the Al/BaTiO3 (BTO)/ITO structure fabricated at hand, by cross-analyzing the resistive memory characteristics in terms of various barium titanate (BTO) film thicknesses, it is found that ...
Ricky Wenkuei Chuang +2 more
doaj +1 more source
Resistive switching in ZrO2 films: physical mechanism for filament formation and dissolution [PDF]
, 2014 Resistive switching devices, also called memristors, have attracted much attention due to their potential memory, logic and even neuromorphic applications.
MacLaren, DA +2 more
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Metal oxide semiconductor nanomembrane-based soft unnoticeable multifunctional electronics for wearable human-machine interfaces [PDF]
, 2019 Wearable human-machine interfaces (HMIs) are an important class of devices that enable human and machine interaction and teaming. Recent advances in electronics, materials, and mechanical designs have offered avenues toward wearable HMI devices. However,
Chen, Jie +9 more
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PRAP-PIM: A weight pattern reusing aware pruning method for ReRAM-based PIM DNN accelerators
High-Confidence Computing, 2023 Resistive Random-Access Memory (ReRAM) based Processing-in-Memory (PIM) frameworks are proposed to accelerate the working process of DNN models by eliminating the data movement between the computing and memory units.
Zhaoyan Shen +5 more
doaj +1 more source
RRAM variability and its mitigation schemes [PDF]
, 2016 Emerging technologies such as RRAMs are attracting significant attention due to their tempting characteristics such as high scalability, CMOS compatibility and non-volatility to replace the current conventional memories.
Amat, Esteve +3 more
core +1 more source
Characteristics of the dynamics of breakdown filaments in Al2O3/InGaAs stacks [PDF]
, 2015 In this paper, the Al2O3/InGaAs interface was studied by X-ray photoelectron spectroscopy (XPS) after a breakdown (BD) event at positive bias applied to the gate contact.
Cohen Weinfeld, K. +3 more
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Sequence learning in a spiking neuronal network with memristive synapses
Neuromorphic Computing and Engineering, 2023 Brain-inspired computing proposes a set of algorithmic principles that hold promise for advancing artificial intelligence. They endow systems with self learning capabilities, efficient energy usage, and high storage capacity.
Younes Bouhadjar +5 more
doaj +1 more source
Advanced Intelligent Systems, 2020 Herein, a feasible method is provided for circuit implementation of the convolutional neural network (CNN) in neuromorphic hardware using the multiple layers‐stacked resistance switching random access memory (ReRAM).
Yumin Kim +8 more
doaj +1 more source