Results 1 to 10 of about 10,643 (120)
NPG Asia Materials, 2023 Various memristive devices have been proposed for use in neuromorphic computing systems as artificial synapses. Analog synaptic devices with linear conductance updates during training are efficiently essential to train neural networks.
Keonhee Kim +14 more
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Nature Communications, 2022 Conventional filamentary memristors are limited in dynamics by the high electric-field dependence of the conductive filament. Here, Jeong et al. presents a method which creates a cluster-type memristor, enabling large conductance range and long data ...
Jaehyun Kang +10 more
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Scientific Reports, 2021 Mid-infrared wavelengths are called the molecular fingerprint region because it contains the fundamental vibrational modes inherent to the substances of interest. Since the mid-infrared spectrum can provide non-destructive identification and quantitative
Hwa-Seub Lee +7 more
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Novel nano-plasmonic sensing platform based on vertical conductive bridge
Scientific Reports, 2021 A novel nano-plasmonic sensing platform based on vertical conductive bridge was suggested as an alternative geometry for taking full advantages of unique properties of conductive junction while substantially alleviating burdens in lithographic process ...
Hyo-Seung Park +5 more
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Frontiers in Neuroscience, 2021 A major characteristic of spiking neural networks (SNNs) over conventional artificial neural networks (ANNs) is their ability to spike, enabling them to use spike timing for coding and efficient computing.
Laxmi R. Iyer +3 more
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A triple-level cell charge trap flash memory device with CVD-grown MoS2
Results in Physics, 2022 This study investigates the triple-level cell (TLC) memory retention of a MoS2-channel based charge trap flash (CTF) device. A top-gated CTF device with a high-κ gate dielectric is found to have a high coupling ratio, which enhances the tunneling ...
Minkyung Kim +9 more
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An Optimized Deep Spiking Neural Network Architecture Without Gradients
IEEE Access, 2022 We present an end-to-end trainable modular event-driven neural architecture that uses local synaptic and threshold adaptation rules to perform transformations between arbitrary spatio-temporal spike patterns.
Yeshwanth Bethi +4 more
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Crystals, 2023 The compatibility of memristor materials with advanced complementary metal-oxide-semiconductor (CMOS) technology is a key factor for microelectronics element base manufacturing.
Dmitry Mizginov +5 more
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Event-Based Feature Extraction Using Adaptive Selection Thresholds
Sensors, 2020 Unsupervised feature extraction algorithms form one of the most important building blocks in machine learning systems. These algorithms are often adapted to the event-based domain to perform online learning in neuromorphic hardware. However, not designed
Saeed Afshar +5 more
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The Intel neuromorphic DNS challenge
Neuromorphic Computing and Engineering, 2023 A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different neuromorphic solutions on important tasks and to compare them to state-of-the-art conventional solutions.
Jonathan Timcheck +7 more
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