Results 211 to 220 of about 48,649 (254)
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Zero-power optoelectronic synaptic devices
Nano Energy, 2020Abstract Synaptic devices for neuromorphic computing have been recently on the fast track of development. One of the most prominent features of synaptic devices is their potentially ultra-low energy consumption. However, relatively large energy has always been consumed to induce the postsynaptic current (PSC) of a synaptic device up to now.
Deren Yang, Yiqiang Zhang, Yue Wang
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Dual‐Modal Optoelectronic Synaptic Devices with Versatile Synaptic Plasticity
Advanced Functional Materials, 2021AbstractOptoelectronic synaptic devices that mimic biological synapses are critical building blocks of artificial neural networks (ANN) based on optoelectronic integration. Here it is shown that an optoelectronic synaptic device based on the hybrid structure of silicon nanocrystals (Si NCs) and poly(3‐hexylthiophene) (P3HT) can work with dual modes ...
Yue Wang +5 more
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Synaptic Depression as a Timing Device
Physiology, 2005A depressing synapse transforms a time interval into a voltage amplitude. The effect of that transformation on the output of the neuron and network depends on the kinetics of synaptic depression and properties of the postsynaptic neuron and network.
Lucinda A, Grande, William J, Spain
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Synaptic electronics: materials, devices and applications
Nanotechnology, 2013In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological synaptic plasticity and learning are described. The material properties and electrical switching characteristics of a variety of synaptic devices are discussed, with a focus on the use of synaptic devices for neuromorphic or brain-inspired computing ...
Duygu, Kuzum +2 more
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Synaptic Metaplasticity Realized in Oxide Memristive Devices
Advanced Materials, 2015Metaplasticity, a higher order of synaptic plasticity, as well as a key issue in neuroscience, is realized with artificial synapses based on a WO3 thin film, and the activity-dependent metaplastic responses of the artificial synapses, such as spike-timing-dependent plasticity, are systematically investigated.
Zheng-Hua, Tan +5 more
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ReRAM-based synaptic device for neuromorphic computing
2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014To compete with nonvolatile FLASH memory technology, we need to develop stackable, cross-point ReRAM device. Although various materials have been reported, it is difficult to meet device criteria such as high speed operation, low power switching, switching uniformity, endurance, long-term retention and selection device for cross-point array.
Jun-Woo Jang +3 more
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Design considerations of synaptic device for neuromorphic computing
2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital Boolean computing. Recently, two-terminal emerging memory devices that show electrically-triggered resistance modulation have been proposed as synaptic devices for neuromorphic computing.
Shimeng Yu +2 more
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Emulating Bilingual Synaptic Response Using a Junction-Based Artificial Synaptic Device
ACS Nano, 2017Excitatory and inhibitory postsynaptic potentials are the two fundamental categories of synaptic responses underlying the diverse functionalities of the mammalian nervous system. Recent advances in neuroscience have revealed the co-release of both glutamate and GABA neurotransmitters from a single axon terminal in neurons at the ventral tegmental area ...
He Tian +12 more
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Silicon-based optoelectronic synaptic devices*
Chinese Physics B, 2020High-performance neuromorphic computing (i.e., brain-like computing) is envisioned to seriously demand optoelectronically integrated artificial neural networks (ANNs) in the future. Optoelectronic synaptic devices are critical building blocks for optoelectronically integrated ANNs.
Lei Yin, Xiaodong Pi, Deren Yang
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Organic synaptic devices for neuromorphic systems
Journal of Physics D: Applied Physics, 2018Abstract The development of synaptic devices with biologically-inspired information processing functions and low power consumption is critically important for the hardware implementation of highly anticipated brain-like computing systems.
Jia Sun, Ying Fu, Qing Wan
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