Results 21 to 30 of about 84,713 (260)
Optoelectronic Synaptic Devices for Neuromorphic Computing [PDF]
Advanced Intelligent Systems, 2020 Neuromorphic computing can potentially solve the von Neumann bottleneck of current mainstream computing because it excels at self‐adaptive learning and highly parallel computing and consumes much less energy. Synaptic devices that mimic biological synapses are critical building blocks for neuromorphic computing.
Yue Wang +7 more
openaire +2 more sources
All oxide based flexible multi-folded invisible synapse as vision photo-receptor
Scientific Reports, 2023 All oxide-based transparent flexible memristor is prioritized for the potential application in artificially simulated biological optoelectronic synaptic devices.
Ping-Xing Chen +2 more
doaj +1 more source
Synaptic memory devices from CoO/Nb:SrTiO 3 junction [PDF]
Royal Society Open Science, 2019 Non-volatile memristors are promising for future hardware-based neurocomputation application because they are capable of emulating biological synaptic functions. Various material strategies have been studied to pursue better device performance, such as lower energy cost, better biological plausibility, etc.
Le Zhao +5 more
openaire +3 more sources
Spiking Neural Networks for Inference and Learning: A Memristor-based Design Perspective [PDF]
, 2019 On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential.
Abbott +56 more
core +2 more sources
Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition [PDF]
, 2015 A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density.
Saxena, Vishal, Wu, Xinyu, Zhu, Kehan
core +3 more sources
Neuromorphic Learning towards Nano Second Precision [PDF]
, 2013 Temporal coding is one approach to representing information in spiking neural networks. An example of its application is the location of sounds by barn owls that requires especially precise temporal coding. Dependent upon the azimuthal angle, the arrival
Meier, Karlheinz +3 more
core +1 more source
Vertical 3-Terminal Artificial Synaptic Devices
Journal of Flexible and Printed Electronics, 2023 Recently, synaptic devices have the advantages of being able to process information in parallel. However, nondestructive weight control is limited in 2-terminal synaptic devices because reading and writing are conducted in a common electrode. Hence, 3-terminal
Nahyun Jeong, Kyung-Geun Lim
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Opto-Electronic Advances, 2022 The human visual system, dependent on retinal cells, can be regarded as a complex combination of optical system and nervous system. Artificial retinal system could mimic the sensing and processing function of human eyes.
Caihong Li +9 more
doaj +1 more source
A geographically distributed bio-hybrid neural network with memristive plasticity [PDF]
, 2017 Throughout evolution the brain has mastered the art of processing real-world inputs through networks of interlinked spiking neurons. Synapses have emerged as key elements that, owing to their plasticity, are merging neuron-to-neuron signalling with ...
Corna, Andrea +10 more
core +1 more source
MoS2-based Charge-trapping synaptic device with electrical and optical modulated conductance
Nanophotonics, 2020 The synapse is one of the fundamental elements in human brain performing functions such as learning, memorizing, and visual processing. The implementation of synaptic devices to realize neuromorphic computing and sensing tasks is a key step to artificial
Zhang Min +9 more
doaj +1 more source