Results 21 to 30 of about 77,137 (273)
Advanced Electronic Materials, 2023 Neuromorphic computing employs a great number of artificial synapses which transfer information between neurons. Conventional two‐ or three‐terminal artificial synapses with homosynaptic plasticity suffer from a positive feedback loop problem.
Fengben Xi +6 more
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Advanced Intelligent Systems, 2021 Neuromorphic electronics draw attention as innovative approaches that facilitate hardware implementation of next‐generation artificial intelligent system including neuromorphic in‐memory computing, artificial sensory perception, and humanoid robotics ...
Sung Woon Cho +3 more
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Bio-inspired artificial synapses: Neuromorphic computing chip engineering with soft biomaterials
Memories - Materials, Devices, Circuits and Systems, 2023 In the context of neuromorphic computing chip engineering, this review paper explores the area of bio-inspired artificial synapses with a focus on the incorporation of soft biomaterials.
Tanvir Ahmed
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Advanced Electronic Materials, 2023 Spintronic devices can realize multi‐state storage and be used to simulate artificial synapses or artificial neurons, which makes them have promising application prospect in the field of artificial neural networks (ANN).
Bo Zhang +6 more
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Materials Futures, 2023 Artificial synapses are electronic devices that simulate important functions of biological synapses, and therefore are the basic components of artificial neural morphological networks for brain-like computing.
Fang Nie +11 more
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A minireview on 2D materials-enabled optoelectronic artificial synaptic devices
APL Materials, 2022 Two-dimensional (2D) layered materials exhibit many unique properties, such as near-atomic thickness, electrical tunability, optical tunability, and mechanical deformability, which are characteristically distinct from conventional materials.
Changhyeon Yoo +10 more
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Supervised learning of an opto-magnetic neural network with ultrashort laser pulses [PDF]
, 2019 The explosive growth of data and its related energy consumption is pushing the need to develop energy-efficient brain-inspired schemes and materials for data processing and storage.
Chakravarty, A. +5 more
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Bi2O2Se-based CBRAM integrated artificial synapse
Heliyon, 2023 Integrating two-dimensional (2D) semiconducting materials into memristor structures has paved the way for emerging 2D materials to be employed in a vast field of memory applications. Bismuth oxyselenide (Bi2O2Se), a 2D material with high electron mobility, has attracted significant research interest owing to its great potential in various fields of ...
Dharmendra Verma +3 more
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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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Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex [PDF]
, 2015 Neocortical neurons have thousands of excitatory synapses. It is a mystery how neurons integrate the input from so many synapses and what kind of large-scale network behavior this enables.
Ahmad, Subutai, Hawkins, Jeff
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