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Non‐linear Processing in Artificial Synapses
Kybernetes, 1992Analyses the possibility of allowing non‐linear synaptic processing in Artificial Neural Networks (ANN) both theoretically and practically. The simple computer simulations described strongly suggest that this is a viable alternative, and preferable to ANN with just linear synapses, because of the savings in hardware (fewer components are needed) and ...
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Gold nanogap-based artificial synapses
Japanese Journal of Applied Physics, 2020Abstract The basic building blocks for brain-inspired computing are neurons and their inter-cellular connections, called synapses. In this paper, we report artificial synapses composed of simple gold (Au) nanogaps that function using an electromigration-based method called “activation.” In the activation technique, metal-atom ...
Keita Sakai +6 more
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Transient Potentials Transmitted by an Artificial Electrochemical Synapse
MRS Proceedings, 1990AbstractExperiments have been made with a simple device consisting of two asymmetrically insulated electrodes separated by a thin electrolytic layer. This device has been found to exhibit a wide variety of transient potentials similar to those transmitted by biological synapses, thus suggesting the possibility of constructing a network of similar ...
T. Triffet, P. Calvert, T.W. Huntoon
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Development of an artificial synapse using an electrochemical micropump
Journal of Artificial Organs, 2005Improving the resolution of artificial sensory organs requires an interface that receives external information from electronic circuits and stimulates appropriate neurons individually in response to that information. The method of electric stimulation in available artificial sensory organs is fairly nonselective; therefore, we developed a method of ...
Yasuo, Yoshimi +4 more
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Multi-ReRAM Synapses for Artificial Neural Network Training
2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019Metal-oxide-based resistive memory devices (ReRAM) are being actively researched as synaptic elements of neuromorphic co-processors for training deep neural networks (DNNs). However, device-level non-idealities are posing significant challenges. In this work we present a multi-ReRAM-based synaptic architecture with a counter-based arbitration scheme ...
Irem Boybat +10 more
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Engineer neuromimetic artificial synapses.
Proceedings of the Neuromorphic Materials, Devices, Circuits and Systems, 2023claudia lubrano +3 more
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Flexible artificial synapse with relearning function based on ion gel-graphene FET
Nano Energy, 2021Zihao Niu, Xu Mao, Xiuhan Li
exaly
Redox MXene Artificial Synapse with Bidirectional Plasticity and Hypersensitive Responsibility
Advanced Functional Materials, 2021Huanhuan Wei, Mingxue Ma, Hong Han
exaly
Highly transparent solid-state artificial synapse based on oxide memristor
Applied Surface Science, 2021Ranveer Singh +2 more
exaly