Open Access
Adiabatic superconducting cells for ultra-low-power artificial neural networks
Andrey E. Schegolev
1, 2
,
Publication type: Journal Article
Publication date: 2016-10-05
scimago Q2
wos Q3
SJR: 0.435
CiteScore: 4.8
Impact factor: 2.7
ISSN: 21904286
PubMed ID:
27826513
General Physics and Astronomy
General Materials Science
Electrical and Electronic Engineering
Abstract
We propose the concept of using superconducting quantum interferometers for the implementation of neural network algorithms with extremely low power dissipation. These adiabatic elements are Josephson cells with sigmoid- and Gaussian-like activation functions. We optimize their parameters for application in three-layer perceptron and radial basis function networks.
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Metrics
44
Total citations:
44
Citations from 2024:
6
(13%)
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BibTex
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GOST
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Schegolev A. E. et al. Adiabatic superconducting cells for ultra-low-power artificial neural networks // Beilstein Journal of Nanotechnology. 2016. Vol. 7. pp. 1397-1403.
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Schegolev A. E., Tereshonok M. Adiabatic superconducting cells for ultra-low-power artificial neural networks // Beilstein Journal of Nanotechnology. 2016. Vol. 7. pp. 1397-1403.
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RIS
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TY - JOUR
DO - 10.3762/bjnano.7.130
UR - https://doi.org/10.3762/bjnano.7.130
TI - Adiabatic superconducting cells for ultra-low-power artificial neural networks
T2 - Beilstein Journal of Nanotechnology
AU - Schegolev, Andrey E.
AU - Tereshonok, M.V.
PY - 2016
DA - 2016/10/05
PB - Beilstein-Institut
SP - 1397-1403
VL - 7
PMID - 27826513
SN - 2190-4286
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2016_Schegolev,
author = {Andrey E. Schegolev and M.V. Tereshonok},
title = {Adiabatic superconducting cells for ultra-low-power artificial neural networks},
journal = {Beilstein Journal of Nanotechnology},
year = {2016},
volume = {7},
publisher = {Beilstein-Institut},
month = {oct},
url = {https://doi.org/10.3762/bjnano.7.130},
pages = {1397--1403},
doi = {10.3762/bjnano.7.130}
}