Tunable superconducting neurons for networks based on radial basis functions

Tunable superconducting neurons for networks based on radial basis functions

The hardware implementation of signal microprocessors based on superconducting technologies seems relevant for a number of niche tasks where performance and energy efficiency are critically important. In this paper, we consider the basic elements for superconducting neural networks on radial basis f...

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Bibliographic Details
Main Authors: Andrey E. Schegolev, Nikolay V. Klenov, Sergey V. Bakurskiy, Igor I. Soloviev, Mikhail Yu. Kupriyanov, Maxim V. Tereshonok, Anatoli S. Sidorenko
Format: Article
Language:English
Published: Beilstein-Institut 2022-05-01
Series:Beilstein Journal of Nanotechnology
Subjects:
networks on radial basis functions
josephson circuits
radial basis functions (rbfs)
spintronics
superconducting electronics
superconducting neural network
Online Access:https://doi.org/10.3762/bjnano.13.37

Internet

https://doi.org/10.3762/bjnano.13.37

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