"JOURNAL OF RADIO ELECTRONICS" (Zhurnal Radioelektroniki)  ISSN 1684-1719, N 9, 2016

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Adiabatic superconducting cells for energy-efficient neural networks: physical foundations

 

A. E. Shegolev 1,2, N. V. Klenov 1-5, I. I. Soloviev 3,5,6, M. V. Tereshonok 2

1 Lomonosov Moscow State University, Physical Faculty

2 Moscow Technical University of Communications and Informatics

3 Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics

4 Dukhov All-Russia Research Institute of Automatics

5 Moscow Institute of Physics and Technology, State University

6 Lukin Scientific Research Institute of Physical Problems

The paper is received on September 16, 2016

Abstract. Superconducting digital systems are considered recently as one of the most promising options for the physical implementation of fast and energy-efficient artificial neural networks. Possibility to combine advantages of Josephson active antenna structures, amplifiers and analog-to-digital converters together with neural network circuits in complexes for cognitive signal processing is of particular interest. 
We propose physical foundations for a new energy efficient implementation of artificial neural network algorithms. We describe two neuron cells: Sigma-cell and Gauss-cell with sigmoid- and Gaussian-like activation functions respectively. We developed simple theory to optimize their transfer (flux-to-current) functions for
application in three-layer perceptron and radial basis functions networks. Design of these cells is inspired by adiabatic quantum flux parametron; the both have simple topology and low energy consumption, working in superconducting regime. Maintained similarity of designs allows to use well-developed adiabatic superconductor logic cells in interface circuits. 

Key words: Josephson effect, superconductivity, artificial neural network, neuron, activation function, RBF network, Sigma-cell, S-cell, Gauss-cell, G-cell.

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