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Abstract <p>The Gauss neuron is a nonlinear input signal converter required for the implementation of neural networks based on radial basis functions. It was previously shown that such an element can be realized as a two-junction Josephson interferometer shunted by an additional inductance. For certain values of the inductances, the transfer function can be described by a Gaussian distribution, which determines the name of the proposed interferometers. This work derives new analytical expressions for the transfer function (TF) of the Gauss neuron, providing a deeper understanding of its structure as well as of the dependence of the TF shape on the inductive parameters of the device.</p>

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Analysis of a Superconducting Gauss Neuron Transfer Function

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • F. A. Razorenov,
  • N. S. Shuravin,
  • L. N. Karelina,
  • V. V. Bol’ginov

摘要

Abstract

The Gauss neuron is a nonlinear input signal converter required for the implementation of neural networks based on radial basis functions. It was previously shown that such an element can be realized as a two-junction Josephson interferometer shunted by an additional inductance. For certain values of the inductances, the transfer function can be described by a Gaussian distribution, which determines the name of the proposed interferometers. This work derives new analytical expressions for the transfer function (TF) of the Gauss neuron, providing a deeper understanding of its structure as well as of the dependence of the TF shape on the inductive parameters of the device.