Hardware electronic circuit modeling neuron with diode based non-linearity

The purpose of this study is hardware implementation of the nonlinear electronic generator of neuron-like activity developed previously using nGSPICE software. Based on the previously developed circuits, we simplified the design by reducing the number of components and rearranging nonlinear elements. Various approximations of the nonlinear function were considered by means of different number n of diodes in the circuit, and the dependence of the output signal on n was investigated. Quasi-linear and nonlinear generation regimes were studied. Also, a simple partial bifurcation analysis was performed in order to study the mechanisms of oscillation birth in the circuit. As a result, taking into account the non-ideality of physical components, we came to the conclusion that our circuit developed previously in the ngSPICE simulator can be easily constructed in the hardware.

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Published
2024-09-19
DOI
https://doi.org/10.1109/dcna63495.2024.10718580
Primary Topic
Neural Networks and Applications
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article
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article

Hardware electronic circuit modeling neuron with diode based non-linearity

В. И. Пономаренко, Ilya V. Sysoev, Lev V. Takaishvili
Neural Networks and Applications
article

Hardware electronic circuit modeling neuron with diode based non-linearity

В. И. Пономаренко, Ilya V. Sysoev, Lev V. Takaishvili
article en

Abstract

The purpose of this study is hardware implementation of the nonlinear electronic generator of neuron-like activity developed previously using nGSPICE software. Based on the previously developed circuits, we simplified the design by reducing the number of components and rearranging nonlinear elements. Various approximations of the nonlinear function were considered by means of different number n of diodes in the circuit, and the dependence of the output signal on n was investigated. Quasi-linear and nonlinear generation regimes were studied. Also, a simple partial bifurcation analysis was performed in order to study the mechanisms of oscillation birth in the circuit. As a result, taking into account the non-ideality of physical components, we came to the conclusion that our circuit developed previously in the ngSPICE simulator can be easily constructed in the hardware.

Saratov State University (RU), Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences (RU)
Affordable and clean energy
Openalex Percentile: Top 84%
Neural Networks and Applications
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Hardware electronic circuit modeling neuron with diode based non-linearity — В. И. Пономаренко, Ilya V. Sysoev, et al. · (2024) | TGRS Research Map | TGRS