ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


For citation:

Zelenova V. K. Relay model of a fading neuron. Izvestiya VUZ. Applied Nonlinear Dynamics, 2024, vol. 32, iss. 2, pp. 268-284. DOI: 10.18500/0869-6632-003096, EDN: QZDYAI

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
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Language: 
Russian
Article type: 
Article
UDC: 
530.182
EDN: 

Relay model of a fading neuron

Autors: 
Zelenova Vera Konstantinovna, P. G. Demidov Yaroslavl State University
Abstract: 

This study is a continuation of M. M. Preobrazhenskaya’s work “Relay System of Differential Equations with Delay as a Perceptron Model”, which aimed to combine approaches related to artificial neural networks and modeling biological neurons using differential equations with delay. The model of a single neuron was proposed, which allows for the existence of special modes called “aging” and “dying” behavior of the neuron. The study found a certain range of parameters where the “dying” mode of the neuron exists and numerically demonstrated the existence of the “aging” mode.

Purpose. We will unify the concepts of “aging” and “dying” neurons into the term “freezing” neuron. For this neuron, we will analytically construct a solution and find the range of parameters for its existence and stability, which will extend the results of the reference article.

Methods. To study this model, an auxiliary equation obtained by exponential substitution in the original equation is considered. Then, the method of step integration of a differential equation with delay and the introduction of additional functions are used.

Results. A solution of the “freezing” neuron type for the original model is constructed, and the range of parameters for the existence and stability of this solution is described.

Conclusion. The study obtained an extension of results for solutions of a special type in the model proposed by M. M. Preobrazhenskaya.

Acknowledgments: 
This work was carried out within the framework of a development programme for the Regional Scientific and Educational Mathematical Center of the Yaroslavl State University with financial support from the Ministry of Science and Higher Education of the Russian Federation (Аgreement on provision of subsidy from the federal budget No. 075-02-2023-948)
Reference: 
  1. Preobrazhenskaia MM. Relay system of differential equations with delay as a perceptron model. In: Kryzhanovsky B, Dunin-Barkowski W, Redko V, Tiumentsev Y. (eds.): Proceedings of the XXIV International Conference on Neuroinformatics «Advances in Neural Computation, Machine Learning, and Cognitive Research VI». 17-21 October 2022, Moscow, Russia. Cham: Springer Cham; 2022. P. 530–539.
  2. Kashchenko SA. Models of Wave Memory. Cham: Springer International Publishing; 2015. 267 p. (Lecture Notes in Morphogenesis).
  3. Hutchinson GE. Circular causal systems in ecology. Annals of the New York Academy of Sciences. Teleological Mechanisms. 1948;50(4):221–246. DOI: 10.1111/j.1749-6632.1948.tb39854.x.
  4. Kolesov АY, Mishchenko ЕF, Rozov NK. A modification of Hutchinson’s equation. Computational Mathematics and Mathematical Physics. 2010;50(12):2099–2112.
  5. El’sgol’ts LE., Norkin SB. Introduction to the Theory and Application of Differential Equations with Deviating Arguments. New York: Academic Press; 1973. 356 p.
Received: 
31.08.2023
Accepted: 
17.01.2024
Available online: 
19.02.2024
Published: 
29.03.2024