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This article is cited in 43 scientific papers (total in 43 papers)
Self-excited relaxation oscillations in networks of impulse neurons
S. D. Glyzina, A. Yu. Kolesova, N. Kh. Rozovb a Yaroslavl State University
b Moscow State University
Abstract:
This paper addresses the problem of mathematical modelling of neuron activity. New classes of singularly perturbed differential-difference equations with Volterra-type delay are proposed and used to describe how single neurons and also neural networks function with various kinds of connections (electrical or chemical). Special asymptotic methods are developed which make it possible to analyse questions of the existence and stability of relaxation periodic motions in such systems.
Bibliography: 56 titles.
Keywords:
neuron models, differential-difference equations, asymptotic behaviour, relaxation oscillations, stability, buffering, bursting effect.
Received: 05.02.2015
Citation:
S. D. Glyzin, A. Yu. Kolesov, N. Kh. Rozov, “Self-excited relaxation oscillations in networks of impulse neurons”, Russian Math. Surveys, 70:3 (2015), 383–452
Linking options:
https://www.mathnet.ru/eng/rm9659https://doi.org/10.1070/RM2015v070n03ABEH004951 https://www.mathnet.ru/eng/rm/v70/i3/p3
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Abstract page: | 1047 | Russian version PDF: | 414 | English version PDF: | 43 | References: | 84 | First page: | 53 |
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