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JOURNALS // Uspekhi Matematicheskikh Nauk // Archive

Uspekhi Mat. Nauk, 2015 Volume 70, Issue 3(423), Pages 3–76 (Mi rm9659)

This article is cited 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.

UDC: 517.926

MSC: 34C26, 34K26, 92C20

Received: 05.02.2015

DOI: 10.4213/rm9659


 English version:
Russian Mathematical Surveys, 2015, 70:3, 383–452

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© Steklov Math. Inst. of RAS, 2024