RUS  ENG JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB
 General information Latest issue Archive Impact factor Search papers Search references RSS Latest issue Current issues Archive issues What is RSS

 Model. Anal. Inform. Sist.: Year: Volume: Issue: Page: Find

 Model. Anal. Inform. Sist., 2014, Volume 21, Number 5, Pages 38–48 (Mi mais397)

Application of the method of quasi-normal forms to the mathematical model of a single neuron

M. M. Preobrazhenskaya

P. G. Demidov Yaroslavl State University

Abstract: We consider a scalar nonlinear differential-difference equation with two delays, which models the behavior of a single neuron. Under some additional suppositions for this equation it is applied a well-known method of quasi-normal forms. Its essence lies in the formal normalization of the Poincare–Dulac, the production of a quasi-normal form and the subsequent application of the conformity theorems. In this case, the result of the application of quasi-normal forms is a countable system of differential-difference equations, which manages to turn into a boundary value problem of the Korteweg–de Vries equation. The investigation of this boundary value problem allows to make the conclusion about the behavior of the original equation. Namely, for a suitable choice of parameters in the framework of this equation it is implemented the buffer phenomenon consisting in the presence of the bifurcation mechanism for the birth of an arbitrarily large number of stable cycles.

Keywords: buffering, differential-difference equation, asymptotic form, stability, Korteweg–de Vries equation, quasi-normal forms.

Full text: PDF file (441 kB)
References: PDF file   HTML file
UDC: 517.9

Citation: M. M. Preobrazhenskaya, “Application of the method of quasi-normal forms to the mathematical model of a single neuron”, Model. Anal. Inform. Sist., 21:5 (2014), 38–48

Citation in format AMSBIB
\Bibitem{Pre14} \by M.~M.~Preobrazhenskaya \paper Application of the method of quasi-normal forms to the mathematical model of a single neuron \jour Model. Anal. Inform. Sist. \yr 2014 \vol 21 \issue 5 \pages 38--48 \mathnet{http://mi.mathnet.ru/mais397}