Abstract

This paper considers a mathematical model of a ring neural network with an even number of synaptically interacting elements. The model is a system of scalar nonlinear differential-difference equations, the right-hand sides of which depend on a large parameter. The unknown functions being contained in the system characterize membrane potentials of neurons. It is of interest to search within the system for special periodic solutions, so-called impulse-refractory modes. Functions with odd numbers of the impulse-refraction cycle have an asymptotically large burst and the functions with even numbers are asymptotically small. For this purpose, two substitutions are made sequentially, making it possible to study of a two-dimensional system of nonlinear differential-difference singularly perturbed equations with two delays instead of the initial system. Further, as the large parameter tends to infinity, the limiting object is defined, which is a relay system of equations with two delays. Using the step-by-step method, we prove that the solution of a relay system with an initial function from a suitable class is a periodic function with required properties. Then, using the Poincare operator and the Schauder principle, the existence of a relaxation periodic solution of a two-dimensional singularly perturbed system is proven. To do this, we construct asymptotics of this solution, and then prove its closeness to the solution of the relay system. The exponential estimate of the Frechet derivative of the Poincare operator implies uniqueness of the solution of a two-dimensional differential-difference system of equations with two delays in the constructed class of functions and is used to justify the exponential orbital stability of this solution. Furthermore, with the help of reverse replacement, the proven result is transferred to the original system.

Highlights

  • The model is a system of scalar nonlinear differentialdifference equations

  • the right parts of which depend on large parameters

  • The unknown functions included in the system characterize the membrane potentials of the neurons

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Summary

Постановка задачи

В которой uj(t) > 0 нормированные мембранные потенциалы нейронов, m ∈ N фиксированное число, h ∈ (0, 1) параметр, определяющий запаздывание в цепи связи, b = const > 0, u∗ = exp(c λ) пороговое значение, управляющее взаимодействием, c = const ∈ R, слагаемые bg uj−1 ln(u∗/uj)uj моделируют синаптическую связь. В работах [1,2,3,4,5] для систем, подобных (1) (с произвольным числом осцилляторов и без запаздывания h в цепи связи), показано существование дискретных бегущих волн. 1. Отметим, что в силу свойств (2) справедливы предельные равенlim f exp(x/ε) = R(x) d=ef 1 при x < 0,. В силу сделанной экспоненциальной замены (5) постановка задачи для системы (6) состоит в отыскании периодического релаксационного режима, такого, что x1(t) меняет знак, а x2(t) остается отрицательной (отделенной от нуля) при всех t > 0

План исследования
Исследование предельного релейного уравнения
Формулировка основного результата
Доказательство теоремы 2
Заключение
Full Text
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