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Approximate expressions of the bifurcating periodic solutions in a neuron model with delay-dependent parameters by perturbation approach

机译:具时滞参数的神经元模型中分岔周期解的近似表示

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摘要

This paper is interested in gaining insights of approximate expressions of the bifurcating periodic solutions in a neuron model. This model shares the property of involving delay-dependent parameters. The presence of such dependence requires the use of suitable criteria which usually makes the analytical work so harder. Most existing methods for studying the nonlinear dynamics fail when applied to such a class of delay models. Although Xu et al. (Phys Lett A 354:126–136, ) studied stability switches, Hopf bifurcation and chaos of the neuron model with delay-dependent parameters, the dynamics of this model are still largely undetermined. In this paper, a detailed analysis on approximation to the bifurcating periodic solutions is given by means of the perturbation approach. Moreover, some examples are provided for comparing approximations with numerical solutions of the bifurcating periodic solutions. It shows that the dynamics of the neuron model with delay-dependent parameters is quite different from that of systems with delay-independent parameters only.
机译:本文感兴趣的是获得神经元模型中分叉周期解的近似表达式的见解。该模型具有涉及延迟相关参数的特性。存在这种依赖性需要使用适当的标准,这通常会使分析工作变得更加困难。当应用于此类延迟模型时,大多数研究非线性动力学的现有方法都会失败。虽然徐等人。 (Phys Lett A 354:126–136,)研究了具有依赖于延迟的参数的神经元模型的稳定性开关,霍普夫分叉和混沌,该模型的动力学仍不确定。本文采用摄动法对分岔周期解的逼近进行了详细分析。此外,提供一些示例以将近似与分叉周期解的数值解进行比较。它表明具有时延相关参数的神经元模型的动力学与仅具有时延独立参数的系统的动力学有很大不同。

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