Approximate expressions of the bifurcating periodic solutions in a neuron model with delay-dependent parameters by perturbation approach |
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Authors: | Min Xiao Jinde Cao |
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Institution: | 1Department of Mathematics, Southeast University, 210096 Nanjing, People’s Republic of China ;2School of Mathematics and Information Technology, Nanjing Xiaozhuang University, 210017 Nanjing, People’s Republic of China |
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Abstract: | 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, 2006) 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. |
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Keywords: | Neuron model Delay-dependent parameters Approximation Periodic solution Perturbation approach |
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