Spatiotemporal Dynamics in Reaction–Diffusion Neural Networks Near a Turing–Hopf Bifurcation Point

Author:

Lin Jiazhe1,Xu Rui2ORCID,Tian Xiaohong2

Affiliation:

1. Institute of Applied Mathematics, Army Engineering University, Shijiazhuang 050003, Hebei, P. R. China

2. Complex Systems Research Center, Shanxi University, Taiyuan 030006, Shanxi, P. R. China

Abstract

Since the electromagnetic field of neural networks is heterogeneous, the diffusion phenomenon of electrons exists inevitably. In this paper, we investigate the existence of Turing–Hopf bifurcation in a reaction–diffusion neural network. By the normal form theory for partial differential equations, we calculate the normal form on the center manifold associated with codimension-two Turing–Hopf bifurcation, which helps us understand and classify the spatiotemporal dynamics close to the Turing–Hopf bifurcation point. Numerical simulations show that the spatiotemporal dynamics in the neighborhood of the bifurcation point can be divided into six cases and spatially inhomogeneous periodic solution appears in one of them.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanxi Province

Shanxi Scientific Data Sharing Platform for Animal Diseases

Science and Technology Innovation Team of Shanxi Province

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modeling and Simulation,Engineering (miscellaneous)

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