Turing instability and pattern formation of neural networks with reaction–diffusion terms

被引：1
|
作者：
Hongyong Zhao
Xuanxuan Huang
Xuebing Zhang
机构：
[1] Nanjing University of Aeronautics and Astronautics,Department of Mathematics, School of Sciences
来源：
Nonlinear Dynamics | 2014年 / 76卷
关键词：
Stability; Reaction–diffusion; Turing instability; Amplitude equations; Neural networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a model for a network of neurons with reaction–diffusion is investigated. By analyzing the linear stability of the system, Hopf bifurcation and Turing unstable conditions are obtained. Based on this, standard multiple-scale analysis is used for deriving the amplitude equations of the model for the excited modes in the Turing bifurcation. Moreover, the stability of different patterns is also determined. The obtained results enrich the dynamics of neurons’ network system.
引用
收藏
页码：115 / 124
页数：9
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