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- Title
Turing instability and pattern formation of neural networks with reaction-diffusion terms.
- Authors
Zhao, Hongyong; Huang, Xuanxuan; Zhang, Xuebing
- Abstract
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.
- Subjects
ARTIFICIAL neural networks; REACTION-diffusion equations; HOPF bifurcations; COMBINATORIAL optimization; SIGNAL processing; PATTERN perception
- Publication
Nonlinear Dynamics, 2014, Vol 76, Issue 1, p115
- ISSN
0924-090X
- Publication type
Article
- DOI
10.1007/s11071-013-1114-2