Equivariant Normal Forms for Parameterized Delay Differential Equations with Applications to Bifurcation Theory

被引:0
|
作者
Shang Jiang GUO [1 ]
Yu Ming CHEN [2 ]
Jian Hong WU [3 ]
机构
[1] College of Mathematics and Econometrics, Hu'nan University
[2] Department of Mathematics, Wilfrid Laurier University
[3] Department of Mathematics and Statistics, York
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中图分类号
O175 [微分方程、积分方程];
学科分类号
070104 ;
摘要
In this paper, we develop an efficient approach to compute the equivariant normal form of delay differential equations with parameters in the presence of symmetry. We present and justify a process that involves center manifold reduction and normalization preserving the symmetry, and that yields normal forms explicitly in terms of the coefficients of the original system. We observe that the form of the reduced vector field relies only on the information of the linearized system at the critical point and on the inherent symmetry, and the normal forms give critical information about not only the existence but also the stability and direction of bifurcated spatiotemporal patterns. We illustrate our general results by some applications to fold bifurcation, equivariant Hopf bifurcation and Hopf-Hopf interaction, with a detailed case study of additive neurons with delayed feedback.
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页码:825 / 856
页数:32
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