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Stability and Hopf bifurcation of a delayed reaction-diffusion neural network

机译:时滞反应扩散神经网络的稳定性和Hopf分支

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摘要

In this paper, a delayed reaction-diffusion neural network with Neumann boundary conditions is investigated. By analyzing the corresponding characteristic equations, the local stability of the trivial uniform steady state is discussed. The existence of Hopf bifurcation at the trivial steady state is established. Using the normal form theory and the center manifold reduction of partial function differential equations, explicit formulae are derived to determine the direction and stability of bifurcating periodic solutions. Numerical simulations are carried out to illustrate the main results.
机译:本文研究了具有Neumann边界条件的时滞反应扩散神经网络。通过分析相应的特征方程,讨论了琐碎均匀稳态的局部稳定性。确定了琐碎稳态下霍夫夫分叉的存在。利用范式理论和偏函数微分方程的中心流形归约,导出了明确的公式来确定分叉周期解的方向和稳定性。进行数值模拟以说明主要结果。

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