中央歧管
数学
分叉
人工神经网络
余维数
离散时间和连续时间
理论(学习稳定性)
Hopfield网络
拓扑(电路)
数学分析
控制理论(社会学)
应用数学
纯数学
计算机科学
霍普夫分叉
物理
组合数学
非线性系统
统计
人工智能
控制(管理)
量子力学
机器学习
作者
Éva Kaslik,Štefan Bálint
标识
DOI:10.1016/j.chaos.2007.01.126
摘要
In this paper, a bifurcation analysis is undertaken for a discrete-time Hopfield neural network of two neurons with two different delays and self-connections. Conditions ensuring the asymptotic stability of the null solution are found, with respect to two characteristic parameters of the system. It is shown that for certain values of these parameters, Fold or Neimark-Sacker bifurcations occur, but Flip and codimension 2 (Fold–Neimark-Sacker, double Neimark-Sacker, resonance 1:1 and Flip–Neimark-Sacker) bifurcations may also be present. The direction and the stability of the Neimark-Sacker bifurcations are investigated by applying the center manifold theorem and the normal form theory.
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