论文标题
模拟具有单个延迟微分方程的复杂网络
Emulating complex networks with a single delay differential equation
论文作者
论文摘要
带有时间拖延反馈的单个动态系统可以效仿网络。延迟系统的这种属性使它们成为机器学习应用程序的极其有用的工具。在这里，我们描述了几种可能的设置，这些设置允许模拟多层（深）馈电网络以及通过具有延迟反馈的单个系统的任意邻接矩阵的耦合离散地图的循环网络。虽然网络的大小可以是任意的，但生成延迟系统的变量数量很少，包括标量案例。
A single dynamical system with time-delayed feedback can emulate networks. This property of delay systems made them extremely useful tools for Machine Learning applications. Here we describe several possible setups, which allow emulating multilayer (deep) feed-forward networks as well as recurrent networks of coupled discrete maps with arbitrary adjacency matrix by a single system with delayed feedback. While the network's size can be arbitrary, the generating delay system can have a low number of variables, including a scalar case.
