论文标题
全球动力学组合模型：从数据中学习循环运动
Combinatorial models of global dynamics: learning cycling motion from data
论文作者
论文摘要
我们描述了一种计算方法，用于构建某些动力学系统的粗制组合模型，其中宏观状态通过系统的基本循环运动给出。我们的方法特别适用于时间序列数据。我们通过扰动的双井哈密顿官和洛伦兹系统来说明构造。
We describe a computational method for constructing a coarse combinatorial model of some dynamical system in which the macroscopic states are given by elementary cycling motions of the system. Our method is in particular applicable to time series data. We illustrate the construction by a perturbed double well Hamiltonian as well as the Lorenz system.
