Combinatorial models of global dynamics: learning cycling motion from data
Dynamical Systems
2023-12-22 v4 Chaotic Dynamics
Abstract
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.
Cite
@article{arxiv.2001.07066,
title = {Combinatorial models of global dynamics: learning cycling motion from data},
author = {Ulrich Bauer and David Hien and Oliver Junge and Konstantin Mischaikow and Max Snijders},
journal= {arXiv preprint arXiv:2001.07066},
year = {2023}
}
Comments
Replacement of the accidentally submitted v2