Dynamic mode decomposition and its variants
PJ Schmid - Annual Review of Fluid Mechanics, 2022 - annualreviews.org
Dynamic mode decomposition (DMD) is a factorization and dimensionality reduction
technique for data sequences. In its most common form, it processes high-dimensional …
technique for data sequences. In its most common form, it processes high-dimensional …
Data-driven model reduction and transfer operator approximation
In this review paper, we will present different data-driven dimension reduction techniques for
dynamical systems that are based on transfer operator theory as well as methods to …
dynamical systems that are based on transfer operator theory as well as methods to …
Rigorous data‐driven computation of spectral properties of Koopman operators for dynamical systems
Koopman operators are infinite‐dimensional operators that globally linearize nonlinear
dynamical systems, making their spectral information valuable for understanding dynamics …
dynamical systems, making their spectral information valuable for understanding dynamics …
On the numerical approximation of the Perron-Frobenius and Koopman operator
Nonparametric approximation of conditional expectation operators
Given the joint distribution of two random variables $ X, Y $ on some second countable
locally compact Hausdorff space, we investigate the statistical approximation of the $ L^ 2 …
locally compact Hausdorff space, we investigate the statistical approximation of the $ L^ 2 …