English

Wavelet-Based Observables for Koopman Analysis: An Extended Dynamic Mode Decomposition Framework

Numerical Analysis 2026-05-15 v1 Artificial Intelligence Numerical Analysis Dynamical Systems Functional Analysis

Abstract

We present an in-depth analysis of the Koopman semigroup via wavelet transform. Towards this goal, we start by introducing the wavelet-based observables and show that they are eigenfunctions of the Koopman semigroup when this semigroup is considered over the Banach space of continuous functions on a compact forward-invariant set endowed with the supremum norm. We then construct closed-form expressions of the action of the Koopman semigroup and its resolvent in terms of these observables. To approximate the action of Koopman semigroup numerically, we combine Extended Dynamic Mode Decomposition (EDMD) with the proposed wavelet-based observables leading to the Wavelet Dynamic Mode Decomposition via Continuous Wavelet Transform (cWDMD) algorithm. We validate our theoretical results on two numerical examples.

Keywords

Cite

@article{arxiv.2605.14224,
  title  = {Wavelet-Based Observables for Koopman Analysis: An Extended Dynamic Mode Decomposition Framework},
  author = {Cankat Tilki and Serkan Gugercin},
  journal= {arXiv preprint arXiv:2605.14224},
  year   = {2026}
}