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Related papers: A Data-Driven Approximation of the Koopman Operato…

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The Koopman operator is a linear operator that describes the evolution of scalar observables (i.e., measurement functions of the states) in an infinitedimensional Hilbert space. This operator theoretic point of view lifts the dynamics of a…

Optimization and Control · Mathematics 2021-10-19 Gregory Snyder , Zhuoyuan Song

In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace. The Koopman operator is an infinite-dimensional linear operator that evolves…

Dynamical Systems · Mathematics 2016-04-27 Steven L. Brunton , Bingni W. Brunton , Joshua L. Proctor , J. Nathan Kutz

Koopman analysis provides a general framework from which to analyze a nonlinear dynamical system in terms of a linear operator acting on an infinite-dimensional observable space. This theoretical framework provides a rigorous underpinning…

Dynamical Systems · Mathematics 2022-10-11 Dan Wilson

The Koopman operator is beneficial for analyzing nonlinear and stochastic dynamics; it is linear but infinite-dimensional, and it governs the evolution of observables. The extended dynamic mode decomposition (EDMD) is one of the famous…

Numerical Analysis · Mathematics 2022-05-18 Jun Ohkubo

This paper develops data-driven methods to identify eigenfunctions of the Koopman operator associated to a dynamical system and subspaces that are invariant under the operator. We build on Extended Dynamic Mode Decomposition (EDMD), a…

Systems and Control · Electrical Eng. & Systems 2021-02-26 Masih Haseli , Jorge Cortés

We establish the convergence of a class of numerical algorithms, known as Dynamic Mode Decomposition (DMD), for computation of the eigenvalues and eigenfunctions of the infinite-dimensional Koopman operator. The algorithms act on data…

Dynamical Systems · Mathematics 2017-11-21 Hassan Arbabi , Igor Mezić

Koopman operators and transfer operators represent nonlinear dynamics in state space through its induced action on linear spaces of observables and measures, respectively. This framework enables the use of linear operator theory for…

Dynamical Systems · Mathematics 2025-06-06 Claire Valva , Dimitrios Giannakis

The Koopman operator allows for handling nonlinear systems through a (globally) linear representation. In general, the operator is infinite-dimensional - necessitating finite approximations - for which there is no overarching framework.…

Systems and Control · Electrical Eng. & Systems 2021-12-23 Petar Bevanda , Stefan Sosnowski , Sandra Hirche

Dynamic mode decomposition (DMD) gives a practical means of extracting dynamic information from data, in the form of spatial modes and their associated frequencies and growth/decay rates. DMD can be considered as a numerical approximation…

Dynamical Systems · Mathematics 2017-10-03 Hao Zhang , Scott T. M. Dawson , Clarence W. Rowley , Eric A. Deem , Louis N. Cattafesta

Koopman operator theory shows how nonlinear dynamical systems can be represented as an infinite-dimensional, linear operator acting on a Hilbert space of observables of the system. However, determining the relevant modes and eigenvalues of…

Machine Learning · Computer Science 2022-04-06 Daniel J. Alford-Lago , Christopher W. Curtis , Alexander T. Ihler , Opal Issan

The Koopman operator and its data-driven approximations, such as extended dynamic mode decomposition (EDMD), are widely used for analysing, modelling, and controlling nonlinear dynamical systems. However, when the true Koopman…

Dynamical Systems · Mathematics 2026-02-05 Roland Schurig , Pieter van Goor , Karl Worthmann , Rolf Findeisen

This paper tackles the data-driven approximation of unknown dynamical systems using Koopman-operator methods. Given a dictionary of functions, these methods approximate the projection of the action of the operator on the finite-dimensional…

Systems and Control · Electrical Eng. & Systems 2023-02-28 Masih Haseli , Jorge Cortés

The Koopman operator is a mathematical tool that allows for a linear description of non-linear systems, but working in infinite dimensional spaces. Dynamic Mode Decomposition and Extended Dynamic Mode Decomposition are amongst the most…

Machine Learning · Computer Science 2021-03-26 Francesco Zanini , Alessandro Chiuso

Spectral decomposition of the Koopman operator is attracting attention as a tool for the analysis of nonlinear dynamical systems. Dynamic mode decomposition is a popular numerical algorithm for Koopman spectral analysis; however, we often…

Machine Learning · Computer Science 2018-01-31 Naoya Takeishi , Yoshinobu Kawahara , Takehisa Yairi

Dynamic Mode Decomposition (DMD) is a technique to approximate generally non-linear dynamical systems using linear techniques, which are better understood and easier to analyze. Koopman theory extends DMD by transforming the original system…

Optimization and Control · Mathematics 2022-11-15 Sourya Dey

We present a flexible data-driven method for dynamical system analysis that does not require explicit model discovery. The method is rooted in well-established techniques for approximating the Koopman operator from data and is implemented…

Dynamical Systems · Mathematics 2023-11-01 Jason J. Bramburger , Giovanni Fantuzzi

The Koopman representation is an infinite dimensional linear representation of linear or nonlinear dynamical systems. It represents the dynamics of output maps (aka observables), which are functions on the state space whose evaluation is…

Systems and Control · Electrical Eng. & Systems 2022-05-18 Bassam Bamieh

Koopman operator is a composition operator defined for a dynamical system described by nonlinear differential or difference equation. Although the original system is nonlinear and evolves on a finite-dimensional state space, the Koopman…

Systems and Control · Computer Science 2018-05-08 Yoshihiko Susuki , Igor Mezic , Fredrik Raak , Takashi Hikihara

When complex systems with nonlinear dynamics achieve an output performance objective, only a fraction of the state dynamics significantly impacts that output. Those minimal state dynamics can be identified using the differential geometric…

Optimization and Control · Mathematics 2022-10-19 Shara Balakrishnan , Aqib Hasnain , Robert Egbert , Enoch Yeung

Koopman operators are infinite-dimensional operators that linearize nonlinear dynamical systems, facilitating the study of their spectral properties and enabling the prediction of the time evolution of observable quantities. Recent methods…

Dynamical Systems · Mathematics 2025-06-06 Nicolas Boullé , Matthew J. Colbrook
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