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Extracting the latent underlying structures of complex nonlinear local and nonlocal flows is essential for their analysis and modeling. In this work, we attempt to provide a consistent framework through Koopman theory and its related…

Dynamical Systems · Mathematics 2021-12-23 Ido Cohen , Guy Gilboa

A Koopman decomposition is a powerful method of analysis for fluid flows leading to an apparently linear description of nonlinear dynamics in which the flow is expressed as a superposition of fixed spatial structures with exponential time…

Fluid Dynamics · Physics 2019-09-25 Jacob Page , Rich R. Kerswell

Local Koopman spectral problem is studied to resolve all dynamics for a nonlinear system. The proposed spectral problem is compatible with the linear spectral theory for various linear systems, and several properties of local Koopman…

Fluid Dynamics · Physics 2020-07-02 Wei Zhang , Mingjun Wei

A Koopman decomposition of a complex system leads to a representation in which nonlinear dynamics appear to be linear. The existence of a linear framework with which to analyse nonlinear dynamical systems brings new strategies for…

Fluid Dynamics · Physics 2019-03-12 Jeremy Parker , Jacob Page

We develop a new generalization of Koopman operator theory that incorporates the effects of inputs and control. Koopman spectral analysis is a theoretical tool for the analysis of nonlinear dynamical systems. Moreover, Koopman is intimately…

Optimization and Control · Mathematics 2016-02-25 Joshua L. Proctor , Steven L. Brunton , J. Nathan Kutz

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

The field of dynamical systems is being transformed by the mathematical tools and algorithms emerging from modern computing and data science. First-principles derivations and asymptotic reductions are giving way to data-driven approaches…

Dynamical Systems · Mathematics 2021-11-02 Steven L. Brunton , Marko Budišić , Eurika Kaiser , J. Nathan Kutz

The emergence of Dynamic Mode Decomposition (DMD) as a practical way to attempt a Koopman mode decomposition of a nonlinear PDE presents exciting prospects for identifying invariant sets and slowly decaying transient structures buried in…

Fluid Dynamics · Physics 2018-08-01 Jacob Page , Rich R. Kerswell

Spectral decomposition of dynamical systems is a popular methodology to investigate the fundamental qualitative and quantitative properties of these systems and their solutions. In this chapter, we consider a class of nonlinear cooperative…

Systems and Control · Computer Science 2019-04-23 Hossein K. Mousavi , Christoforos Somarakis , Qiyu Sun , Nader Motee

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

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

A majority of methods from dynamical systems analysis, especially those in applied settings, rely on Poincar\'e's geometric picture that focuses on "dynamics of states". While this picture has fueled our field for a century, it has shown…

Dynamical Systems · Mathematics 2013-01-01 Marko Budišić , Ryan M. Mohr , Igor Mezić

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

System representations inspired by the infinite-dimensional Koopman operator (generator) are increasingly considered for predictive modeling. Due to the operator's linearity, a range of nonlinear systems admit linear predictor…

Machine Learning · Computer Science 2022-05-31 Petar Bevanda , Max Beier , Sebastian Kerz , Armin Lederer , Stefan Sosnowski , Sandra Hirche

The Koopman Mode Decomposition (KMD) is a data-analysis technique which is often used to extract the spatio-temporal patterns of complex flows. In this paper, we use KMD to study the dynamics of the lid-driven flow in a two-dimensional…

Fluid Dynamics · Physics 2018-01-03 Hassan Arbabi , Igor Mezić

The Koopman operator has emerged as a powerful tool for the analysis of nonlinear dynamical systems as it provides coordinate transformations to globally linearize the dynamics. While recent deep learning approaches have been useful in…

Dynamical Systems · Mathematics 2020-06-23 Shaowu Pan , Karthik Duraisamy

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 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

Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of nonlinear systems. However, existing DMD theory deals primarily with sequential time…

Numerical Analysis · Mathematics 2014-12-17 Jonathan H. Tu , Clarence W. Rowley , Dirk M. Luchtenburg , Steven L. Brunton , J. Nathan Kutz

Any deterministic autonomous dynamical system may be globally linearized by its' Koopman operator. This object is typically infinite-dimensional and can be approximated by the so-called Dynamic Mode Decomposition (DMD). In DMD, the central…

Dynamical Systems · Mathematics 2023-12-14 Gowtham S Seenivasaharagavan , Milan Korda , Hassan Arbabi , Igor Mezić
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