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Applied and Computational Harmonic Analysis
Article . 2020 . Peer-reviewed
License: Elsevier Non-Commercial
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2017
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Data-driven spectral analysis of the Koopman operator

Authors: Mihai Putinar; Mihai Putinar; Igor Mezic; Milan Korda;

Data-driven spectral analysis of the Koopman operator

Abstract

Starting from measured data, we develop a method to compute the fine structure of the spectrum of the Koopman operator with rigorous convergence guarantees. The method is based on the observation that, in the measure-preserving ergodic setting, the moments of the spectral measure associated to a given observable are computable from a single trajectory of this observable. Having finitely many moments available, we use the classical Christoffel-Darboux kernel to separate the atomic and absolutely continuous parts of the spectrum, supported by convergence guarantees as the number of moments tends to infinity. In addition, we propose a technique to detect the singular continuous part of the spectrum as well as two methods to approximate the spectral measure with guaranteed convergence in the weak topology, irrespective of whether the singular continuous part is present or not. The proposed method is simple to implement and readily applicable to large-scale systems since the computational complexity is dominated by inverting an $N\times N$ Hermitian positive-definite Toeplitz matrix, where $N$ is the number of moments, for which efficient and numerically stable algorithms exist; in particular, the complexity of the approach is independent of the dimension of the underlying state-space. We also show how to compute, from measured data, the spectral projection on a given segment of the unit circle, allowing us to obtain a finite-dimensional approximation of the operator that explicitly takes into account the point and continuous parts of the spectrum. Finally, we describe a relationship between the proposed method and the so-called Hankel Dynamic Mode Decomposition, providing new insights into the behavior of the eigenvalues of the Hankel DMD operator. A number of numerical examples illustrate the approach, including a study of the spectrum of the lid-driven two-dimensional cavity flow.

Countries
United States, United Kingdom
Keywords

math.NA, Numerical and Computational Mathematics, Data-driven methods, Applied Mathematics, math.SP, Numerical & Computational Mathematics, Spectral analysis, Dynamical Systems (math.DS), Numerical Analysis (math.NA), Toeplitz matrix, Pure Mathematics, Moment problem, Mathematics - Spectral Theory, Christoffel-Darboux kernel, FOS: Mathematics, Mathematics - Numerical Analysis, Mathematics - Dynamical Systems, Koopman operator, Spectral Theory (math.SP), math.DS

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    92
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    Top 1%
    influence
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    Top 10%
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    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
92
Top 1%
Top 10%
Top 1%
Green
bronze