Evaluating the accuracy of the dynamic mode decomposition

DOI10.3934/jcd.2020002zbMath1448.37103arXiv1710.00745OpenAlexW2986214183MaRDI QIDQ2192452

Hao Zhang, Scott T. M. Dawson, Clarence W. Rowley, Eric A. Deem, Louis N. Cattafesta

Publication date: 17 August 2020

Published in: Journal of Computational Dynamics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.00745

zbMATH Keywords

model selectionreduced order modelingdata-driven methodsdynamic mode decompositionKoopman operator

Mathematics Subject Classification ID

Time series analysis of dynamical systems (37M10) Linear composition operators (47B33) Numerical problems in dynamical systems (65P99)

Related Items (2)

Sparsity-promoting algorithms for the discovery of informative Koopman-invariant subspaces ⋮ Data-driven operator theoretic methods for phase space learning and analysis

Uses Software

• odmd
• PRMLT

Cites Work

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• Radial kernels and their reproducing kernel Hilbert spaces
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• Optimal mode decomposition for unsteady flows
• Model Reduction for Flow Analysis and Control
• Dynamic mode decomposition of numerical and experimental data
• Data Driven Modal Decompositions: Analysis and Enhancements
• Spectral analysis of nonlinear flows
• Variable Projection Methods for an Optimized Dynamic Mode Decomposition
• Online Dynamic Mode Decomposition for Time-Varying Systems
• Recursive dynamic mode decomposition of transient and post-transient wake flows

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