Keyword

dynamic mode decomposition

Description: A data-driven numerical method that extracts spatial modes and their temporal dynamics from time-evolving measurements or simulations.

Primary topic: Model Reduction and Neural Networks (38%)

Wikidata ID: wiki/Q5318993

OpenAlex ID: keywords/dynamic-mode-decomposition

Dynamic mode decomposition of numerical and experimental data

2010 · PETER J. SCHMID · Journal of Fluid Mechanics · 5,911

Spectral analysis of nonlinear flows

2009 · CLARENCE W. ROWLEY, IGOR MEZIĆ, et al. · Journal of Fluid Mechanics · 2,323

A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition

2015 · Matthew O. Williams, Ioannis G. Kevrekidis, et al. · Journal of Nonlinear Science · 1,944

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On dynamic mode decomposition: Theory and applications

2014 · Jonathan H. Tu, Clarence W. Rowley, et al. · Journal of Computational Dynamics · 1,528

Spectral proper orthogonal decomposition and its relationship to dynamic mode decomposition and resolvent analysis

2018 · Aaron Towne, Oliver T. Schmidt, et al. · Journal of Fluid Mechanics · 1,434

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Dynamic Mode Decomposition

2016 · J. Nathan Kutz, Steven L. Brunton, et al. · Society for Industrial and Applied Mathematics eBooks · 1,181

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Dynamic Mode Decomposition with Control

2016 · Joshua L. Proctor, Steven L. Brunton, et al. · SIAM Journal on Applied Dynamical Systems · 1,116

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Analysis of Fluid Flows via Spectral Properties of the Koopman Operator

2012 · Igor Mezić · Annual Review of Fluid Mechanics · 980

Sparsity-promoting dynamic mode decomposition

2014 · Mihailo R. Jovanović, Peter J. Schmid, et al. · Physics of Fluids · 899

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Model Reduction for Flow Analysis and Control

2016 · Clarence W. Rowley, Scott T.M. Dawson · Annual Review of Fluid Mechanics · 791

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Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses

2012 · Kevin K. Chen, Jonathan H. Tu, et al. · Journal of Nonlinear Science · 722

Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems

2016 · J. Nathan Kutz, Steven L. Brunton, et al. · 662

A Data–driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition

2016 · Matthew O. Williams, Ioannis G. Kevrekidis, et al. · 652

Dynamic Mode Decomposition and Its Variants

2021 · Peter J. Schmid · Annual Review of Fluid Mechanics · 642

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

2016 · Steven L. Brunton, Bingni W. Brunton, et al. · PLoS ONE · 629

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Applications of the dynamic mode decomposition

2010 · P. J. Schmid, L. Li, et al. · Theoretical and Computational Fluid Dynamics · 620

Modern Koopman Theory for Dynamical Systems

2022 · Steven L. Brunton, Marko Budišić, et al. · SIAM Review · 575

Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator

2017 · Hassan Arbabi, Igor Mezić · SIAM Journal on Applied Dynamical Systems · 476

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Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition

2015 · Bingni W. Brunton, Lise A. Johnson, et al. · Journal of Neuroscience Methods · 470

Multiresolution Dynamic Mode Decomposition

2016 · J. Nathan Kutz, Xing Fu, et al. · SIAM Journal on Applied Dynamical Systems · 442

Higher Order Dynamic Mode Decomposition

2017 · Soledad Le Clainche, José M. Vega · SIAM Journal on Applied Dynamical Systems · 417

Spectral proper orthogonal decomposition

2016 · Moritz Sieber, C. Oliver Paschereit, et al. · Journal of Fluid Mechanics · 399

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Application of the dynamic mode decomposition to experimental data

2011 · Peter J. Schmid · Experiments in Fluids · 358

Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems

2019 · Enoch Yeung, Soumya Kundu, et al. · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · 337

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Sparse Identification of Nonlinear Dynamics with Control (SINDYc)**SLB acknowledges support from the U.S. Air Force Center of Excellence on Nature Inspired Flight Technologies and Ideas (FA9550-14-1-0398). JLP thanks Bill and Melinda Gates for their active support of the Institute of Disease Modeling and their sponsorship through the Global Good Fund. JNK acknowledges support from the U.S. Air Force Office of Scientific Research (FA9550-09-0174).

2016 · Steven L. Brunton, Joshua L. Proctor, et al. · IFAC-PapersOnLine · 335

Works count: 4,902

Citation count: 71,930