Time-Delay Observables for Koopman: Theory and Applications
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Publication:5109371
DOI10.1137/18M1216572zbMath1441.37090arXiv1810.01479OpenAlexW3019988632MaRDI QIDQ5109371
Steven L. Brunton, Eurika Kaiser, Mason Kamb, J. Nathan Kutz
Publication date: 11 May 2020
Published in: SIAM Journal on Applied Dynamical Systems (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1810.01479
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Cites Work
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- Discovering governing equations from data by sparse identification of nonlinear dynamical systems
- Relationship between singular spectrum analysis and Fourier analysis: theory and application to the monitoring of volcanic activity
- A data-driven approximation of the koopman operator: extending dynamic mode decomposition
- Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series
- Extracting qualitative dynamics from experimental data
- An analytic approach to practical state space reconstruction
- Chaos, fractals, and noise: Stochastic aspects of dynamics.
- Applied Koopman theory for partial differential equations and data-driven modeling of spatio-temporal systems
- On convergence of extended dynamic mode decomposition to the Koopman operator
- Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
- Linearization in the large of nonlinear systems and Koopman operator spectrum
- Koopman operator-based model reduction for switched-system control of PDEs
- Delay-coordinate maps and the spectra of Koopman operators
- Data-driven spectral decomposition and forecasting of ergodic dynamical systems
- Spectral properties of dynamical systems, model reduction and decompositions
- On dynamic mode decomposition: theory and applications
- Applied Koopmanism
- The Optimal Hard Threshold for Singular Values is <inline-formula> <tex-math notation="TeX">\(4/\sqrt {3}\) </tex-math></inline-formula>
- Dynamic mode decomposition of numerical and experimental data
- Spectral analysis of nonlinear flows
- An eigensystem realization algorithm for modal parameter identification and model reduction
- Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator
- Variable Projection Methods for an Optimized Dynamic Mode Decomposition
- Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
- Dynamical Systems of Continuous Spectra
- Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability
- Higher Order Dynamic Mode Decomposition
- Continuous analogues of matrix factorizations
- Linearly Recurrent Autoencoder Networks for Learning Dynamics
- A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems