Data-driven inference of high-accuracy isostable-based dynamical models in response to external inputs
From MaRDI portal
Publication:5000884
DOI10.1063/5.0042874zbMath1475.37096arXiv2102.04526OpenAlexW3173159451MaRDI QIDQ5000884
Publication date: 15 July 2021
Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2102.04526
coupled neuronsKoopman operatorone-dimensional Burgers' equationisostable response functionsisostable-to-output relationships
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Cites Work
- Unnamed Item
- A data-driven approximation of the koopman operator: extending dynamic mode decomposition
- Greater accuracy and broadened applicability of phase reduction using isostable coordinates
- Applied Koopman theory for partial differential equations and data-driven modeling of spatio-temporal systems
- Phase reduction and phase-based optimal control for biological systems: a tutorial
- Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
- Phase-amplitude dynamics in terms of extended response functions: invariant curves and Arnold tongues
- Koopman operator-based model reduction for switched-system control of PDEs
- Isostables, isochrons, and Koopman spectrum for the action-angle representation of stable fixed point dynamics
- Dynamic Mode Decomposition with Control
- Extending Phase Reduction to Excitable Media: Theory and Applications
- A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
- Applied Koopmanism
- Model Reduction for Flow Analysis and Control
- Global Stability Analysis Using the Eigenfunctions of the Koopman Operator
- Spectral analysis of nonlinear flows
- Turbulence, Coherent Structures, Dynamical Systems and Symmetry
- Generalizing Koopman Theory to Allow for Inputs and Control
- Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator
- Phase-amplitude reduction of transient dynamics far from attractors for limit-cycling systems
- Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
- Global computation of phase-amplitude reduction for limit-cycle dynamics
- Analysis of Fluid Flows via Spectral Properties of the Koopman Operator
- A data-driven phase and isostable reduced modeling framework for oscillatory dynamical systems
- Augmented Phase Reduction of (Not So) Weakly Perturbed Coupled Oscillators
- Koopman-mode decomposition of the cylinder wake
