Pages that link to "Item:Q897161"
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The following pages link to A data-driven approximation of the koopman operator: extending dynamic mode decomposition (Q897161):
Displaying 50 items.
- Koopman operator-based driver-vehicle dynamic model for shared control systems (Q2692004) (← links)
- Spectral proper orthogonal decomposition (Q2814951) (← links)
- Spectral Identification of Networks Using Sparse Measurements (Q2967812) (← links)
- Data Driven Modal Decompositions: Analysis and Enhancements (Q3174790) (← links)
- Tensor-based dynamic mode decomposition (Q3176543) (← links)
- Manifold learning for organizing unstructured sets of process observations (Q3303828) (← links)
- Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks (Q4557699) (← links)
- Extracting Sparse High-Dimensional Dynamics from Limited Data (Q4561658) (← links)
- Data-Driven Discovery of Closure Models (Q4562411) (← links)
- Koopman Operator Family Spectrum for Nonautonomous Systems (Q4562415) (← links)
- Sparse reduced-order modelling: sensor-based dynamics to full-state estimation (Q4563901) (← links)
- Crisis of the chaotic attractor of a climate model: a transfer operator approach (Q4569304) (← links)
- Generalizing Koopman Theory to Allow for Inputs and Control (Q4571161) (← links)
- Dynamically Orthogonal Numerical Schemes for Efficient Stochastic Advection and Lagrangian Transport (Q4580294) (← links)
- Koopman analysis of the long-term evolution in a turbulent convection cell (Q4582914) (← links)
- Insights into the dynamics of conical breakdown modes in coaxial swirling flow field (Q4585889) (← links)
- Data-driven reduced modelling of turbulent Rayleigh–Bénard convection using DMD-enhanced fluctuation–dissipation theorem (Q4585936) (← links)
- Identifying finite-time coherent sets from limited quantities of Lagrangian data (Q4591745) (← links)
- Dynamic reconstruction and data reconstruction for subsampled or irregularly sampled data (Q4594126) (← links)
- Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator (Q4601202) (← links)
- Optimized Sampling for Multiscale Dynamics (Q4627447) (← links)
- Phase-amplitude reduction of transient dynamics far from attractors for limit-cycling systems (Q4642546) (← links)
- Data-adaptive harmonic spectra and multilayer Stuart-Landau models (Q4644288) (← links)
- Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator (Q4644309) (← links)
- On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions (Q4686615) (← links)
- A Review on Reduced Order Modeling using DMD-Based Methods (Q4973303) (← links)
- Centering Data Improves the Dynamic Mode Decomposition (Q4983495) (← links)
- Data-Driven Model Predictive Control using Interpolated Koopman Generators (Q4983502) (← links)
- On explaining the surprising success of reservoir computing forecaster of chaos? The universal machine learning dynamical system with contrast to VAR and DMD (Q4983648) (← links)
- Sparsity-promoting algorithms for the discovery of informative Koopman-invariant subspaces (Q4987934) (← links)
- Data-driven resolvent analysis (Q4989070) (← links)
- Kernel-based parameter estimation of dynamical systems with unknown observation functions (Q4989104) (← links)
- Estimation of the Koopman Generator by Newton's Extrapolation (Q4992258) (← links)
- 9 From the POD-Galerkin method to sparse manifold models (Q4993250) (← links)
- On Koopman mode decomposition and tensor component analysis (Q4993697) (← links)
- Error Bounds for Dynamical Spectral Estimation (Q4999356) (← links)
- Data-driven inference of high-accuracy isostable-based dynamical models in response to external inputs (Q5000884) (← links)
- A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data Using Unstructured Spatial Discretizations (Q5005016) (← links)
- Deep learning models for global coordinate transformations that linearise PDEs (Q5014841) (← links)
- Data-Driven Learning for the Mori--Zwanzig Formalism: A Generalization of the Koopman Learning Framework (Q5023533) (← links)
- An Adaptive Phase-Amplitude Reduction Framework without $\mathcal{O}(\epsilon)$ Constraints on Inputs (Q5024518) (← links)
- Efficiency of randomised dynamic mode decomposition for reduced order modelling (Q5031486) (← links)
- Approximating Matrix Eigenvalues by Subspace Iteration with Repeated Random Sparsification (Q5038410) (← links)
- Numerical methods to evaluate Koopman matrix from system equations* (Q5048531) (← links)
- Koopman analysis of quantum systems* (Q5057844) (← links)
- Extracting stochastic dynamical systems with α-stable Lévy noise from data (Q5066035) (← links)
- Spectral Discovery of Jointly Smooth Features for Multimodal Data (Q5070856) (← links)
- Discriminant Dynamic Mode Decomposition for Labeled Spatiotemporal Data Collections (Q5072984) (← links)
- Modern Koopman Theory for Dynamical Systems (Q5075835) (← links)
- Reduced Operator Inference for Nonlinear Partial Differential Equations (Q5088794) (← links)
