Pages that link to "Item:Q2513924"

The following pages link to On dynamic mode decomposition: theory and applications (Q2513924):

Displaying 50 items.

• Compressed sensing and dynamic mode decomposition (Q317178) (← links)
• A kernel-based method for data-driven Koopman spectral analysis (Q317185) (← links)
• On the numerical approximation of the Perron-Frobenius and Koopman operator (Q333775) (← links)
• Data-driven model reduction and transfer operator approximation (Q722011) (← links)
• Sparse + low-energy decomposition for viscous conservation laws (Q729181) (← links)
• Koopman spectra in reproducing kernel Hilbert spaces (Q778031) (← links)
• Detecting regime transitions in time series using dynamic mode decomposition (Q781788) (← links)
• Variational approach to closure of nonlinear dynamical systems: autonomous case (Q781793) (← links)
• Ruelle-Pollicott resonances of stochastic systems in reduced state space. Part III: Application to the Cane-Zebiak model of the El Niño-southern oscillation (Q781815) (← links)
• Study of the thermo-magneto-hydrodynamic flow of micropolar-nanofluid in square enclosure using dynamic mode decomposition and proper orthogonal decomposition (Q821097) (← links)
• A data-driven approximation of the koopman operator: extending dynamic mode decomposition (Q897161) (← links)
• Spatio-temporal Koopman decomposition (Q1631295) (← links)
• Optimal control formulation of pulse-based control using Koopman operator (Q1641069) (← links)
• An improved criterion to select dominant modes from dynamic mode decomposition (Q1672141) (← links)
• A coherent structure approach for parameter estimation in Lagrangian data assimilation (Q1691285) (← links)
• High-dimensional time series prediction using kernel-based koopman mode regression (Q1696900) (← links)
• Applied Koopman theory for partial differential equations and data-driven modeling of spatio-temporal systems (Q1723113) (← links)
• Projection-based model reduction: formulations for physics-based machine learning (Q1739759) (← links)
• On convergence of extended dynamic mode decomposition to the Koopman operator (Q1744123) (← links)
• On reduced input-output dynamic mode decomposition (Q1756919) (← links)
• Energy preserving model order reduction of the nonlinear Schrödinger equation (Q1756920) (← links)
• Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control (Q1796994) (← links)
• Randomized model order reduction (Q2000522) (← links)
• Reduced order optimal control of the convective FitzHugh-Nagumo equations (Q2004569) (← links)
• Memory-based reduced modelling and data-based estimation of opinion spreading (Q2022637) (← links)
• Koopman operator framework for time series modeling and analysis (Q2022703) (← links)
• Koopman operator spectrum for random dynamical systems (Q2022704) (← links)
• An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques (Q2024169) (← links)
• Koopman operator approach for computing structure of solutions and observability of nonlinear dynamical systems over finite fields (Q2036487) (← links)
• Reproducing kernel Hilbert space compactification of unitary evolution groups (Q2036491) (← links)
• Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories (Q2050562) (← links)
• Low-rank dynamic mode decomposition: an exact and tractable solution (Q2062877) (← links)
• Dynamics in a confined mass-spring chain with \(1/r\) repulsive potential: strongly nonlinear regime (Q2070214) (← links)
• Data-driven operator theoretic methods for phase space learning and analysis (Q2083237) (← links)
• Statistical modeling and an adaptive averaging technique for strong convergence of the dynamic mode decomposition (Q2088764) (← links)
• Strong consistency of the projected total least squares dynamic mode decomposition for datasets with random noise (Q2111579) (← links)
• Data-driven reduced-order modeling for nonautonomous dynamical systems in multiscale media (Q2112501) (← links)
• Data-driven approximation of the Koopman generator: model reduction, system identification, and control (Q2115518) (← links)
• Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism (Q2123923) (← links)
• Data-driven modeling of two-dimensional detonation wave fronts (Q2124122) (← links)
• On generalized residual network for deep learning of unknown dynamical systems (Q2124404) (← links)
• Spatial early warning signals for tipping points using dynamic mode decomposition (Q2128710) (← links)
• A data-driven, physics-informed framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings (Q2129328) (← links)
• Extended dynamic mode decomposition for inhomogeneous problems (Q2132641) (← links)
• Detection and prediction of equilibrium states in kinetic plasma simulations via mode tracking using reduced-order dynamic mode decomposition (Q2133488) (← links)
• Deep learning nonlinear multiscale dynamic problems using Koopman operator (Q2133546) (← links)
• A reduced order method for nonlinear parameterized partial differential equations using dynamic mode decomposition coupled with \(k\)-nearest-neighbors regression (Q2133585) (← links)
• A Koopman framework for rare event simulation in stochastic differential equations (Q2133784) (← links)
• Data-driven acceleration of thermal radiation transfer calculations with the dynamic mode decomposition and a sequential singular value decomposition (Q2134534) (← links)
• Correcting noisy dynamic mode decomposition with Kalman filters (Q2137999) (← links)