Results 1 to 10 of about 17,648 (273)

A Matlab Toolbox for Extended Dynamic Mode Decomposition Based on Orthogonal Polynomials and p-q Quasi-Norm Order Reduction [PDF]

Mathematics, 2022
Extended Dynamic Mode Decomposition (EDMD) allows an approximation of the Koopman operator to be derived in the form of a truncated (finite dimensional) linear operator in a lifted space of (nonlinear) observable functions.
Camilo Garcia-Tenorio, Alain Vande Wouwer   +1 more
doaj   +4 more sources

Extended-Kalman-filter-based dynamic mode decomposition for simultaneous system identification and denoising. [PDF]

PLoS ONE, 2019
A new dynamic mode decomposition (DMD) method is introduced for simultaneous system identification and denoising in conjunction with the adoption of an extended Kalman filter algorithm.
Taku Nonomura, Hisaichi Shibata, Ryoji Takaki   +2 more
doaj   +6 more sources

Evaluation of the Regions of Attraction of Higher-Dimensional Hyperbolic Systems Using Extended Dynamic Mode Decomposition

Automation, 2023
This paper provides the theoretical foundation for the approximation of the regions of attraction in hyperbolic and polynomial systems based on the eigenfunctions deduced from the data-driven approximation of the Koopman operator.
Camilo Garcia-Tenorio, Duvan Tellez-Castro, Eduardo Mojica-Nava, Alain Vande Wouwer   +3 more
doaj   +4 more sources

Extending the extended dynamic mode decomposition with latent observables: the latent EDMD framework [PDF]

Machine Learning: Science and Technology, 2023
Bernard O Koopman proposed an alternative view of dynamical systems based on linear operator theory, in which the time evolution of a dynamical system is analogous to the linear propagation of an infinite-dimensional vector of observables.
Said Ouala, Bertrand Chapron, Fabrice Collard, Lucile Gaultier, Ronan Fablet   +4 more
doaj   +5 more sources

Trigonometric Embeddings in Polynomial Extended Mode Decomposition—Experimental Application to an Inverted Pendulum

Mathematics, 2021
The extended dynamic mode decomposition algorithm is a tool for accurately approximating the point spectrum of the Koopman operator. This algorithm provides an approximate linear expansion of non-linear discrete-time systems, which can be useful for ...
Camilo Garcia-Tenorio, Gilles Delansnay, Eduardo Mojica-Nava, Alain Vande Wouwer   +3 more
doaj   +4 more sources

Orthogonal polynomial approximation and Extended Dynamic Mode Decomposition in chaos

SIAM Journal on Numerical Analysis
Extended Dynamic Mode Decomposition (EDMD) is a data-driven tool for forecasting and model reduction of dynamics, which has been extensively taken up in the physical sciences.
Wormell, Caroline L.
core   +4 more sources

Data-driven MPC with stability guarantees using extended dynamic mode decomposition

IEEE Transactions on Automatic Control
For nonlinear (control) systems, extended dynamic mode decomposition (EDMD) is a popular method to obtain data-driven surrogate models. Its theoretical foundation is the Koopman framework, in which one propagates observable functions of the state to ...
Grüne, Lars, Schaller, Manuel, Bold, Lea, Worthmann, Karl   +3 more
core   +5 more sources

Investigation of the Unsteady External and Underhood Airflow of the DrivAer model by Dynamic Mode Decomposition Methods

International Journal of Automotive Engineering, 2017
In this research, we conduct unsteady CFD to investigate the effect of engine bay flow on the steady and unsteady aerodynamics of the extended DrivAer model reproducing engine bay flow.
Daiki Matsumoto, Lukas Haag, Thomas Indinger   +2 more
doaj   +2 more sources

Adaptive Koopman Operator Learning via Iterative Projections: Time-Series Data Prediction Using Extended Dynamic Mode Decomposition

IEEE Access
This paper presents a novel framework for adaptive learning of Koopman operator to predict the behavior of nonlinear time-varying dynamical systems based on the celebrated extended dynamic mode decomposition (EDMD).
Reiya Asuke, Masahiro Yukawa
doaj   +2 more sources

Application of noise-filtering techniques to data-driven analysis of electric power systems based on higher-order dynamic mode decomposition

International Journal of Electrical Power & Energy Systems
A transition to renewable energy is increasing the long-distance export of power, with reduced spinning inertia and small stability margins. In this work, we apply higher-order variants of a data-driven technique, the dynamic mode decomposition (DMD ...
C.N.S. Jones, S.V. Utyuzhnikov
doaj   +2 more sources