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On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator [PDF]

open access: greenJournal of Nonlinear Science, 2017
Extended Dynamic Mode Decomposition (EDMD) is an algorithm that approximates the action of the Koopman operator on an $N$-dimensional subspace of the space of observables by sampling at $M$ points in the state space. Assuming that the samples are drawn either independently or ergodically from some measure $ $, it was shown that, in the limit as $M ...
Milan Korda, Igor Mezić
openalex   +5 more sources

On the Effect of Quantization on Extended Dynamic Mode Decomposition [PDF]

open access: green2025 American Control Conference (ACC)
Extended Dynamic Mode Decomposition (EDMD) is a widely used data-driven algorithm for estimating the Koopman Operator. EDMD extends Dynamic Mode Decomposition (DMD) by lifting the snapshot data using nonlinear dictionary functions before performing the estimation.
Dilip Kumar Maity, Debdipta Goswami
openalex   +3 more sources

Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator [PDF]

open access: greenChaos: An Interdisciplinary Journal of Nonlinear Science, 2017
Numerical approximation methods for the Koopman operator have advanced considerably in the last few years. In particular, data-driven approaches such as dynamic mode decomposition (DMD)51 and its generalization, the extended-DMD (EDMD), are becoming increasingly popular in practical applications.
Qianxiao Li   +3 more
openalex   +6 more sources

Floquet angular modulation for 6G systems. [PDF]

open access: yesSci Rep
Hamdi B   +7 more
europepmc   +1 more source

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