Can DMD be used as a preprocessing step for other machine learning algorithms?

Apr 6, 2017 ... ... dynamic mode decomposition (WR-DMD). Our proposed method is validated on ten different healthy volunteers' kidney DCE-MRI data sets. The ... Title, 24. DGLR STAB-Symposium. Duration, 13 - 14 November 2024. Degree of recognition, National event. Location, OTH Regensburg. City, Regensburg. Aug 29, 2024 ... We apply here an unsupervised data-driven algorithm, Dynamic Mode Decomposition (DMD), to sEEG recordings from five focal epilepsy patients. Jul 28, 2023 ... When analyzing high-dimensional time series, the DMD algorithm requires extremely large amounts of computational power. To accelerate the DMD ... We propose a modal decomposition algorithm to perform the analysis using finite-length data sequences generated from a nonlinear system. Dynamic Mode Decomposition (DMD) is a popular data-driven analysis technique used to decompose complex, nonlinear systems into a set of modes, revealing ... Nov 12, 2021 ... The method is capable of characterizing nonlinear, time-varying, multidimensional time series data in a computationally efficient manner. The ... Jan 10, 2023 ... The Dynamic Mode Decomposition has proved to be a very efficient technique to study dynamic data. This is entirely a data-driven approach that ... A spatio-temporal method based on Robust Three-stage Dynamic Mode Decomposition (RTDMD) is proposed to improve the modal parameter estimation of ... Jun 19, 2019 ... ... method for modeling dynamical systems called the Dynamic Mode Decomposition (DMD). This is a recent method that has first emerged in the ...