What are the challenges of applying DMD to systems with discrete particle interactions?

Spectral decomposition of the Koopman operator is attracting attention as a tool for the analysis of nonlinear dynamical systems. Dynamic mode decomposition. May 26, 2022 ... May 26, 2022. DTU Wind and Energy Systems. 27. Identification of large-scale, atmospheric structures using, Dynamic Mode Decomposition. Dynamic mode decomposition (DMD) is a recently developed method focused on discovering coherent spatial-temporal modes in high-dimensional data collected from ... ... dynamic mode decomposition to reconstruct the final steady state given only few snapshots of the simulation, and the reduction of the parameter space by AS ... Jul 25, 2016 ... The DMD converts a dynamical system into a superposition of modes whose dynamics are governed by eigenvalues. Sep 6, 2024 ... Dynamic mode decomposition analysis of very low frequency oscillations on the Irish grid. In 59th International Universities Power ... In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially high-dimensional data sets. Feb 8, 2025 ... Huang, Qiuxiang, Kou, Jiaqing, Tian, Fang Bao, Young, John, Lai, Joseph C.S., & Ravi, Sridhar (2023) Dynamic mode decomposition for unsteady ... Title, 24. DGLR STAB-Symposium. Duration, 13 - 14 November 2024. Degree of recognition, National event. Location, OTH Regensburg. City, Regensburg. Dynamic Mode Decomposition (DMD) is a popular data-driven analysis technique used to decompose complex, nonlinear systems into a set of modes, revealing ...