What insights can DMD provide into the structure and dynamics of turbulence?

... dynamic mode decomposition (DMD). The DMD spectrum and DMD modes are retrieved from the propagation of the relevant states along the topological boundary ... Jun 5, 2015 ... We will show that this approach is, in effect, an extension of dynamic mode decomposition (DMD), which has been used to approximate the Koopman ... Mar 19, 2019 ... Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, ... In particular, we explore an algorithm rooted in fluid-dynamics, known as higher-order Dynamic Mode Decomposition, which is designed to capture the ... May 30, 2024 ... Dive into the research topics of 'Camera-Based Dynamic Vibration Analysis Using Transformer-Based Model CoTracker and Dynamic Mode Decomposition ... Dynamic Mode Decomposition (DMD) is a popular data-driven analysis technique used to decompose complex, nonlinear systems into a set of modes, revealing ... Jan 27, 2022 ... an equation-free, data-driven method for identifying coherent flow structures and their associated spatiotemporal dynamics — to estimate future ... In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially high-dimensional data sets. Abstract. This work develops compressed sensing strategies for computing the dynamic mode decomposition (DMD) from heavily subsampled or compressed data. The ... In this paper, we propose subspace DMD as an algorithm for the Koopman analysis of random dynamical systems with observation noise.