What are some promising future directions for DMD research and applications?

Understanding nonlinear dynamical systems (NLDSs) is challenging in a variety of engineering and scientific fields. Dynamic mode decomposition (DMD), ... Jul 28, 2023 ... When analyzing high-dimensional time series, the DMD algorithm requires extremely large amounts of computational power. To accelerate the DMD ... 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 ... Jun 10, 2024 ... In summary, we have introduced a data-driven approach based on DMD to accelerate first-principles calculations of nonequilibrium electron ... We propose a modal decomposition algorithm to perform the analysis using finite-length data sequences generated from a nonlinear system. Aug 29, 2024 ... We apply here an unsupervised data-driven algorithm, Dynamic Mode Decomposition (DMD), to sEEG recordings from five focal epilepsy patients. Feb 6, 2015 ... ... dynamic mode decomposition of large datasets. The dymode package also includes dymodem, a Matlab implementation of the code which accepts ... Jul 20, 2024 ... ... dynamic mode decomposition method'. Together they form a unique fingerprint. Decomposition Method Mathematics 100%. Dynamic Mode ... Jan 27, 2022 ... an equation-free, data-driven method for identifying coherent flow structures and their associated spatiotemporal dynamics — to estimate future ... Jul 9, 2014 ... ... dynamic modes' and to the decomposition technique as the 'dynamic mode decomposition'. This technique is at the basis of a Koopman analysis ...