Results 1 to 10 of about 47,248 (288)

Non-Stationary Dynamic Mode Decomposition. [PDF]

IEEE Access, 2023
Many physical processes display complex high-dimensional time-varying behavior, from global weather patterns to brain activity. An outstanding challenge is to express high dimensional data in terms of a dynamical model that reveals their spatiotemporal ...
Ferré J, Rokem A, Buffalo EA, Kutz JN, Fairhall A.   +4 more
europepmc   +5 more sources

Robust Dynamic Mode Decomposition

IEEE Access, 2021
This paper develops a robust dynamic mode decomposition (RDMD) method endowed with statistical and numerical robustness. Statistical robustness ensures estimation efficiency at the Gaussian and non-Gaussian probability distributions, including heavy ...
Netto, Marcos, Mili, Lamine M., Mili, Lamine, Abolmasoumi, Amir Hossein, Hossein Abolmasoumi, Amir   +4 more
core   +5 more sources

Large Eddy Simulation and Dynamic Mode Decomposition of Turbulent Mixing Layers

Applied Sciences (Switzerland), 2021
Turbulent mixing layers are canonical flow in nature and engineering, and deserve comprehensive studies under various conditions using different methods. In this paper, turbulent mixing layers are investigated using large eddy simulation and dynamic mode
Yuwei Cheng, Qian Chen
exaly   +4 more sources

On Alternative Algorithms for Computing Dynamic Mode Decomposition

Computation, 2022
Dynamic mode decomposition (DMD) is a data-driven, modal decomposition technique that describes spatiotemporal features of high-dimensional dynamic data.
Gyurhan Nedzhibov
core   +2 more sources

Delay-Embedding Spatio-Temporal Dynamic Mode Decomposition

Mathematics
Spatio-temporal dynamic mode decomposition (STDMD) is an extension of dynamic mode decomposition (DMD) designed to handle spatio-temporal datasets. It extends the framework so that it can analyze data that have both spatial and temporal variations.
Gyurhan Nedzhibov
core   +2 more sources

Preconditioned dynamic mode decomposition and mode selection algorithms for large datasets using incremental proper orthogonal decomposition

AIP Advances, 2017
In this letter, we propose a simple and efficient framework of dynamic mode decomposition (DMD) and mode selection for large datasets. The proposed framework explicitly introduces a preconditioning step using an incremental proper orthogonal ...
Yuya Ohmichi
core   +2 more sources

Real-time motion detection using dynamic mode decomposition. [PDF]

EURASIP J Image Video Process
Dynamic mode decomposition (DMD) is a numerical method that seeks to fit time-series data to a linear dynamical system. In doing so, DMD decomposes dynamic data into spatially coherent modes that evolve in time according to exponential growth/decay or ...
Mignacca M, Brugiapaglia S, Bramburger JJ.   +2 more
europepmc   +2 more sources

Moving Target Detection Using Dynamic Mode Decomposition. [PDF]

Sensors (Basel), 2018
It is challenging to detect a moving target in the reverberant environment for a long time. In recent years, a kind of method based on low-rank and sparse theory was developed to study this problem.
Yin J, Liu B, Zhu G, Xie Z.
europepmc   +2 more sources

Personalized prediction of gait freezing using dynamic mode decomposition. [PDF]

Sci Rep
Freezing of gait (FoG) is a common severe gait disorder in patients with advanced Parkinson’s disease. The ability to predict the onset of FoG episodes early on allows for timely intervention, which is essential for improving the life quality of patients.
Fu Z, Lin C, Zhang Y.
europepmc   +2 more sources

Camera-Based Dynamic Vibration Analysis Using Transformer-Based Model CoTracker and Dynamic Mode Decomposition. [PDF]

Sensors (Basel)
Accelerometers are commonly used to measure vibrations for condition monitoring in mechanical and civil structures; however, their high cost and point-based measurement approach present practical limitations.
Cheng L, de Groot J, Xie K, Si Y, Han X.
europepmc   +2 more sources