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
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Bagging, optimized dynamic mode decomposition for robust, stable forecasting with spatial and temporal uncertainty quantification [PDF]
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2022 Dynamic mode decomposition (DMD) provides a regression framework for adaptively learning a best-fit linear dynamics model over snapshots of temporal, or spatio-temporal, data. A variety of regression techniques have been developed for producing the linear model approximation whose solutions are exponentials in time.
Diya Sashidhar, J. Nathan Kutz
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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
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PF-DMD: Physics-fusion dynamic mode decomposition for accurate and robust forecasting of dynamical systems with imperfect data and physics [PDF]
, 2023 The DMD (Dynamic Mode Decomposition) method has attracted widespread attention as a representative modal-decomposition method and can build a predictive model. However, the DMD may give predicted results that deviate from physical reality in some scenarios, such as dealing with translation problems or noisy data.
Yin, Yuhui +5 more
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Grassmannian Geometry Meets Dynamic Mode Decomposition in DMD-GEN: A New Metric for Mode Collapse in Time Series Generative Models [PDF]
CoRRGenerative models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) often fail to capture the full diversity of their training data, leading to mode collapse. While this issue is well-explored in image generation, it remains underinvestigated for time series data.
Amine Mohamed Aboussalah +1 more
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Regularized dynamic mode decomposition algorithm for time sequence predictions
Theoretical and Applied Mechanics LettersDynamic mode decomposition (DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions.
Xiaoyang Xie, Shaoqiang Tang
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Prediction of induced soil vibration during pile vibrodriving using Dynamic Mode Decomposition (DMD)
Journal of Physics: Conference SeriesAbstract This study investigates using the Dynamic Mode Decomposition (DMD) algorithm to perform approximations and time-ahead prediction of soil vibrations during the vibrodriving process. Geotechnical applications face challenges in modeling and predicting soil vibrations due to the soil’s heterogeneous nature.
Williams Riquer, Francisco +3 more
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Towards an Adaptive Dynamic Mode Decomposition
Results in Control and Optimization, 2022 Dynamic Mode Decomposition (DMD) is a tool that creates an approximate model from spatio-temporal data. We have developed an architecture of this tool that will adapt to the data from a given problem by leveraging time delay coordinates, projections, and
Mohammad N. Murshed, M. Monir Uddin
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Dynamic mode decomposition of numerical data in natural circulation
Brazilian Journal of Radiation Sciences, 2021 Dynamic mode decomposition (DMD) has been used for experimental and numerical data analysis in fluid dynamics. Despite of its advantages, the application of the DMD methodology to investigate the natural circulation in nuclear reactors are very scarce in
José Luiz Horacio Faccini
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Tomographic Particle Image Velocimetry and Dynamic Mode Decomposition (DMD) in a Rectangular Impinging Jet: Vortex Dynamics and Acoustic Generation [PDF]
Fluids, 2021 Impinging jets are encountered in ventilation systems and many other industrial applications. Their flows are three-dimensional, time-dependent, and turbulent. These jets can generate a high level of noise and often present a source of discomfort in closed areas.
Hassan H. Assoum +6 more
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