Results 11 to 20 of about 5,543,917 (241)
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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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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Analyzing Nonlinear Dynamics via Data-Driven Dynamic Mode Decomposition-Like Methods
Complexity, 2018 This article presents a review on two methods based on dynamic mode decomposition and its multiple applications, focusing on higher order dynamic mode decomposition (which provides a purely temporal Fourier-like decomposition) and spatiotemporal Koopman ...
Soledad Le Clainche, José M. Vega
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Delay-Embedding Spatio-Temporal Dynamic Mode Decomposition
MathematicsSpatio-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
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Robust Dynamic Mode Decomposition
IEEE Access, 2022 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 ...
Amir Hossein Abolmasoumi +2 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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Swarm Modeling With Dynamic Mode Decomposition
IEEE Access, 2022 Modelling biological or engineering swarms is challenging due to the inherently high dimension of the system, despite the often low-dimensional emergent dynamics.
Emma Hansen +2 more
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Computational and Mathematical Biophysics, 2023 The COVID-19 pandemic recently caused a huge impact on India, not only in terms of health but also in terms of economy. Understanding the spatio-temporal patterns of the disease spread is crucial for controlling the outbreak.
Rana Kanav Singh, Kumari Nitu
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Generalized eigenvalue approach for dynamic mode decomposition
AIP Advances, 2021 Traditional dynamic mode decomposition (DMD) methods inevitably involve matrix inversion, which often brings in numerical instability and spurious modes.
Wei Zhang, Mingjun Wei
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Bilinear dynamic mode decomposition for quantum control
New Journal of Physics, 2021 Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems and desired control objectives are critical for many emerging quantum technologies.
Andy Goldschmidt +4 more
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