Results 31 to 40 of about 47,248 (288)
Constrained Dynamic Mode Decomposition
IEEE Transactions on Visualization and Computer Graphics, 2022 Frequency-based decomposition of time series data is used in many visualization applications. Most of these decomposition methods (such as Fourier transform or singular spectrum analysis) only provide interaction via pre- and post-processing, but no means to influence the core algorithm.
Tim Krake +3 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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A characteristic dynamic mode decomposition [PDF]
Theoretical and Computational Fluid Dynamics, 2019 Temporal or spatial structures are readily extracted from complex data by modal decompositions like Proper Orthogonal Decomposition (POD) or Dynamic Mode Decomposition (DMD). Subspaces of such decompositions serve as reduced order models and define either spatial structures in time or temporal structures in space.
Sesterhenn, Jörn, Shahirpour, Amir
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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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Identification of dynamic textures using Dynamic Mode Decomposition [PDF]
, 2020 Dynamic Textures (DTs) are image sequences of moving scenes that present stationary properties in time. In this paper, we apply Dynamic Mode Decomposition (DMD) and Dynamic Mode Decomposition with Control (DMDc) to identify a parametric model of dynamic ...
Valceschini, Nicholas +3 more
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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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Scale-Separated Dynamic Mode Decomposition
, 2022 MatLab code to implement the Scale-Separated Dynamic Mode Decomposition method on electron density profile data ...
Alford-Lago
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Applying Dynamic Mode Decomposition to Interconnected Systems for Forecasting and System Identification [PDF]
, 2023 Dynamic Mode Decomposition (DMD) describes a family of dynamical systems analysis approaches that approximate complex, likely non-linear behaviors with a low-rank linear operator.
Bridges, Noah
core
Randomized Projection Learning Method for Dynamic Mode Decomposition
Mathematics, 2021 A data-driven analysis method known as dynamic mode decomposition (DMD) approximates the linear Koopman operator on a projected space. In the spirit of Johnson–Lindenstrauss lemma, we will use a random projection to estimate the DMD modes in a reduced ...
Sudam Surasinghe, Erik M. Bollt
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Investigating properties of the cardiovascular system using innovative analysis algorithms based on ensemble empirical mode decomposition [PDF]
, 2012 This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited - Copyright @ 2012 Jia-Rong Yeh et al ...
Lin, TY +5 more
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