Results 31 to 40 of about 275,780 (304)
Large Eddy Simulation and Dynamic Mode Decomposition of Turbulent Mixing Layers
Applied Sciences, 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
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Dynamic Mode Decomposition of Fontan Hemodynamics in an Idealized Total Cavopulmonary Connection. [PDF]
Fluid Dyn Res, 2014 Delorme YT +4 more
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Visualization and selection of Dynamic Mode Decomposition components for unsteady flow
Visual Informatics, 2021 Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data.
T. Krake +4 more
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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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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.
Jörn Sesterhenn, Amir Shahirpour
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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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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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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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Higher Order Dynamic Mode Decomposition [PDF]
SIAM Journal on Applied Dynamical Systems, 2017 This paper deals with an extension of dynamic mode decomposition (DMD), which is appropriate to treat general periodic and quasi-periodic dynamics, and transients decaying to periodic and quasiperiodic attractors, including cases (not accessible to standard DMD) that show limited spatial complexity but a very large number of involved frequencies.
Le Clainche Martínez, Soledad +1 more
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