Results 31 to 40 of about 5,559,251 (271)
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
doaj +1 more source
Modal Analysis of the Human Brain Using Dynamic Mode Decomposition. [PDF]
Bioengineering (Basel)McLean J +3 more
europepmc +2 more sources
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
openaire +2 more sources
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
openaire +3 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Enhanced monopulse radar tracking using empirical mode decomposition [PDF]
, 2010 Monopulse radar processors are used to track targets that appear in the look direction beamwidth. The target tracking information (range, azimuth angle, and elevation angle) are affected when manmade high power interference (jamming) is introduced to the
Elgamel, Sherif A.E.H., Soraghan, J.J.
core +3 more sources
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
doaj +1 more source
Port-Hamiltonian Dynamic Mode Decomposition
SIAM Journal on Scientific Computing, 2023 We present a novel physics-informed system identification method to construct a passive linear time-invariant system. In more detail, for a given quadratic energy functional, measurements of the input, state, and output of a system in the time domain, we find a realization that approximates the data well while guaranteeing that the energy functional ...
Riccardo Morandin +2 more
openaire +3 more sources