Efficient sensor node selection for observability Gramian optimization
Optimization approaches that determine sensitive sensor nodes in a large-scale, linear time-
invariant, and discrete-time dynamical system are examined under the assumption of …
invariant, and discrete-time dynamical system are examined under the assumption of …
Density field reconstruction from time-series schlieren images via extended phase-consistent dynamic mode decomposition
T Shigeta, T Nagata, T Nonomura - Experiments in Fluids, 2023 - Springer
The extended phase-consistent dynamic mode decomposition (DMD) method, which
reconstructs density fields from density gradient fields in multiple directions, was developed …
reconstructs density fields from density gradient fields in multiple directions, was developed …
[HTML][HTML] Dynamic mode decomposition based on expectation–maximization algorithm for simultaneous system identification and denoising
The present study proposes a novel dynamic mode decomposition (DMD) that can
simultaneously estimate the reduced-order model, the original signal, and the …
simultaneously estimate the reduced-order model, the original signal, and the …
[HTML][HTML] Reservoir computing reduced-order model based on particle image velocimetry data of post-stall flow
The present study proposes a reservoir computing reduced-order model (RCROM) of the
post-stall flow around the National Advisory Committee for Aeronautics 0015 airfoil based on …
post-stall flow around the National Advisory Committee for Aeronautics 0015 airfoil based on …
[HTML][HTML] Objective Model Selection in Physics: Exploring the Finite Information Quantity Approach
B Menin - Journal of Applied Mathematics and Physics, 2024 - scirp.org
Traditional methods for selecting models in experimental data analysis are susceptible to
researcher bias, hindering exploration of alternative explanations and potentially leading to …
researcher bias, hindering exploration of alternative explanations and potentially leading to …
[PDF][PDF] Reduced-order Reconstruction of Flow Field with Optimized Sparse Sampling and Data-driven Model
K YAMADA - tohoku.repo.nii.ac.jp
A systematic method is developed in this research to reconstruct a flow field from only a few
point measurements. The presented formulations give an estimate of flow fields instead of …
point measurements. The presented formulations give an estimate of flow fields instead of …
EM アルゴリズムに基づく動的モード分解による大規模データからの低次元化システムの同定
岩崎有登， 佐々木康雄， 永田貴之， 金子紗弓… - … 連合講演会講演論文集 …, 2023 - jstage.jst.go.jp
EMアルゴリズムに基づく動的モード分解による 大規模データからの低次元化システムの同定 Page 1
EMアルゴリズムに基づく動的モード分解による 大規模データからの低次元化システムの同定 ○岩崎 …
EMアルゴリズムに基づく動的モード分解による 大規模データからの低次元化システムの同定 ○岩崎 …