A survey on the methods and results of data-driven koopman analysis in the visualization of dynamical systems
N Parmar, HH Refai… - IEEE Transactions on Big …, 2020 - ieeexplore.ieee.org
Koopman mode decomposition is a flow analysis technique developed by Igor Mezić in
2004, based upon the Koopman operator first proposed by Bernard Koopman in 1931. Via …
2004, based upon the Koopman operator first proposed by Bernard Koopman in 1931. Via …
Exploring the Molecular-Scale Structures at Solid/Liquid Interfaces of Li-Ion Battery Materials: A Force Spectroscopy Analysis with Sparse Modeling
Y Yamagishi, S Ohuchi, E Igaki, K Kobayashi - Nano Letters, 2024 - ACS Publications
In this study, we clarify the liquid structure formed at the interface between LiCoO2 (LCO),
the cathode material of Li-ion batteries, and propylene carbonate (PC), which is used as a …
the cathode material of Li-ion batteries, and propylene carbonate (PC), which is used as a …
Reduced-order modeling for dynamic mode decomposition without an arbitrary sparsity parameter
Dynamic mode decomposition (DMD) yields a linear, approximate model of a system's
dynamics that is built from data. This paper seeks to reduce the order of this model by …
dynamics that is built from data. This paper seeks to reduce the order of this model by …
Normal mode analysis of a relaxation process with Bayesian inference
Measurements of relaxation processes are essential in many fields, including nonlinear
optics. Relaxation processes provide many insights into atomic/molecular structures and the …
optics. Relaxation processes provide many insights into atomic/molecular structures and the …
Complex energies of the coherent longitudinal optical phonon–plasmon coupled mode according to dynamic mode decomposition analysis
In a dissipative quantum system, we report the dynamic mode decomposition (DMD)
analysis of damped oscillation signals. We used a reflection-type pump-probe method to …
analysis of damped oscillation signals. We used a reflection-type pump-probe method to …
Reduced-order modeling using dynamic mode decomposition and least angle regression
Dynamic Mode Decomposition (DMD) yields a linear, approximate model of a system's
dynamics that is built from data. We seek to reduce the order of this model by identifying a …
dynamics that is built from data. We seek to reduce the order of this model by identifying a …
Data-Driven Modeling and Estimation of Unsteady Flow Past Aerodynamic Surfaces
J Graff - 2023 - search.proquest.com
Estimation of unsteady flow-fields around flight vehicles may improve flow interactions and
lead to enhanced vehicle performance. Recent progress in computing has enabled the …
lead to enhanced vehicle performance. Recent progress in computing has enabled the …
Appropriate basis selection based on Bayesian inference for analyzing measured data reflecting photoelectron wave interference
In this study, we applied Bayesian inference to extended X-ray absorption fine structure
(EXAFS) to select an appropriate basis from Fourier, windowed Fourier, and advanced …
(EXAFS) to select an appropriate basis from Fourier, windowed Fourier, and advanced …
Data-Driven Modeling of Unsteady Fluid Flows Using Least Angle Regression
J Graff - 2021 - search.proquest.com
Recent progress in computing has enabled the development of data-driven techniques for
developing models of dynamical systems. These models are often large in size, yet may …
developing models of dynamical systems. These models are often large in size, yet may …
スパース・モデリングを用いた広域X 線吸収微細構造の解析
赤井一郎， 岩満一功， 五十嵐康彦， 岡田真人… - 日本結晶学会 …, 2020 - jstage.jst.go.jp
抄録 We propose a new method to extract the informations of microscopic structure from the
extended X-ray absorption fine structure by the application of sparse modeling based on a …
extended X-ray absorption fine structure by the application of sparse modeling based on a …