Compressed dynamic mode decomposition for background modeling
We introduce the method of compressed dynamic mode decomposition (cDMD) for
background modeling. The dynamic mode decomposition is a regression technique that …
background modeling. The dynamic mode decomposition is a regression technique that …
[HTML][HTML] Nonlinearity in thermal comfort-based control systems: A systematic review
This work presents an in-depth systematic literature review of the strategies used to
characterise and quantify thermal comfort conditioned by mechanical HVAC systems. The …
characterise and quantify thermal comfort conditioned by mechanical HVAC systems. The …
[HTML][HTML] Robust and optimal sparse regression for nonlinear PDE models
DR Gurevich, PAK Reinbold… - Chaos: An Interdisciplinary …, 2019 - pubs.aip.org
This paper investigates how models of spatiotemporal dynamics in the form of nonlinear
partial differential equations can be identified directly from noisy data using a combination of …
partial differential equations can be identified directly from noisy data using a combination of …
Randomized low-rank dynamic mode decomposition for motion detection
NB Erichson, C Donovan - Computer Vision and Image Understanding, 2016 - Elsevier
This paper introduces a fast algorithm for randomized computation of a low-rank Dynamic
Mode Decomposition (DMD) of a matrix. Here we consider this matrix to represent the …
Mode Decomposition (DMD) of a matrix. Here we consider this matrix to represent the …
Spatiotemporal superresolution measurement based on POD and sparse regression applied to a supersonic jet measured by PIV and near-field microphone
The present study proposed the framework of the spatiotemporal superresolution
measurement based on the sparse regression with dimensionality reduction using the …
measurement based on the sparse regression with dimensionality reduction using the …
Quantitative evaluation of predictability of linear reduced-order model based on particle-image-velocimetry data of separated flow field around airfoil
A quantitative evaluation method for a reduced-order model of the flow field around an
NACA0015 airfoil based on particle image velocimetry (PIV) data is proposed in the present …
NACA0015 airfoil based on particle image velocimetry (PIV) data is proposed in the present …
Data-driven modeling of an elastomer bushing system under various visco-hyperelastic deformations
Since visco-hyperelastic materials are vastly used in different industries, a proper
constitutive model plays a key role in predicting materials' behavior. On the other hand, due …
constitutive model plays a key role in predicting materials' behavior. On the other hand, due …
Self-excited second-order azimuthal thermoacoustic instabilities in an annular combustor with oblique-injecting swirling burners
Y Fang, G Wang, Z Lyu - … of Engineering for …, 2022 - asmedigitalcollection.asme.org
In this paper, we experimentally investigate the thermoacoustic instability issue in an
annular combustor with 16 oblique-injecting premixed swirling burners. It is demonstrated …
annular combustor with 16 oblique-injecting premixed swirling burners. It is demonstrated …
Development of reduced order hydro-mechanical models of fractured media
Fully coupled hydro-mechanical simulations of fractured media require sophisticated non-
linear solvers to capture the complex relationship between fluid flow and a material's …
linear solvers to capture the complex relationship between fluid flow and a material's …
Structural balance of multiplex signed networks: A distributed data-driven approach
This paper examines the data-driven verification of structural balance of multiplex networks
by utilizing the dataset generated by the bipartite consensus dynamics adopted by each …
by utilizing the dataset generated by the bipartite consensus dynamics adopted by each …