Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Travis Askham"'
Publikováno v:
IEEE Access, Vol 7, Pp 1404-1423 (2019)
Regularized regression problems are ubiquitous in statistical modeling, signal processing, and machine learning. Sparse regression, in particular, has been instrumental in scientific model discovery, including compressed sensing applications, variabl
Externí odkaz:
https://doaj.org/article/1e55d42d8d56408eb857d269c8285e7e
Publikováno v:
SIAM Journal on Applied Dynamical Systems. 21:60-79
The dynamic mode decomposition (DMD) is a broadly applicable dimensionality reduction algorithm that approximates a matrix containing time-series data by the outer product of a matrix of exponentials, representing Fourier-like time dynamics, and a ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef147931a20eb0020b3341d707c7b617
https://doi.org/10.1137/21m1417405
https://doi.org/10.1137/21m1417405
Autor:
Antoine Cerfon, Geoffrey McFadden, Jon Wilkening, Jungpyo Lee, Tonatiuh Sanchez-Vizuet, Lise-Marie Imbert-Gérard, Dhairya Malhotra, Lee Ricketson, Martin Greenwald, Matt Landreman, Jeffrey Freidberg, Mike O'Neil, Felix Parra, Manas Rachh, Travis Askham, Eugenia Kim, Dan Segal, Justin Ball, Di Qi, Andrew Majda
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad145b993a805de25aa43884c72266f3
https://doi.org/10.2172/1856740
https://doi.org/10.2172/1856740
Publikováno v:
Journal of Computational Physics. 474:111792
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f4aa5b51337dbd3caf5a0ba00568e43
https://doi.org/10.1016/j.jcp.2022.111792
https://doi.org/10.1016/j.jcp.2022.111792
Autor:
Travis Askham, J. Nathan Kutz
Publikováno v:
SIAM Journal on Applied Dynamical Systems. 17:380-416
The dynamic mode decomposition (DMD) has become a leading tool for data-driven modeling of dynamical systems, providing a regression framework for fitting linear dynamical models to time-series measurement data. We present a simple algorithm for comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46df7ba80b0980ac692cd4c36709d58f
https://doi.org/10.1137/m1124176
https://doi.org/10.1137/m1124176
The integral equation approach to partial differential equations (PDEs) provides significant advantages in the numerical solution of the incompressible Navier-Stokes equations. In particular, the divergence-free condition and boundary conditions are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1cd03d7d3ded034854ae01522e98ad9
http://arxiv.org/abs/1908.07392
http://arxiv.org/abs/1908.07392
Autor:
Travis Askham, Manas Rachh
The eigenvalues and eigenfunctions of the Stokes operator have been the subject of intense analytical investigation and have applications in the study and simulation of the Navier-Stokes equations. As the Stokes operator is a fourth-order operator, c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::900c098795e5775b6e49997467e64297
http://arxiv.org/abs/1904.07351
http://arxiv.org/abs/1904.07351
Publikováno v:
Proceedings. Mathematical, Physical, and Engineering Sciences
Hybrid systems are traditionally difficult to identify and analyze using classical dynamical systems theory. Moreover, recently developed model identification methodologies largely focus on identifying a single set of governing equations solely from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f8042d8a1dee712e2f79059995886a2
http://arxiv.org/abs/1808.03251
http://arxiv.org/abs/1808.03251
Publikováno v:
IEEE Access, Vol 7, Pp 1404-1423 (2019)
Regularized regression problems are ubiquitous in statistical modeling, signal processing, and machine learning. Sparse regression in particular has been instrumental in scientific model discovery, including compressed sensing applications, variable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aef3a481b9f9b0218e7303a9873f017b
The problem of optimally placing sensors under a cost constraint arises naturally in the design of industrial and commercial products, as well as in scientific experiments. We consider a relaxation of the full optimization formulation of this problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eac5d29b518e0d3176861a1795baf94c