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pro vyhledávání: '"Anna Matsekh"'
Autor:
Anna Pietarila Graham, Jeffrey Haack, Alex Long, Christopher Mauney, Daniel Holladay, Rob Aulwes, Philipp Edelmann, Jonathan Pietarila Graham, Sumathi Lakshmiranganatha, Anna Matsekh, Nathan Hart, Robert Zerr, Daniel Magee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84a8f98d21a86c40ad4f7bf94e6ad24b
https://doi.org/10.2172/1900454
https://doi.org/10.2172/1900454
Publikováno v:
Journal of Computational Physics. 388:416-438
We propose an efficient, robust, Lagrangian (characteristic-based) transport solver for 1-D time-dependent thermal radiative transfer (TRT) applications within the context of a moment-accelerated (High-Order/Low-Order, HOLO) algorithm. This novel tra
On learning particle distributions in the 1D implicit Monte Carlo simulations of radiation transport
Publikováno v:
Applications of Machine Learning 2020.
Monte Carlo based thermal radiative transfer (TRT) codes provide a flexible framework for large-scale high-energy-density simulations. Compared to their deterministic counterparts, Monte Carlo methods are easier to implement in complex geometries and
Autor:
Anna Matsekh
Publikováno v:
Applied Numerical Mathematics. 54:208-221
We present a new algorithm for computing eigenvectors of real symmetric tridiagonal matrices based on Godunov's two-sided Sturm sequence method and inverse iteration, which we call the Godunov-inverse iteration. We use eigenvector approximations comp
Autor:
James Theiler, Anna Matsekh
Publikováno v:
IGARSS
We use singular vectors of the whitened cross-covariance matrix of two hyper-spectral images and the Golub-Kahan permutations in order to obtain equivalent tridiagonal representations of the coefficient matrices for a family of covariance-based quadr
Autor:
James Theiler, Anna Matsekh
Publikováno v:
SPIE Proceedings.
A family of subtraction-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both c