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High-dimensional separable compression and basic operations: a PGD arithmetic toolbox

Author
Diez, P.; Zlotnik, S.; Huerta, A.
Type of activity
Presentation of work at congresses
Name of edition
14th U. S. National Congress on Computational Mechanics
Date of publication
2017
Presentation's date
2017-07-17
Book of congress proceedings
14th U.S. National Congress on Computational Mechanics July 17-20, 2017, Montreal, Quebec, Canada
First page
196
Last page
196
URL
http://14.usnccm.org/sites/default/files/ABSTRACTS%20A-L.pdf Open in new window
Abstract
Separable approximations efficiently deal with high-dimensional data. In particular, the Proper Generalized Decomposition (PGD) provides separable functions as solutions of boundary value problems. The general PGD framework contains a large family of methodologies, all of them providing solutions of separable objects, that is a sum of terms, being each term a product of 1D functions (or arrays). Some of the PGD methodologies have been conceived to tackle nonlinear problems. We present a general ...
Group of research
LACÀN - Numerical Methods for Applied Sciences and Engineering

Participants