Multivariate function approximation using sparse grids and high Dimensional Model Representation – a comparison
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RIS BIB ENDNOTEMultivariate function approximation using sparse grids and high Dimensional Model Representation – a comparison
Data publikacji: 10.02.2015
Czasopismo Techniczne, 2014, Nauki Podstawowe Zeszyt 3 NP (17) 2014, s. 97 - 107
https://doi.org/10.4467/2353737XCT.14.318.3406Autorzy
Multivariate function approximation using sparse grids and high Dimensional Model Representation – a comparison
In many areas of science and technology, there is a need for effective procedures for approximating multivariate functions. Sparse grids and cut-HDMR (High Dimensional Model Representation) are two alternative approaches to such multivariate approximations. It is therefore interesting to compare these two methods. Numerical experiments performed in this study indicate that the sparse grid approximation is more accurate than the cut-HDMR approximation that uses a comparable number of known values of the approximated function unless the approximated function can be expressed as a sum of high order polynomials of one or two variables.
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Informacje: Czasopismo Techniczne, 2014, Nauki Podstawowe Zeszyt 3 NP (17) 2014, s. 97 - 107
Typ artykułu: Oryginalny artykuł naukowy
Tytuły:
Multivariate function approximation using sparse grids and high Dimensional Model Representation – a comparison
Multivariate function approximation using sparse grids and high Dimensional Model Representation – a comparison
Institute of Teleinformatics, Faculty of Physics, Mathematics and Computer Science, Cracow University of Technology
Publikacja: 10.02.2015
Status artykułu: Otwarte
Licencja: Żadna
Udział procentowy autorów:
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