Empirical Interpolation Decomposition

Many physical problems need a multidimensional description and involve high dimensional spaces. Standard discretization techniques often lead to an excessive computation time. To solve this problem, we develop in this paper an empirical interpolation decomposition (EID) for multivariate functions. T...

Full description

Saved in:
Bibliographic Details
Published in:Acta applicandae mathematicae 2019-12, Vol.164 (1), p.49-64
Main Authors: Toumi, Asma, De Vuyst, Florian
Format: Article
Language:English
Subjects:
Algorithms
Applications of Mathematics
Approximation
Calculus of Variations and Optimal Control
Optimization
Computational Mathematics and Numerical Analysis
Computer Science
Decomposition
Hypotheses
Interpolation
Mathematics
Mathematics and Statistics
Modeling and Simulation
Partial Differential Equations
Probability Theory and Stochastic Processes
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Many physical problems need a multidimensional description and involve high dimensional spaces. Standard discretization techniques often lead to an excessive computation time. To solve this problem, we develop in this paper an empirical interpolation decomposition (EID) for multivariate functions. This method provides an approximate representation of a given function in separate form. Error estimates of the developed EID are derived and some properties are given.
ISSN:0167-8019
1572-9036
DOI:10.1007/s10440-018-0223-9