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research article

On the optimal polynomial approximation of stochastic PDEs by Galerkin and Collocation methods

Beck, Joakim
•
Nobile, Fabio  
•
Tamellini, Lorenzo  
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2012
Mathematical Models and Methods in Applied Sciences (M3AS)

In this work we focus on the numerical approximation of the solution u of a linear elliptic PDE with stochastic coefficients. The problem is rewritten as a parametric PDE and the functional dependence of the solution on the parameters is approximated by multivariate polynomials. We first consider the Stochastic Galerkin method, and rely on sharp estimates for the decay of the Fourier coefficients of the spectral expansion of u on an orthogonal

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Type
research article
DOI
10.1142/S0218202512500236
Web of Science ID

WOS:000307022100006

Author(s)
Beck, Joakim
Nobile, Fabio  
Tamellini, Lorenzo  
Tempone, Raul
Date Issued

2012

Publisher

World Scientific Publ Co Pte Ltd

Published in
Mathematical Models and Methods in Applied Sciences (M3AS)
Volume

22

Issue

9

Start page

1250023.1

End page

1250023.33

Subjects

Uncertainty Quantification

•

PDEs with random data

•

elliptic equations

•

multivariate polynomial approximation

•

best M-terms approximation

•

Stochastic Galerkin methods

•

Smolyak approximation

•

Sparse grids

•

Stochastic Collocation methods

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CSQI  
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/79593
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