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Sparse spectral approximations for computing polynomial functionals
Erwan Faou 1, 2, Fabio Nobile 3, Christophe Vuillot 2, 4
(2012)

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral eigenfunctions that turns out to be satisfied in many cases, including the Fourier and Hermite basis.
1:  Institut de Recherche Mathématique de Rennes (IRMAR)
CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
2:  IPSO (INRIA - IRMAR)
CNRS : UMR6074 – INRIA – Université de Rennes 1
3:  Ecole Polytechnique Fédérale de Lausanne (EPFL)
École Polytechnique Fédérale de Lausanne
4:  École normale supérieure de Cachan, antenne de Bretagne (ENS Cachan Bretagne)
École normale supérieure de Cachan - ENS Cachan
Analyse numérique
Mathematics/Numerical Analysis
Spectral methods – Sparse representations – Hermite polynomials
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