A Generalized Empirical Interpolation Method: application of reduced basis techniques to data assimilation
Numerical Analysis
2017-05-09 v1 Analysis of PDEs
Abstract
This paper introduces a generalization of the empirical interpolation method (EIM) and the reduced basis method (RBM) in order to allow their combination with data mining and data assimilation. The purpose is to be able to derive sound information from data and reconstruct information, possibly taking into account noise in the acquisition, that can serve as an input to models expressed by partial differential equations. The approach combines data acquisition (with noise) with domain decomposition techniques and reduced basis approximations.
Keywords
Cite
@article{arxiv.1512.00683,
title = {A Generalized Empirical Interpolation Method: application of reduced basis techniques to data assimilation},
author = {Y. Maday and O. Mula},
journal= {arXiv preprint arXiv:1512.00683},
year = {2017}
}
Comments
in Analysis and Numerics of Partial Differential Equations, Springer INdAM Series, volume 4, p. 221--235, 2013