A generalized empirical interpolation method: application of reduced basis techniques to data assimilation. (English) Zbl 1267.62013
Brezzi, Franco (ed.) et al., Analysis and numerics of partial differential equations. Selected papers based on a meeting in memory of Enrico Magenes, 2011. Milano: Springer (ISBN 978-88-470-2591-2/hbk; 978-88-470-2592-9/ebook). Springer INdAM Series 4, 221-235 (2013).
Summary: This paper, written as a tribute to Enrico Magenes, a giant that has kindly and warmly supported generations of young researchers, 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.
For the entire collection see [Zbl 1257.00014].
For the entire collection see [Zbl 1257.00014].
MSC:
| 62-07 | Data analysis (statistics) (MSC2010) |
