Model reduction by separation of variables: a comparison between Hierarchical Model reduction and Proper Generalized Decomposition
Code:
62/2018
Title:
Model reduction by separation of variables: a comparison between Hierarchical Model reduction and Proper Generalized Decomposition
Date:
Thursday 13th December 2018
Author(s):
Perotto, S.; Carlino, M.G.; Ballarin, F.
Abstract:
Hierarchical Model reduction and Proper Generalized
Decomposition both exploit separation of variables
to perform a model reduction. After setting the basics, we exemplify
these techniques on some standard elliptic problems
to highlight pros and cons of the two procedures, both from a
methodological and a numerical viewpoint.