Proceedings in Applied Mathematics and Mechanics (2014)
Himpe Christian and Ohlberger Mario
By Himpe Christian
Working Paper (2020)
In this work, the empirical-Gramian-based model reduction methods: Empirical poor man's truncated balanced realization, empirical approximate balancing, empirical dominant subspaces, empirical balanced truncation, and empirical balanced gains are compared in a non-parametric and two parametric variants, via ten error measures: Approximate Lebesgue L_0, L_1, L_2, L_∞, Hardy H_2, H_∞, Hankel, Hilbert-Schmidt-Hankel, modified induced primal, and modified induced dual norms, for variants of the thermal block model reduction benchmark. This comparison is conducted via a new meta-measure for model reducibility called MORscore.
Himpe C. (2020) Comparing (Empirical-Gramian-Based) Model Order Reduction Algorithms. Working Paper.