Module Handbook

  • Dynamischer Default-Fachbereich geändert auf MAT

Course MAT-81-39-K-7

Model Order Reduction for Large Scale Systems (2V, 4.5 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
2 V Lecture 4.5 CP 28 h 107 h
(2V) 4.5 CP 28 h 107 h

Basedata

SWS 2V
CP, Effort 4.5 CP = 135 h
Position of the semester 1 Sem. irreg.
Level [7] Master (Advanced)
Language [EN] English
Lecturers
+ further Lecturers of the department Mathematics
Area of study [MAT-TEMA] Industrial Mathematics
Additional informations
Livecycle-State [NORM] Active

Contents

Model reduction methods for ordinary and partial differential equations are discussed, in particular
  • Krylov space methods,
  • reduced bases,
  • Proper Orthogonal Decomposition (POD).

Literature

  • A.C. Antoulas: Approximation of Large-Scale Dynamical Systems,
  • A.T. Patera and G. Rozza, Reduced Basis Approximation and A Posteriori Error Estima-tion for Parametrized Partial Differential Equations,
  • P. Benner, V. Mehrmann, D.C. Sorensen: Dimension Reduction of Large-Scale Systems,
  • W.H. Schilders, H.A. van der Vorst, J. Rommes: Model Order Reduction: Theory, Re-search Aspects and Applications.

Materials

[MAT:LIT]

References to Course [MAT-81-39-K-7]

Module Name Context
[MAT-81-39-M-7] Model Order Reduction for Large Scale Systems P: Obligatory 2V, 4.5 LP