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Numerical Solution Methods for Finite Dimensional Problems
(dt. Numerik endlichdimensionaler Probleme)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (4 SWS), recitation class (2 SWS),
270 hours (90 h attendance, 180 h private study)
Credit points,
formal requirements		 9 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises.
Examination type: Written or oral examination (individual examination)
Language,
Grading		 English,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Mathematics.
Duration,
frequency		 One semester,
Jedes zweite Wintersemester
Person in charge of the module's outline Prof. Dr. Christian Rieger

Contents

Methods for eigenvalue problems of matrices, fast iteration methods for large systems of equations. Selected additions, such as curve tracking for nonlinear equation systems or fast decomposition methods (FFT, wavelet transformation)


Qualification Goals

Students

  • are able to classify practical problems in terms of applicable procedures and the effort involved,
  • understand various procedures, their different areas of application and their differences in terms of efficiency and universality,
  • recognize how to build up and analyze solution methods from different basic procedures for complex tasks,
  • understand, in the core topic of iterative methods for large systems of equations, the construction of efficient methods by combining building blocks of different characteristics,
  • have deepened mathematical working methods(developing mathematical intuition and its formal justification, abstraction, proof),
  • have improved their oral communication skills in exercises by practicing free speech in front of an audience and in discussion.

Prerequisites

None. The competences taught in the following modules are recommended: either Foundations of Mathematics and Linear Algebra I and Linear Algebra II or Basic Linear Algebra, either Analysis I and Analysis II or Basic Real Analysis, Numerical Analysis.


Applicability

Module imported from M.Sc. Mathematics.

It can be attended at FB12 in study program(s)

  • B.Sc. Data Science
  • B.Sc. Mathematics
  • B.Sc. Business Mathematics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Mathematics
  • LAaG Mathematics

When studying B.Sc. Data Science, this module can be attended in the study area Free Compulsory Elective Modules.

The module is assigned to Mathematics. Further information on eligibility can be found in the description of the study area.


Recommended Reading

  • Stoer, J., Bulirsch, R.: Numerische Mathematik II, Springer, 2000;
  • Golub, G., van Loan, C.: Matrix Computations, The Johns Hopkins University Press, 1990;
  • Hanke-Bourgeois, M.: Grundlagen der Numerischen Mathematik und des Wissenschaftlichen Rechnens, Teubner, 2002.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2023/24. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

  • Winter 2016/17 (no corresponding element)
  • Summer 2018 (no corresponding element)
  • Winter 2018/19 (no corresponding element)
  • Winter 2019/20 (no corresponding element)
  • Winter 2020/21 (no corresponding element)
  • Summer 2021 (no corresponding element)
  • Winter 2021/22 (no corresponding element)
  • Winter 2022/23 (no corresponding element)
  • Winter 2023/24

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.