Universität Wien

052101 VU Numerical Algorithms (2019W)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 07.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 14.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 21.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 28.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 04.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 11.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 18.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 25.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 02.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 09.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 16.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 13.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 20.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 27.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
  • Monday 27.01. 15:00 - 16:30 Hörsaal 2, Währinger Straße 29 2.OG

Information

Aims, contents and method of the course

Get acquainted with fundamental concepts of numerical algorithms (approximations in numerical computation, conditioning, numerical stability) and with techniques for the analysis of numerical algorithms (perturbation theory). Study selected numerical algorithms (mostly matrix algorithms) in detail. Understand the interdependencies between problem data, numerical algorithm, implementation of the algorithm, hardware, performance and accuracy.

Assessment and permitted materials

Three sets of homework problems (with theoretical and programming components - implementation, experimentation, analysis); test in the middle and in the end of the semester.

Minimum requirements and assessment criteria

The maximum possible score is 100 points (12 per set of homework problems, 32 per test). At least 50 points are required for passing the course.

Examination topics

Material presented in class and contents of homework problems.

Reading list

Slides; M. T. Heath: “Scientific Computing – an Introductory Survey”

Association in the course directory

Last modified: Mo 07.09.2020 15:20