050074 VO Mathematical Modelling in Scientific Computing (2016W)
Labels
Details
Language: German
Examination dates
- Thursday 26.01.2017 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Wednesday 31.05.2017 08:00 - 09:30 Hörsaal 1, Währinger Straße 29 1.UG
- Wednesday 28.06.2017 08:00 - 09:30 Hörsaal 1, Währinger Straße 29 1.UG
Lecturers
Classes (iCal) - next class is marked with N
Do 06.10. VO 08:00 - 11:15h, UE entfällt
Do 13.10. VO entfällt
- Thursday 06.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 13.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 20.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 27.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 03.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 10.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 17.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 24.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 01.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 15.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 12.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
- Thursday 19.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Information
Aims, contents and method of the course
Foundations of digital signal processing: linear systems, transformations (Discrete Fourier Transform, z Transform, FFT), filter, signal sampling and reconstructionFundamentals of performance analysis of communication networks (stochastic processes, simple queueing models, Erlang's loss formula)Basic simulation technics (random numbers, discrete event simulation, applications)
Assessment and permitted materials
Written exam at the end of the course.
Minimum requirements and assessment criteria
The students acquire the skills to apply the mathematical methods presented for analysing related problems in the field of scientific computing and solving them with the help of relevant software support.
Examination topics
Presentation including jointly solved example problems.Assumed previous knowledge: mathematics according to the module "Mathematische Basistechniken" (especially complex numbers and complex exponential function; matrix calculation, eigenvalues and eigenvectors), formal techniques of scientific computing according to the module "Formale Techniken des Scientific Computing"
Reading list
Oppenheim, Alan; Schafer, Ronald: Discrete-Time Signal Processing. Prentice Hall.Lyons, Richard: Understanding Digital Signal Processing. 3. Auflage, Pearson 2011.Meyer Martin: Signalverarbeitung, 7. Auflage. Vieweg, Teubner, Wiesbaden 2013 (ISBN 978-3-8348-0494-5).L. Kleinrock: Queuing Systems I: Theory. Wiley 1975.B. Haverkort: Performance of Computer Communication Systems: A Model-based Approach. Wiley 1998.Baron, Michael: Probability and Statistics for Computer Scientists. Chapman & Hall / CRC 2007 (ISBN 1-58488-641-2).Überhuber, Christian, Katzenbeisser Stefan: MATLAB 6 Springer, Wien 2000
(ISBN 3-211-83487-7).Weitere Literatur wird in der VO bekanntgegeben.
(ISBN 3-211-83487-7).Weitere Literatur wird in der VO bekanntgegeben.
Association in the course directory
Last modified: Mo 07.09.2020 15:29