Universität Wien FIND
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050074 VO Mathematical Modelling in Scientific Computing (2014W)

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Details

Language: German

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

On Oct 9, Nov 27 and Jan 8, the lecture takes place 8:00 - 11:15 am (no UE classes on these days). No lectures on Nov 13 and Nov 20, instead a "Tutorium" is offered. The final examination is scheduled for Jan 29, 2015.

Thursday 02.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 09.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 16.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 23.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 30.10. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 06.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 13.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 20.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 27.11. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 04.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 11.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 18.12. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 08.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 15.01. 08:00 - 09:30 Hörsaal 2, Währinger Straße 29 2.OG
Thursday 22.01. 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 reconstruction

Fundamentals 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).

Further literature will be announced during the course.

Association in the course directory

Last modified: Tu 17.12.2019 16:50