htw saar Piktogramm
Back to Main Page

Choose Module Version:
XML-Code

flag

Numerical Software

Module name (EN): Numerical Software
Degree programme: Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2011
Module code: MST.NSW
Hours per semester week / Teaching method: 2V+2PA (4 hours per week)
ECTS credits: 5
Semester: according to optional course list
Mandatory course: no
Language of instruction:
German
Assessment:
Case studies and micro-projects with the applications discussed

[updated 19.02.2018]
Curricular relevance:
KI672 Computer Science and Communication Systems, Bachelor, ASPO 01.10.2014, semester 6, optional course, technical
KIB-NUMS Computer Science and Communication Systems, Bachelor, ASPO 01.10.2017, optional course, technical
MST.NSW Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2012, optional course, technical
MST.NSW Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2019, optional course, technical
MST.NSW Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2020, optional course, technical
PIBWI92 Applied Informatics, Bachelor, ASPO 01.10.2011, semester 6, optional course, informatics specific
PIB-NUMS Applied Informatics, Bachelor, ASPO 01.10.2017, optional course, informatics specific
MST.NSW Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2011, optional course, technical
Workload:
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
MST.MA1 Mathematics I
MST.MA2 Mathematics II


[updated 10.05.2019]
Recommended as prerequisite for:
MST.MA3 Mathematics III / Applied Mathematics


[updated 10.05.2019]
Module coordinator:
Prof. Dr. Gerald Kroisandt
Lecturer:
Dipl.-Math. Dimitri Ovrutskiy


[updated 10.05.2019]
Lab:
Applied Mathematics, Statistics, and eLearning (5306)
Learning outcomes:
After successfully completing this module, students will be able to independently implement algorithms using Matlab to solve mathematical problems, process experimental data and display this data graphically.

[updated 19.02.2018]
Module content:
- Programming in Matlab
- Types of Matlab programs
- Graphical output in 2D and 3D
- Diagrams of statistical data and measurement data
- Symbolic calculations
 
Applications:
- Numerical integration
- Regression, interpolation and approximation
- Zero and fixed-point search
- Gradient method
 
 


[updated 19.02.2018]
Teaching methods/Media:
100% of the lecture will take place in the PC lab "Angewandte Mathematik, Statistik und eLearning".  All of the practical exercises for the lecture, as well as solving exercises, homework and case studies will be done with the e-learning system MathCoach and with mathematical numerical software (AMSEL lab: PC lab: "Angewandte Mathematik, Statistik und eLearning").

[updated 24.02.2018]
Recommended or required reading:
F. und F. Grupp: MATLAB 7 für Ingenieure: Grundlagen und Programmierbeispiele
O. Beucher: MATLAB und Simulink: Grundlegende Einführung für Studenten und Ingenieure in der Praxis (z.B. Pearson Studium, 2008)
W. Schweizer: MATLAB kompakt (z.B. Oldenbourg, 2009)
Lecture notes

[updated 19.02.2018]
[Sun Sep 19 15:09:23 CEST 2021, CKEY=km, BKEY=yst, CID=MST.NSW, LANGUAGE=en, DATE=19.09.2021]