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Engineering Tools

Module name (EN):
Name of module in study programme. It should be precise and clear.
Engineering Tools
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Electrical Engineering and Information Technology, Bachelor, ASPO 01.10.2018
Module code: E2307
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P211-0098
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V (2 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
2
Semester: 3
Mandatory course: yes
Language of instruction:
German
Assessment:
Project work

[updated 08.01.2020]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

E2307 (P211-0098) Electrical Engineering and Information Technology, Bachelor, ASPO 01.10.2018 , semester 3, mandatory course, technical
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
30 class hours (= 22.5 clock hours) over a 15-week period.
The total student study time is 60 hours (equivalent to 2 ECTS credits).
There are therefore 37.5 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Martin Buchholz
Lecturer: Prof. Dr. Martin Buchholz

[updated 10.09.2018]
Learning outcomes:
After successfully completing this course, students will be able to select a suitable calculation tool for a given engineering task. - They will know how to use MATLAB and Simulink for solving mathematical problems numerically and simulating systems. - Students will be able to apply MATLAB´s vector- and matrix-based approach to given examples. - They will be able to use MATLAB and Simulink to generate, process and evaluate signals and systems. - Students will be able to process data using MATLAB and Simulink, as well as display and analyze simulation or measurement results. - They will be capable of applying their knowledge to image and audio signal processing. - Students will understand the possibilities of and methods used by LABVIEW for simulation and lab work. - They will have acquired the basic knowledge necessary for taking part in other modules where these engineering tools are applied in a more subject-specific manner.

[updated 08.01.2020]
Module content:
1. MATLAB´s user interface 2. Working interactively with the basic elements and functions in MATLAB 3. Programming in MATLAB: scripts and functions 4. Representing measurement results in 2D and 3D graphics 5. File operations 6. Signal processing with MATLAB 7. Image processing with MATLAB 8. Symbolic math 9. Introduction to Simulink 10. Signal processing with Simulink 11. Introduction to LABVIEW

[updated 08.01.2020]
Teaching methods/Media:
Lecture notes, smartboard, PC with MATLAB and LABVIEW classroom license

[updated 08.01.2020]
Recommended or required reading:
Bode, Helmut: MATLAB-SIMULINK: Analyse dynamischer Systeme, Teubner, 2006, 2. Aufl. Bosl, Angelika: Einführung in MATLAB/Simulink, Hanser, (latest edition) Georgi, Wolfgang; Metin, Ergun: Einführung in LabVIEW, Hanser, (latest edition) Grupp, Frieder: Simulink: Grundlagen und Beispiele, Oldenbourg, 2007, ISBN 978-3-486-580914 Hoffmann, Josef; Quint, Franz: Signalverarbeitung mit Matlab und Simulink: Anwendungsorientierte Simulationen, Oldenbourg, 2007 Kammeyer, Karl-Dirk; Kroschel, Kristian: Digitale Signalverarbeitung Filterung und Spektralanalyse mit MATLAB-Übungen, Springer Vieweg, (latest edition) Werner, Martin: Digitale Signalverarbeitung mit Matlab, Intensivkurs mit 16 Versuchen, Vieweg + Teubner, (latest edition)

[updated 08.01.2020]
 
[Thu Dec 26 16:47:55 CET 2024, CKEY=e3E2307, BKEY=ei, CID=E2307, LANGUAGE=en, DATE=26.12.2024]