htw saar Piktogramm QR-encoded URL
Back to Main Page Choose Module Version:
emphasize objectives XML-Code

flag



Digital Signal Processing

Module name (EN):
Name of module in study programme. It should be precise and clear.
Digital Signal Processing
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: E2510
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.
P200-0005
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+2P (4 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.
5
Semester: 5
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam

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

E2510 (P200-0005) Electrical Engineering and Information Technology, Bachelor, ASPO 01.10.2018 , semester 5, 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).
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):
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 module, students will be able to carry out digital signal processing and analyze telecommunications signals and systems. They will be familiar with the different structures of discrete time systems and be able to analyze them analytically with the help of the discrete Fourier transform and the Z-transform. They will be capable of specifying and implementing digital, recursive and non-recursive filters based on a defined filter specification. Students will be able to use development tools that simulate algorithms and implement them in an FPGA using a model-based approach. They will be able to describe the design flow for the real-time realization of digital algorithms. Student will independently implement digital filters, signal generators and other digital algorithms in the course of this module.

[updated 08.01.2020]
Module content:
1. Introduction, motivation 2. Basics 3. Ideal and real sampling, sampling theorem, practical aspects of sampling 4. Discrete-time signals and systems 5. Discrete time convolution, FIR and IIR systems 6. Structure of discrete time systems 7. Representation of discrete time signals and systems in the frequency domain 8. The Z-transform 9. Designing recursive digital filters 10. Design of non-recursive digital filters 11. Simulating digital signal processing systems 12. Model-based implementation of digital algorithms in an FPGA Tutorials will be available for each chapter. Parallel to the theoretical part, digital algorithms will be simulated in the PC lab using a suitable software tool and prepared for implementation in an FPGA (Field Programable Gate Array) or DSP (Digital Signal Processor).

[updated 08.01.2020]
Teaching methods/Media:
Lecture notes, beamer, PC lab, EDA simulation tools with classroom licenses

[updated 08.01.2020]
Recommended or required reading:
Brigham, Elbert Oran: FFT Anwendungen, Oldenbourg, 1997 Götz, Hermann: Einführung in die digitale Signalverarbeitung, Teubner, 1998, 3. Aufl. 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) Oppenheim, Alan V.; Schafer, Ronald W.; Buck, John R.: Zeitdiskrete Signalverarbeitung, Oldenbourg, (latest edition) Schmidt, Herrad; Schwabl-Schmidt, Manfred: Digitale Filter: Theorie und Praxis mit AVR-Mikrocontrollern, Springer Vieweg, 2014, ISBN 978-3658035228 Stearns, Samuel D.; Hush Don R.: Digitale Verarbeitung analoger Signale, Oldenbourg, 1999, 7. Aufl. von Grünigen, Daniel Ch.: Digitale Signalverarbeitung, Hanser, (latest edition) Werner, Martin: Digitale Signalverarbeitung mit Matlab, Intensivkurs mit 16 Versuchen, Vieweg + Teubner, (latest edition)

[updated 08.01.2020]
 
[Fri Apr 26 15:25:13 CEST 2024, CKEY=e3E2510, BKEY=ei, CID=E2510, LANGUAGE=en, DATE=26.04.2024]