Inhalt
[ 521HARDDSVU13 ] UE Digital signal processing
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Es ist eine neuere Version 2022W dieser LV im Curriculum Bachelor's programme Computer Science 2022W vorhanden. |
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(*) Unfortunately this information is not available in english. |
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Workload |
Education level |
Study areas |
Responsible person |
Hours per week |
Coordinating university |
1,5 ECTS |
B3 - Bachelor's programme 3. year |
Computer Science |
Mario Huemer |
1 hpw |
Johannes Kepler University Linz |
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Detailed information |
Original study plan |
Bachelor's programme Computer Science 2021S |
Objectives |
Students understand the basic mathematical methods for describing analog and discrete time signals as well as linear, time-invariant systems. Students are able to design digital filters with the help of (e.g. Matlab based) design tools. They are able to program and apply the basic digital signal processing algorithms (e.g. FFT, convolution, FIR and IIR filtering).
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Subject |
The exercise course aims to deepen the understanding of the material presented in the corresponding lecture.
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Criteria for evaluation |
Assessment of bi-weekly analytic and Matlab-programming exercises.
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Methods |
The contents of the lecture is deepened by examples and Matlab-simulations. By working on bi-weekly analytic examples and Matlab-programming assignments, which are discussed after submission, students acquire the skills to program and apply the basic digital signal processing algorithms (e.g. FFT, convolution, FIR and IIR filtering).
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Language |
German |
Study material |
Lecture slides
Daniel von Grünigen, Digitale Signalverarbeitung, 4. Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag, 2008.
Ken Steiglitz, A Digital Signal Processing Primer, Addison-Wesley Publishing Company, 1995.
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Changing subject? |
No |
Further information |
https://www.jku.at/en/institute-of-signal-processing/teaching/course-description/
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Corresponding lecture |
(*)INBIPUECAR2: UE Computer Architecture 2 (1,5 ECTS) bzw. INBIPUEARC2: UE Rechnerarchitektur 2 (1,5 ECTS) bzw. INBVCUEPARR: UE Parallele Rechner (1,5 ECTS)
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On-site course |
Maximum number of participants |
35 |
Assignment procedure |
Direct assignment |
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