| Detailed information |
| Original study plan |
Bachelor's programme Computer Science 2022W |
| Objectives |
Students know and 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, correlation).
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| Subject |
- Characterization of signals
- Spectral representation of analog signals
- Sampling and reconstruction, Sampling theorem
- Spectral representation of discrete time signals (discrete time Fourier transform, DFT, FFT and applications)
- Discrete time systems
- Design of digital filters (FIR, IIR)
- Correlation and applications
- Time-Frequency-Analysis
- Further topics in signal processing
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| Criteria for evaluation |
Written exam
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| Methods |
Lecture using slides and blackboard, Matlab based presentations
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| Language |
German |
| Study material |
PDF versions of the slides used in the lecture will be made available via Moodle (weekly).
Recommended reading:
- 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 |
(*)INBIPVOCAR2: VO Computer Architecture 2 (3 ECTS) bzw. INBIPVOARC2: VO Rechnerarchitektur 2 (3 ECTS) bzw. INBVCVOPARR: VO Parallele Rechner (3 ECTS)
bzw. INMAWKVDSVA: KV Digitale Sprachverarbeitung (3 ECTS)
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