Digital Signal Processing
| Lecturer (assistant) | |
|---|---|
| Number | 0000003879 |
| Type | lecture with integrated exercises |
| Duration | 4 SWS |
| Term | Sommersemester 2026 |
| Language of instruction | English |
| Position within curricula | See TUMonline |
| Dates | See TUMonline |
- 08.07.2026 09:45-11:15 Theresianum, 0606, Hörsaal ansteigend, ohne exp. B
- 09.07.2026 09:45-11:15 N 1090 ZG, Hörsaal mit exp. Bühne
- 15.07.2026 09:45-11:15 Theresianum, 0606, Hörsaal ansteigend, ohne exp. B
- 16.07.2026 09:45-11:15 N 1090 ZG, Hörsaal mit exp. Bühne
Admission information
Description
Differences and similarities between one-dimensional and multidimensional DSP, two-dimensional signals and systems, sampling of spatio-temporal signals, two- and multi-dimensional filters, linear block transforms, filterbank transforms, lifting implementation, geometric wavelets, inverse problems for multi-dimensional signals, selected applications of DSP in media processing.
Prerequisites
Linear algebra, signals and systems, stochastic signals
The following modules should be passed before taking the course:
- EI00330 Signaltheorie
- EI00340 Stochastische Signale- EI00440 Nachrichtentechnik
Some programming experience in Matlab is highly recommended. For participants with no or very little Matlab experience, significant additional effort at the beginning of the semester will be required.
The following modules should be passed before taking the course:
- EI00330 Signaltheorie
- EI00340 Stochastische Signale- EI00440 Nachrichtentechnik
Some programming experience in Matlab is highly recommended. For participants with no or very little Matlab experience, significant additional effort at the beginning of the semester will be required.
Teaching and learning methods
Learning method:
In addition to the individual methods of the students consolidated knowledge is aspired by repeated lessons in exercises and tutorials.
Teaching method:
During the lectures students are instructed in a teacher-centered style. The exercises are held in a student-centered way. Additionally, selected concepts are implemented using Matlab
Medienform:
The following kinds of media are used:
- Presentations
- Lecture notes
- Exercises with solutions
- Live Matlab demos
- Interactive Matlab lab sessions
In addition to the individual methods of the students consolidated knowledge is aspired by repeated lessons in exercises and tutorials.
Teaching method:
During the lectures students are instructed in a teacher-centered style. The exercises are held in a student-centered way. Additionally, selected concepts are implemented using Matlab
Medienform:
The following kinds of media are used:
- Presentations
- Lecture notes
- Exercises with solutions
- Live Matlab demos
- Interactive Matlab lab sessions