Digital Signal Processing (TSRT78)
Course Information, 2024HT
Course Description
Welcome to the course page of TSRT78!
Signal processing is about extracting information from sensors and other data generating sources providing a stream of numerical time series data. Available methods are either non-parametric for extracting trends or frequency information in the data, or model-based parametric methods that can gain further insights of the data generation mechanisms.
This course describes the most important methods and algorithms for signal processing, and the course covers basic theory with tools from algebra, complex analysis and statistics to examples of real-world applications.
Topics include: discrete Fourier transform (DFT), signal modelling (both in the frequency and in the time domain), model estimation, spectral estimation, Wiener filtering, Kalman filtering and adaptive filtering.
As a motivation, the wildlife lecture below shows some examples of how the course knowledge can be used to protect wildlife.
Course Structure
This course gives 6hp (of which 1hp are labs). The course structure is as follows:
- Lectures: 14 (including invited speakers from the industry)
- Exercises sessions: 12
- Labs: 2 mandatory labs
- Exam: Exam (4 hours), including both written and computer problems
Further information about the labs is available on Lisam under course TSRT78.
- The use of computers is highly integrated in the course and more than half of the exercises take place in ISY’s computer labs. More information about the computer labs is available here.
- The computer and Matlab are “allowed aids” during the exam. The exam takes place in ISY’s computer labs.
- All students will have personal accounts and in this way have unlimited access to the computer labs also outside the scheduled time. In order to enter the computer labs and Laboteket (where the two labs takes place), you will need your LiU-card.
- Many of the exercise problems require the use of Matlab for solving. Matlab can be downloaded from the student portal.
Lectures
Examiner and lecturer is Fredrik Gustafsson,
E-mail: fredrik.gustafsson_at_liu.se.
| Lecture | Contents | Chapter | |
|---|---|---|---|
| 1 | Introduction, frequency description of signals | 1, 2.1-2.5 | le1.pdf |
| 2 | Frequency description continued, DFT | 2.6-2.6 | le2.pdf |
| 3 | Introducing stochastic signals and spectral estimation | 3 | le3.pdf |
| 4 | Design and use of filters | 4 | le4.pdf |
| 5 | Signal models | 5 | le5.pdf |
| 6 | Estimating signal models | 6 | le6.pdf |
| 7 | Wiener filter | 7 + appendix | le7.pdf |
| 8 | Wiener filter continued, Kalman filter derivation | 7-8 | le8.pdf |
| 9 | Kalman filter, theory | 8 | le9.pdf |
| 10 | Kalman filter, practice | 8 | le10.pdf |
| 11 | Adaptive filtering, theory | 9 | le11.pdf |
| 12 | Adaptive filtering, practice | 9 | le12.pdf |
| 13 | Guest lecture from NIRA Dynamics and Summary | ||
| 14 | Earlier MSc projects and guest lectures from Oticon |
Exercises
Teaching assistant is Daniel Bossér,
E-mail: daniel.bosser_at_liu.se
| Topic | Exercises | Extra Exercises | Notes |
|---|---|---|---|
| 01 DFT | 2.1bc, 2.3a, 2.12, 2.22a | 2.7, 2.15, 2.20a, 3.6 | 1.pdf |
| 02 DFT (C) | 2.3bc, 2.5, 2.10, 2.22b | 2.4, 2.6, 2.8, 2.20b | 2.zip |
| 03 Spectrum/Filtering (C) | 2.25, 3.2, 4.16, 4.18 | 3.1, 4.19, 4.21, 4.22 | 3.pdf |
| 04 Signal Models | 5.3, 5.9, 5.11, 5.12 | 6.11, 6.15 | 4.pdf |
| 05 Signal Models (C) | 6.5, 6.18, 6.7 | 6.4, 6.6, 6.13, 6.17 | 5.pdf |
| 06 Wiener Filter | 7.2, 7.7 | 7.5, 7.6 | 6.pdf |
| 07 Wiener filter and Kalman filter | 8.1, 8.6, 8.11 | 8.2, 8.9, 8.13 | 7.pdf |
| 08 Wiener filter and Kalman filter (C) | 7.8, 8.15 | 7.9, 8.4 | - |
| 09 Kalman filter (C) | 8.3, 8.17 | 8.16, 8.18 | - |
| 10 Adaptive filtering (C) | 9.4, 9.6, 9.12a | 9.8, 9.9 | - |
| 11 Adaptive filtering (C) | 9.7, 9.13, 9.10 | 9.2 | - |
Course material
The course material consists of,
- Gustafsson, F., Ljung, L. and Millnert, M. “Signal Processing”, 2011. A list of errata in the equations is available. The MATLAB functions for the book are available here.
- Gunnarsson, F., Tjärnström, F. and Gustafsson, F. “Signal Processing - Exercises”, 2010. The data files for the exercises can be downloaded here.
- Lab instructions are available here.
The course books are not available at Studentlitteratur anymore. We will 2024 offer the course books printed locally at LiU for free to all registered course attendees. The list of errata for the textbook has been corrected. The two books will be distributed during one of the first lectures.
Mailing list
If you registered for the course you are automatically on the list
tsrt78-ht2024_xs_at_student.liu.se. Information may also be
announced using this list.