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:

Further information about the labs is available on Lisam under course TSRT78.

Lectures

Examiner and lecturer is Fredrik Gustafsson,
E-mail: fredrik.gustafsson_at_liu.se.

Lecture Contents Chapter PDF
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  
5 Signal models 5  
6 Estimating signal models 6  
7 Wiener filter 7 + appendix  
8 Wiener filter continued, Kalman filter introduction 7-8  
9 Kalman filter, derivation 8  
10 Kalman filter, properties and applications 8  
11 Adaptive signal processing 9  
12 Design of adaptive algorithms 9  
13 Summary    
14 Guest lectures    

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 -
02 DFT (C) 2.3bc, 2.5, 2.10, 2.22b 2.4, 2.6, 2.8, 2.20b -
03 Spectrum/Filtering (C) 2.25, 3.2, 4.16, 4.18 3.1, 4.19, 4.21, 4.22 -
04 Signal Models 5.3, 5.9, 5.11, 5.12 6.11, 6.15 -
05 Signal Models (C) 6.5, 6.18, 6.7 6.4, 6.6, 6.13, 6.17 -
06 Weiner Filter 7.2, 7.7 7.5, 7.6 -
07 Weiner filter and Kalman filter 8.1, 8.6, 8.11 8.2, 8.9, 8.13 -
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 9.4, 9.6, 9.7 9.8, 9.9 -
11 Adaptive filtering 9.12a, 9.13, 9.10 9.2 -

Course material

The course material consists of,

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.