Adaptive Systems


Lecture Course (2.0 VO)

Course Description: This course builds on the fourth semester course Signal Processing and covers adaptive systems in signal processing and control. LMS algorithm and fundamental concepts in adaptive systems: optimality, convergence, stabilty, accuracy, robustness, tracking, data dependence, computational complexity, implementation and finite word-length effects. Control applications: system idenfitification, self-tunning control, model-reference adaptive control. Signal Processing applications: channel equalization and adaptive detection, echo and noise cancellation, predictive coding and spectral estimation. Selected special algorithms and systems: RLS, blind adaptation, lattice filters, nonlinear systems. The course notes as recorded during lecture presentation in the past terms are available for download in the Teachcenter (login required; link below).

Grading: For the lecture course, the exam consists of a written AND an oral part. For the written part, you have to solve three analytical problems within three hours. These past written exams as well as the problems given below (class material and homework assignments) should help you to prepare. Once you have passed the written exam, you have to take the oral exam (in Prof. Kubin's office, usually one or two weeks after the written exam). For the oral exam, you have to answer two questions (whiteboard available). You can choose the first question yourself!

Problem Classes (1.0 UE)

In the problem classes we will investigate adaptive systems by using analytical methods as well as numerical simulations in MATLAB. The problem classes should demonstrate typical problems and applications, the theoretical concepts, and state-of-the-art algorithms. 

In order to bring the necessary MATLAB programming skills, we recommend you to work through the "Getting Started" tutorial (especially the "Manipulating Matrices" section) of the MATLAB-Documentation at 

To pass the problem class you have to deliver 3 homework assignments. For questions and discussion of course-relateed topics, you can use the newsgroup Our assistants Christian Stetco and Alexander Aigner will answer newsgroup postings and be responsible for the correction of your homework.

The problems can be found in the Handout (latest version).

No Date Topic Problem covered
1  14.10. Intro, Least-Squares Filters P1.1, P1.2, P1.3
2  28.10. Auto-/Cross-Correlation, Wiener Filter  P1.4,P1.5
3  11.11 Under-/Overmodeling, System Identification P1.9-10,P1.12,P1.6
4  18.11 Gradient Method P1.7-P1.14,P1.15
5  02.12 Linear Prediction, LMS P1.17,P4.1,P4.2,P4.4, P3.1
6  20.01 Interference Cancellation, Equalization Intro  
7  27.01 Adaptive Equalizatio, DFE, Fractionally Spaced Equalizer (FSE)  


Homework Problem Sets

To pass the problem class you have to prepare 3 homework assignments. For each assignment you should work in groups of 2 students (you may change your partner from assignment to assignment). In total, 100 points can be obtained (33 or 34 per assignment). Solving Bonus Problems brings extra points. 

No. PDF Date Due Date Additional Material
1  PDF 11.11.2016 02.12.2016  
2  PDF 02.12.2016 20.01.2017  CondEntropy.m BGsQuantizer.m
3   PDF 27.01.2017 24.02.2017  



Discussion of general ideas and questions concerning the homework assignments among students is strongly encouraged. However, all groups are expected to work on their final solutions and documentation individually. Sharing (in particular one-to-one copying) of solutions among groups or copying from other sources such as the internet (including parts of program code) will lead to significant point penalties.


How to deliver your homework?

A delayed submission will cost you a penalty of 10 points per day!

The analytical part of the homework (your calculation sheets) as well as the simulation protocol of the MATLAB part have to be delivered as hardcopy to our mailbox at Inffeldgasse 16c / ground floor. You can find a map pointing your way HERE. Use a printed version of the assignment sheets as the title page and fill in your name(s) and matr. number(s). Please make sure that your approaches, procedures and results ara clearly presented.

Additionally, the MATLAB part of the homework (your MATLAB programs and the simulation protocol) has to be submitted via e-mail to the address hw2 dot spsc at tugraz dot at. The subject of the e-mail should be "AssignmentNo MatrNo1 MatrNo2". Please leave the body of the e-Mail empty (nobody will read it). A complete work consists of all MATLAB files (*.m) and a simulation protocol in PDF format. You have to zip (or tar) all these files to one single file with the name AssignmentNo_MatrNo1_MatNo2 (e.g., ""), which has to be attached to the e-mail. 

References/Text Books

  • G. Moschytz and M. Hofbauer: Adaptive Filter, Springer-Verlag, Berlin Heidelberg, 2000. (Good intuitive introduction (German only!u)).
  • Simon Haykin: Adaptive Filter Theory, Fourth Edition, Prentice-Hall, Inc., Upper Saddle River, NJ, 2002. (The definitive book but a huge number of pages)
  • B. Widrow and S. D. Stearns: Adaptive Signal Processing, Prentice-Hall, Inc., Upper Saddle River, NJ, 1985. (From two of the originators of adaptive system theory. A lot of useful information, but many topics are more detailed covered in Moschytz and Hofbauer)
  • J. R. Treichler, C.R. Johnson, and M.G. Larimore: Theory and Design of Adaptive Filters, Prentice-Hall, Inc., Upper Saddle River, NJ, 2001.
  • M. G. Bellanger: Adaptive Digitial Filters, Second Edition, Marcel Dekker, Inc., New York, 2001.

You can use MATLAB at home directly over a terminal server. Instructions can be found here


Contest Winners 2015-2016

Congratulations to Gabriel Hülser and Felix Rothmund as the winning team in adaptive systems contest!



Education Level: 
Master Level
BGsQuantizer.m638 bytes
handout16.pdf205.99 KB
AS_Assignment1_111116.pdf89.62 KB
AS_Assignment2_021216.pdf118.61 KB
CondEntropy.m1.18 KB
AS_Assignment3.pdf190.77 KB
AS_Assignment3.pdf190.84 KB
hw3.zip549.93 KB