Adaptive filtering and change detection 2005


Undergraduate courses in mathematical statistics, linear algebra, calculus, filter theory, automatic control, stochastic processes and signal processing.


The course starts in mid January 2005 and continues for approximately 14 weeks. The course will be coordinated with a similar course at KTH/UU. The periodicity is every two years.


To be decided, but probably 6 credits. 3 credits (orientation course) or 6 credits (advanced course). 2 more credits to the advanced course for mini-projects.


The goal is to get an understanding for the theory of model based filtering and change detection, with particular attention to applications. The course is divided into three parts: signal, parameter and state estimation. The tools and algorithms are very similar for these parts, but the applications and engineering disciplines in which this theory is commonly described in are quite different. The course consists of 10 lectures.

There is one possibilty to follow the course as an orientation. This shortcut covers adaptive filters and Kalman filters, and it includes all the lectures, Chapters 1,3,5,8 (also 2 and 4, but not in detail) and the introductory basics sections in chapters 6,7,9,10,11 of the compendium.

To the advanced course, there is a possiblity to do application oriented mini-projects, which gives another 2 credit points.

Besides the lectures, the participants organize classes themselves for the exercises. Solutions from earlier years students are available.