Graduate course on Recursive identification, spring 2001
 

Description Recursive identification, also known as adaptive filtering, concerns methodologies how to adaptively update, often in real-time, mathematical models of dynamic systems. It is natural to view it is a subfield of learning systems. It has wide applications, perhaps particularly so in control systems and signal processing.

Contents Introduction. Different approaches to recursive identification. Tracking time-varying systems. A general framework for models and identification methods. Analysis of properties for time-invariant systems. User choices of algorithms. Implemenation aspects. Algorithmic details. Analysis of tracking time-varying systems.

Prerequisites The course should be of interest for graduate students in automatic control, signal processing, systems theory, mathematical statistics, etc. The participants are assumed to have a basic knowledge of system identification using parametric methods, or parameter estimation for dynamic models, or time-series analysis.

Structure The graduate course will be given during period 4, spring semester 2001. There will be one or two four hour session(s) basically each week. Each session will comprise a 2 hour lecture (partly of survey character), and a 2 hour part where the participants will demonstrate solutions to the homework assignments.

Venue The sessions will take place in room 105,  house 8, Polacksbacken, Uppsala.

Examination The participants will be given a set of problems/homework assignments to be solved and demonstrated during the course. There will also be a final take-home exam. The course will give 7 units in the graduate program.