Illustration of optimal filtering for navigation

Welcome to the course FEM3200 Optimal Filtering, 10 credits!

This course gives thorough knowledge of sequential methods for estimation, where streaming data is processed, sample by sample, using a Bayesian approach. The main focus in the course is on optimal linear estimation, Kalman and Wiener filtering, which are systematic methods to solve estimation problems with applications in several technical disciplines, for example in telecommunications, automatic control and signal processing but also in other disciplines, such as econometrics and statistics. The course also provides an introduction to other forms of sequential Bayesian filtering for general non-linear and non-Gaussian systems. The course assumes familiarity with basic concepts from matrix theory, stochastic processes, and linear systems theory.

Lectures will be held at place at Malvinas väg 10, floor 7, "Harry Nyquist" (with one exception).

The first lecture is Wednesday August 31, at 08:15. Please send an email to Mats Bengtsson, if you want to follow the course.

Course content

Please see the course syllabus.

Information and assignments

You will find published information about the course, and published course content, in Modules. There, you will also find the weekly homework assignments and peer grading assignments.

Grades

You can find your grades on submitted assignments under Grades.

Communication and groups

You can find all announcements posted via Announcements.

You are highly encouraged to ask questions and interact with both teacher and fellow students through Discussions.

Contact information

Mats Bengtsson matben@kth.se