Institute of Information Theory and Automation

Statistical methods for estimation of uncertain systems

Lecturer: Doc. Ing. Václav Šmídl, Ph.D.
Faculty: Fakulta elektrotechnická ZČU
Type of course: doktorandský
Department: AS
Semester: oba
Active: yes


The aim of this subject is to teach theory and application of statistical tools that can be used to estimate systems with unknown parameters, unknown state of structure. The basic model to study is linear regression, which is the basis of the least squares method, however it can be used to model more advanced tasks such as structure estimation. Further topics of the subject are: (i) elicitation of unknown model from the measured data, (ii) Monte Carlo methods, and (iii) methods of recursive state estimation, for example application of Bayesian filtering in electrical engineering and communications.
Responsible for information: AS
Last modification: 02.02.2015
Institute of Information Theory and Automation