Stochastic Systems

Lecturer:

Ivan Nagy (gar.)

Tutor:

Ivan Nagy (gar.)

Supervisor:

Department of Applied Mathematics

Synopsis:

Basic knowledge in the field of stochastic processes - description of stochastic processes, their estimation and use for prediction. Ability to apply the theory on transportation problems.

Requirements:

Basic technical university level of Probability and Mathematical Statistics; at least passive knowledege of differential and difference calculus. Elementary knowledge of programming in arbitrary language.

Syllabus of lectures:

Mathematical modelling of dynamical systems, estimation of these models and their utilization for prediction. Illustration on practical transportation tasks. The mathematical theory bases on the subjects of Probability and Mathematical Statistics and uses the methods of Bayesian probabilistic approach. This subject is closely connected with the subject Theory of Transportation.

Syllabus of tutorials:

Study Objective:

Study materials:

J. Anděl: Matematická statistika, SNTL, 1978, Prague.

M. Loeve: Probability Theory, van Nostrand, 1962, Princeton, New Jersey.

I. Nagy: Základy bayesovského odhadování a řízení, publisher CTU, 2003, Prague.

V. Peterka: Bayesian approach to system identification, Oxford, P. Eykhoff ed., Pergamon Press., 1981

Note:

Time-table for winter semester 2011/2012:

Time-table is not available yet

Time-table for summer semester 2011/2012:

Time-table is not available yet

The course is a part of the following study plans: