Stochastic Systems

Lecturer:

Ivan Nagy (gar.)

Tutor:

Ivan Nagy (gar.)

Supervisor:

Department of Applied Mathematics

Synopsis:

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.

Requirements:

Matrix algebra, basics of differential and integral calculus, probability, modeling of processes, basics of systém theory.

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

To introduce the students into the theory of Bayesian decision making and its application to simple practical problems from the area of transportation. After finishing the course, students should be able to construct a model for a simple application and based on it to design an algorithm for prediction or control.

Study materials:

Nagy Ivan, Základy bayesovského odhadování a řízení, Vydavatelství ČVUT, Praha, 2003

Kárný Miroslav, Böhm Josef, Guy Tatiana Valentine, Jirsa Ladislav, Nagy Ivan, Nedoma Petr, Tesař Ludvík: Optimized Bayesian Dynamic Advising: Theory and Algorithms, Springer, (London 2005)

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:

• ME nav.komb. 11/12 (compulsory course)
• BI nav.prez. 11/12 (compulsory course)
• DS nav.prez. 11/12 (compulsory course)
• ID nav.prez. 11/12 (compulsory course)
• ME nav.prez. 11/12 (compulsory course)
• PL nav.prez. 11/12 (compulsory course)