13M051TSS - Theory of Stochastic Systems

Course specification
Course title		Theory of Stochastic Systems
Acronym		13M051TSS
Study programme		Electrical Engineering and Computing
Module
Type of study		master academic studies
Lecturer (for classes)		professor PhD Branko Kovačević professor PhD Željko Đurović
Lecturer/Associate (for practice)		professor PhD Predrag Tadić
Lecturer/Associate (for OTC)
ESPB		6.0	Status	elective
Condition		none
The goal		Objective of the course is for the students to be informed about the techniques for modeling and analysis of stochastich processes, theory of parameters and state estimation, as well as elements of stochastic systems control.
The outcome		Learning outcomes of the course for the students to gain the following skills: to analyze and model stochastic processes, to apply different estimation procedures, and to be able to implement various control strategies for stochastic processes.
Contents
Contents of lectures		Definition of stochastic processes, stationarity, ergodicity, white stochastic processes, spectral analysis of stochastic processes; sestem response on stochastic exitation; Introduction to estimation theory; Estimation of deterministic and random parameters; State space estimation algorithms; Wiener-filter, Kalman fitler, Extended Kalman filtering.
Contents of exercises		Students hava obligation to design some of the considered estimators using by programming language MATLAB.
Literature
Fundamnals of Stochastic Systems and Signals and Estimation Theory, B. Kovacevic, Z. Djurovic, Springer Verlag, 2008.
Number of hours per week during the semester/trimester/year
Lectures	Exercises	OTC	Study and Research	Other classes
3	1
Methods of teaching		45 hours of lectures + 15 hours of auditory exercises
Knowledge score (maximum points 100)
Pre obligations		Points	Final exam	Points
Activites during lectures		0	Test paper	0
Practical lessons		50	Oral examination	50
Projects
Colloquia		0
Seminars		0