MS1TSS - Theory of Stochastic Systems

Course specification
Course title Theory of Stochastic Systems
Acronym MS1TSS
Study programme Electrical Engineering and Computing
Module Signals and Systems
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
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 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.
    1. Fundamnals of Stochastic Systems and Signals and Estimation Theory, B. Kovacevic, Z. Djurovic, Springer Verlag, 2008. (Original title)
    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 0
    Colloquia 0
    Seminars 0