Theory of evaluation of systems in conditions of uncertainty
Course: System Analysis
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Theory of evaluation of systems in conditions of uncertainty
        
    
            Code
        
        
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2022/2023
        
    
            Semester/trimester when the component is delivered
        
        
            7 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            Know the basic approaches to solving problems of assessing the characteristics of systems in the presence of uncertainties.
Be able to calculate estimates of system parameters in the presence of uncertainties depending on the amount of a priori information.
Demonstrate skills of interaction with other people, ability to work in teams.
Be able to organize their own activities and get results within a limited time. Demonstrate the ability to self-study and continue professional development.
        
    
            Form of study
        
        
            Distance form
        
    
            Prerequisites and co-requisites
        
        
            Know: probability theory, probability processes and mathematical statistics, data analysis.
Be able to: apply knowledge of probability theory and mathematical statistics, data analysis.
Have basic skills: solve problems in probability theory and mathematical statistics, data analysis.
        
    
            Course content
        
        
            The discipline "Theory of evaluation of systems in conditions of uncertainty" is an integral part of the cycle of professional training of specialists of educational and qualification level "bachelor"; it includes the following sections: Weighted least squares method and its analysis. Markov's assessment and its possibilities. Estimation with a minimum standard error. The method of maximum likelihood. Minimax approach in evaluation theory. Estimates of Bayes and the maximum of the apothecary probability. Estimation of non-stationary system parameters. Particular attention is paid to gaining experience in the practical use of estimates depending on the amount of a priori information. Discipline is the discipline of free choice of the student.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            5. Ljung L. System Identification: Theory for the User / L. Ljung. - Englewood Cliffs, NJ: Prentice-Hall, 1987.
        
    
            Planned learning activities and teaching methods
        
        
            Lecture, individual work
        
    
            Assessment methods and criteria
        
        
            Test work, exam.
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
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Departments
The following departments are involved in teaching the above discipline