Applications of Renewal Theory
Course: Applied Mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Applications of Renewal Theory
        
    
            Code
        
        
            ДВС.3.04
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2024/2025
        
    
            Semester/trimester when the component is delivered
        
        
            7 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            PLO21.3. Understand the fundamental areas of mathematics and computer science, to the extent necessary for learning mathematical disciplines, applied disciplines and using their methods in a chosen profession.
PLO22.3. Understand the main areas of mathematical logic, theory of algorithms and computational theory, programming theory, probability theory and mathematical statistics.
PLO23.3. Be able to use professional knowledge, skills and abilities in the field of fundamental sections of mathematics and computer science for research of real processes of different nature.
PLO24.3. Be able to independently analyze the relevant subject area, be able to develop mathematical and structural algorithmic models.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            To successfully learn the discipline “Applications of Renewal Theory” the student should satisfy the following requirements. 
They know (a) fundamentals  of mathematical methods for construction, verification and investigation of qualitative characteristics of deterministic and stochastic mathematical models; (b) classical methods of Calculus and Probability Theory.
They can (a) investigate qualitative characteristics of available mathematical models; (b) apply classical methods for solving applied problems in deterministic and stochastic models.
They should be able to (a) apply classical methods of Calculus and Probability Theory; (b) seek information in open sources and properly analyze it. 
        
    
            Course content
        
        
            The course “Applications of Renewal Theory” is aimed at applying results of Renewal Theory, learned by the student when attending the course “Advanced course of Analysis and Probability Theory. Block 1: Elements of Renewal Theory”, to renewal reward processes, renewal equations, regenerative processes, random walks with barrier, perturbed random walks and the Bernoulli sieve. The present course is a natural continuation of the disciplines “Calculus”, “Probability Theory” and “Advanced course of Analysis and Probability Theory. Block 1: Elements of Renewal Theory”.   
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Iksanov O.M. Elements of renewal theory, with applications: Electronic lecture notes. -2023.-122 p. https://do.csc.knu.ua/wp-content/uploads/2023/09/LN_renewal.pdf
2.Iksanov A. Renewal theory for perturbed random walks and similar processes. Cham: Birkhauser, 2016.-250 p. 
3. Mitov K.V., Omey E. Renewal processes. Cham: Springer, 2014. -122 p. 
4.Gut A. Stopped random walks: Limit theorems and applications. 2nd edition. New York: Springer-Verlag, 2009.—263 p.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, consultations, test works, independent work. 
        
    
            Assessment methods and criteria
        
        
            Assessment during the semester:
The maximal number of available points is 100.
Test work no. 1: 30/18 points.
Test work no. 2: 30/18 points.
Test work no. 3: 40/24 points. 
A student is eligible to do over a test work once. The points given are then reduced to at most 80% of the original points.  
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Alexander
                    M.
                    Iksanov
                
                
                    Operations Research  
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Operations Research 
                    
                    
                        Faculty of Computer Science and Cybernetics