Methods of solving inverse problems

Course: Applied Mathematics

Structural unit: Faculty of Computer Science and Cybernetics

Title
Methods of solving inverse problems
Code
ДВС.1.07
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
8 Semester
Number of ECTS credits allocated
6
Learning outcomes
LO 10. To know the methods of choosing rational methods and algorithms for solving mathematical problems of optimization, operations research, optimal management and decision-making, data analysis. PLO 21.1. To know the main sections of applied mathematics and informatics, to the extent necessary for mastering general professional mathematical disciplines, applied disciplines and the use of their methods in the chosen profession.
Form of study
Full-time form
Prerequisites and co-requisites
1. Successful completion of the course: mathematical analysis, functional analysis, linear algebra. 2. Know: basic concepts and facts of mathematical analysis, functional analysis and linear algebra. 3. Be able to: solve typical problems in mathematical analysis, functional analysis and linear algebra. 4. Have basic skills of searching for information on the Internet.
Course content
Part 1. Linear problems. 1 Topic 1. Correctness according to Hadamard. 2 Topic 2. Incorrect problems. Examples. Correctness according to Tikhonov. 3 Topic 3. Normal solvability of operator equations. 4 Topic 4. Quasi solutions. 5 Topic 5. Tikhonov's regularization method. 6 Topic 6. Moore-Penrose pseudo-inverse operator. 7 Topic 7. Direct-dual method. 8 Topic 8. Quasi-inversion method for heat conduction equation with inverse time. Part 2. Nonlinear problems 10 Topic 9. Incorrect optimization problems. 11 Topic 10. Two-level optimization problems. 12 Topic 11. The Tikhonov regularization method for optimization problems. 13 Topic 12. Bakushinsky's iterative regularization method. 14 Topic 13. Browder-Tikhonov scheme. 15 Topic 14. The direct dual method of Shambol-Pock. 16 Topic 15. Theorems about typicality.
Recommended or required reading and other learning resources/tools
1. Bauschke H.H., Combettes P.L. Convex Analysis and Monotone Operator Theory in Hilbert Spaces. – Springer, 2011. 2. Kinderlerer D., Stampakk-ia G. Vvedenie v variatsionnye neravenstva i ikh prilozheniia. – Moskva: Mir, 1983. 3. Gaevskii Kh., Greger K., Zakharias K. Nelineinye operatornye uravneniia i operatornye differentsial-nye uravneniia. – M.: Mir, 1978. 4. Sea Zh. Optimizatsiia. Teoriia i algoritmy. – M.: Mir, 1973. 5. Tikhonov A.N., Arsenin V.Ia. Metody resheniia nekorrektnykh zadach. – M.: Nauka, 1979. 6. Bakushinskii A. B., Goncharskii A. V. Nekorrektnye zadachi. Chislennye metody i prilozheniia. – Moskva: Izd-vo MGU, 1989.
Planned learning activities and teaching methods
Lectures, independent work
Assessment methods and criteria
The maximum number of points that can be obtained by a student: 100/60 points. - semester assessment: 1. Control work 1: RN 1.1., RN 1.2, RN1.3, RN 2.1, RN3.1 – 30 points/18 points. 2. Control work 2: RN 1.1., RN 1.2, RN1.3, RN 2.1, RN3.1 – 30 points/18 points. - final evaluation (in the form of an exam): - the maximum number of points that can be obtained by a student: 40 points; - learning outcomes that will be evaluated: PH1.1, PH1.2, PH1.3, PH2.1; - form of implementation and types of tasks: written. Types of tasks: 4 written tasks.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline