PřF:M8PNM2 Advanced numerical methods II - Course Information
M8PNM2 Advanced numerical methods II
Faculty of ScienceSpring 2023
- Extent and Intensity
- 2/2/0. 4 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (lecturer)
Mgr. Jiří Zelinka, Dr. (lecturer)
RNDr. Bc. Iveta Selingerová, Ph.D. (assistant) - Guaranteed by
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Wed 12:00–13:50 M4,01024
- Timetable of Seminar Groups:
- Prerequisites
- M7PNM1 Advanced numerical methods I
Basic numerical methods of mathematical analysis and linear algebra, basis of functional analysis - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Statistics and Data Analysis (programme PřF, N-MA)
- Course objectives
- The course gives a survey of methods for numerical solving
of differential equations (ordinary and partial).
(1) Students will acquire the most important methods for solving initial-value and boundary-value problems for ordinary differential equations and for solving the basic partial differential equations.
(2) At the end of this course, students will be able to compare the methods not only from the theoretical point of view, but they will understand them from the point of stability, efficiency, etc.
(3) can apply some methods. - Learning outcomes
- Student will be able to:
- design a suitable method for the numerical solution of the differential equation
- Implement the method using proprietary software - Syllabus
- 1. Introduction to nmerical solving of ODE: The solvability of differential equations, approximate solutions, error, stability.
- 2. One-step methods: Euler method, Taylor series method, Runge-Kutta methods
- 3. Multistep methods: Adams methods, predictor-corrector
- 4. Shooting method for solving boundary problems
- 5. Variational methods for ordinary and partial differential equations: Ritz method, Galerkin method.
- 6. Differences methods for ordinary and partial differential equations
- Literature
- REKTORYS, Karel. Variační metody : v inženýrských problémech a v problémech matematické fyziky. Vyd. 6., opr. české 2. Praha: Academia, 1999, 602 s. ISBN 8020007148. info
- VITÁSEK, Emil. Základy teorie numerických metod pro řešení diferenciálních rovnic. 1. vyd. Praha: Academia, 1994, 409 s. ISBN 8020002812. info
- BABUŠKA, Ivo and Milan PRÁGER. Numerické řešení diferanciálních rovnic (Numerical solution of differential equations). 1st ed. Praha: Státní nakladatelství technické literatury, 1964, 238 pp. info
- RALSTON, Anthony. Základy numerické matematiky. 1. české vyd. Praha: Academia, 1973, 635 s. URL info
- Teaching methods
- Lectures, class exercises
- Assessment methods
- Oral examination with preparation.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/spring2023/M8PNM2