PřF:M5180 Numerical Methods II - Course Information
M5180 Numerical Methods II
Faculty of ScienceAutumn 2019
- Extent and Intensity
- 2/1/0. 3 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Bc. Iveta Selingerová, Ph.D. (lecturer)
- Guaranteed by
- doc. Mgr. Jan Koláček, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Wed 8:00–9:50 M4,01024
- Timetable of Seminar Groups:
- Prerequisites
- M4180 Numerical methods I || ( FI:M028 Numerical Methods I )
Differential and integral calculus of one and more variables. Basic knowledge of linear algebra. - 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
- Applied Informatics (programme FI, B-AP)
- Applied Informatics (programme FI, N-AP)
- Applied Mathematics for Multi-Branches Study (programme PřF, B-MA)
- Financial and Insurance Mathematics (programme PřF, B-MA)
- Mathematics (programme PřF, B-MA)
- Statistics and Data Analysis (programme PřF, B-MA)
- Course objectives
- This course together with the course Numerical methods I provides systematic explanation of numerical mathematics as the special scientific discipline. In addition to the classical methods the modern procedures suitable for algorithmization and computer implementation are also presented. During the course, a student is acquainted with advantages and disadvantages of the methods.
- Learning outcomes
- At the end of the course, the student will be able to: define numerical algorithms for interpolation, differentiation, and integration; explain advantages and disadvantages of the mentioned numerical methods; use the numerical methods for solving practical problems.
- Syllabus
- Interpolation-Lagrange interpolation polynomial, Newton interpolation polynomial, the error of the polynomial interpolation,iterated inter- polation, Hermite interpolation polynomial, cubic spline interpolation, general interpolation process
- Numerical differentiation-formulas based on a derivative of an interpolation polynomial, Richardson extrapolation
- Numerical integration-quadrature formulas, degree of exactness and error, Gaussian quadratures, Lobatto quadrature, Newton-Cotes quadratures composite quadratures, integrals with singularities, adaptive quadratures
- Literature
- HOROVA, Ivana and Jiří ZELINKA. Numerické metody (Numerical Methods). 2nd ed. Brno: Masarykova univerzita v Brně, 2004, 294 pp. 3871/Př-2/04-17/31. ISBN 80-210-3317-7. info
- MATHEWS, John H. and Kurtis D. FINK. Numerical methods using MATLAB. 4th ed. Upper Saddle River, N.J.: Pearson, 2004, ix, 680. ISBN 0130652482. info
- BURDEN, Richard L. and Douglas J. FAIRES. Numerical analysis. 3rd ed. Boston: PWS Publishing Company, 1985, 676 pp. ISBN 0-87150-857-5. info
- RALSTON, Anthony. Základy numerické matematiky. Translated by Milan Práger - Emil Vitásek. České vyd. 2. Praha: Academia, 1978, 635 s. info
- PŘIKRYL, Petr. Numerické metody matematické analýzy. 1. vyd. Praha: Nakladatelství technické literatury, 1985, 187 s. URL info
- Teaching methods
- Lecture: 2 hours weekly, theoretical preparation.
Class exercise: 1 hour weekly. Excercise is focused on examples for practicing methods presented in the lecture. - Assessment methods
- Lecture. Attendance of a class exercise is compulsory and a successful written test is required for a credit. The exam is written.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
- Enrolment Statistics (Autumn 2019, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2019/M5180