FI:MA018 Numerical Methods - Course Information
MA018 Numerical Methods
Faculty of InformaticsAutumn 2017
- Extent and Intensity
- 2/2/0. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- Mgr. Jiří Zelinka, Dr. (lecturer)
- Guaranteed by
- prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Thu 8:00–9:50 A320
- Timetable of Seminar Groups:
- Prerequisites
- Differential calculus of functions of one and more variables. Basic knoledge of linear algebra-theory of matrices and solving systems of linear equations.
- 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, N-AP)
- Information Technology Security (eng.) (programme FI, N-IN)
- Information Technology Security (programme FI, N-IN)
- Bioinformatics (programme FI, N-AP)
- Information Systems (programme FI, N-IN)
- Parallel and Distributed Systems (programme FI, N-IN)
- Computer Graphics (programme FI, N-IN)
- Computer Networks and Communication (programme FI, N-IN)
- Computer Systems (programme FI, N-IN)
- Embedded Systems (eng.) (programme FI, N-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (eng.) (programme FI, N-AP)
- Service Science, Management and Engineering (programme FI, N-AP)
- Theoretical Informatics (programme FI, N-IN)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Image Processing (programme FI, N-AP)
- Course objectives
- This course together with the course Numerical Methods II provides complete explanation of numerical mathematics as the separate scientific discipline. The emphasis is given to the algorithmization and computer implementation. Some examples with graphical outputs help to explain even some difficult parts. At the end of course students should be able to apply numerical methods for solving practical problems and use these methods in other disciplines e.g. in statistical methods.
- Syllabus
- 1. Error analysis: absolute and relative error, representation of numbers, error propagation 2. Iterative methods for solving of nonlinear equations: general iterative method, order of the convergence, Newton method and its modifications 3. Direct methods for solving systems of linear equations: methods based on Gaussian elimination, methods for special matrices 4. Iterative methods for solving of systems of linear equations: general construction of iterative methods, Jacobi method, Gauss-Seidel method 5. Solving of systems of nonlinear equations: Newton method 6. Interpolation and approximation: polynomial and piece-wise polynomial interpolation, curve approximations, subdivision schemes, least squares method 7. Numerical differentiation: differentiation schemes 8. Numerical integration: methods based on interpolation, Monte Carlo integration
- Teaching methods
- Lecture: 2 hours weeky, theoretical preparation. Class excercise: 2 hours weekly, Theoretical exercise (1 hour)is focused on solving of problems by methods presented in the lecture, practical exercise (1 hour) in a computer room is aimed at algoritmization and programming of presented numerical methods.
- Assessment methods
- Written exam and work during the semester - 30 points together.
Assessment of the course:
more then 27 points - A
more then 24 points - B
more then 21 points - C
more then 18 points - D
15 points and more - E
less then 15 points - F - Language of instruction
- English
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Autumn 2017, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2017/MA018