Computer methods of applied analysis 2

Mathematics BSc
Course description
2013.

Eötvös Loránd University
Faculty of Science
Institute of Mathematics

Borromean Rings

All courses
Core courses
- Algebra, number theory
- Analysis
- Geometry
  - Geometry 1
- Discrete mathematics
  - Discrete mathematics 1
  - Discrete mathematics 2
- Elementary mathematics
  - Elementary mathematics 1
- Informatics
  - Prog. fundamentals
Pure mathematics
- Algebra, number theory
- Analysis
  - Analysis 3
  - Analysis 4
  - Applied analysis
    - Numerical analysis
    - Appl. anal. comp.
  - Differential equations
    - Differential equations
    - Partial diff. equations
  - Topology
    - Introduction
    - Algebraic topology
  - Complex analysis
  - Functional analysis
  - Function series
- Geometry
- Operations research
  - Operations research 1
  - Operations research 2
- Probability theory
- Informatics
- Computer science
- Foundations of math.
  - Set theory
  - Mathematical logic
Applied mathematics
- Analysis
  - Analysis 3
  - Analysis 4
  - Analysis 5
  - Applied analysis
  - Differential equations
    - Differential equations
    - Partial diff. equations
  - Complex analysis
  - Functional analysis
- Geometry
- Operations research
  - Operations research 1
  - Operations research 2
- Probability theory
- Applied modules
- Informatics
- Algorithms
- Algebra
- Elementary mathematics
  - Elementary mathematics 2
  - Elementary mathematics 3
- Foundations of math.
BSc: general information
Studies

Computer methods of applied analysis 2

Hours lect+pc	Credits lect+pc	Assessment	Specialization	Course code lect/pc	Semester	Status
0 + 1	0 + 2	term grade	applied math.	mm1c2as5a	5	optional

Course coordinator

Ágnes Havasi
Department of Applied Analysis and Computational Mathematics
Institute of Mathematics

Strong	Weak	Prerequisites
Practice class
		Strong: Computer methods of applied analysis1P-a (mm1c2as4a)
		Weak: Numerical analysis2P-a (mm1c2na5a)

Remarks

Form of instruction: The classes are held in a computer laboratory.

Syllabus designed by:

Tamás Kurics, Department of Applied Analysis and Computational Mathematics, Institute of Mathematics.

Prerequisites

Linear algebra, ordinary differential equations.

Course objectives

Applications of the MATLAB package. Writing codes and using toolboxes.

Literature

J. D. Faires, R. Burden: Numerical Methods. Cengage Learning, 2013.

Syllabus

Systems of linear equations.
Matrix decompositions (LU, Cholesky, QR).
Iterative methods for linear systems.
Ordinary differential equations, initial value problems. Runge-Kutta methods. Stability.
One-dimensional boundary value problems, finite difference and finite element methods.