Coursebooks

Numerical analysis

MATH-250

Lecturer(s) :

Kressner Daniel

Language:

English

Summary

Construction and analysis of numerical methods for the solution of problems from linear algebra, integration, approximation, and differentiation.

Content

- Representation of numbers on computers

- Interpolation, numerical integration and differentiation

- Direct and iterative methods for the solution of large systems of equations

- Fourier transform and data compression

 

Keywords

numerical algorithms

numerical linear algebra

 

Learning Prerequisites

Required courses

Analysis I and II

Linear Algebra

Recommended courses

Elements of scientific programming

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Ex cathedra lectures and exercises in the classroom and on the computer

Expected student activities

Attendance of lectures

Doing exercises

Implementing simple programming tools

Solving basic applied mathematics problems

Assessment methods

'Form of examination

17% project or homework. 83% exam.

Resources

Bibliography

Lecture notes accompaying the course will be provided.

Complementary reading:

Ressources en bibliothèque

Prerequisite for

Computational linear algebra

Advanced numerical analysis

Numerical integration of dynamical systems

Other Master courses in numerical analysis and applied mathematics

In the programs

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German