Teaching is done by alternating sequences of short lectures and hands-on practical tutorials in a computer room with the Matlab

^{®}software, largely used in the academic and industrial world.

**Syllabus for 2018-2019.**

The course syllabus is as follow :

- reminder on fundamental Matlab objects: scalars, vectors, matrices. Array (element-wise) operations.

- 2D (reminder) and 3D graphics. Image display.

- Programming basics (revisions and complements)

**Numerical computing fundamentals**[~24h] :

- Rounding error. Method error. Numerical stability of algorithms.

- Square linear system solving. Notion on matrix condition number.

- Least-square sense linear system solving.

- Singular Value Decomposition [SVD], pseudo-inverse and condition number.

- Discrete Fourier Transform and Fast Fourier Transform, 1D (revisions) and 2D.

- Non-linear problem solving (zero finding, numerical quadrature tool use, local and global optimization tool use, ...)

- Ordinary Differential Equation [ODE] solving

- Introduction to Partial Differential Equation [PDE] solving ¿with COMSOL software¿

**Use of Matlab software**[~8h] :

**Requirements :**[PRELIMINARY] General undergraduate knowledge of mathematics: real and complex calculus, linear algebra, Fourier transform and discrete Fourier transform, ordinary differential equations, ... Some basic knowledge of the Matlab software and of numerical computing could be useful but is not mandatory...

**Evaluation mechanism :**Individual final exam

**Last Modification :**Tuesday 9 April 2019