Scientific programming
This course is a sequel to the course Numerical analysis. We will study several basic numerical techniques, amongst which are:
- polynomial and spline interpolation
- solving a non-linear equation
- systems of linear equations
- least squares problems
- function approximation
- Fourier transformation
- optimization
- Gaussian quadrature
- random number generation
The introduction of a technique will be followed by one or more algorithms. Several mathematical and numerical aspects will be treated, such as: error control, sensitivity and complexity. To illustrate each technique we will look at small academic model problems.
Practical information
Students | Bachelor of Computer Science (part 3) |
Period | 1st term 2020-2021 |
Contact hours | Wednesday 13:45-18:00, room M.G.010 |
Tutor | prof. dr. Annie Cuyt |
Time schedule
23 September | Introduction |
30 September | Floats (theory) |
7 October | Floats (practicum) |
14 October | Interpolation (theory) Handing in practicum floats |
21 October | LU-decomposition (theory) Interpolation (practicum) Floats (presentation) |
28 October | LU-decomposition (practicum) Handing in practicum interpolation |
4 November | Interpolation (presentation) Handing in practicum LU-decomposition |
11 November | Least-squares (theory) |
18 November | Quadrature and random numbers (theory) Least-squares (practicum) LU-decomposition (presentation) |
25 November | Quadrature and random numbers (practicum) Handing in practicum least-squares |
2 December | Least-squares (presentation) Handing in practicum quadrature and random numbers |
9 December | Quadrature and random numbers (presentation) |