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) |