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
βStudentsβ | Bachelor of Computer Science (part 3) |
βPeriodβ | 1st term 2020-2021 |
βContact hoursβ | Wednesday 13:45-18:00, room M.G.010 |
βTutorβ | prof. dr. Annie Cuyt |
Time schedule
β23 Septemberβ | Introduction |
β30 Septemberβ | Floats (theory) |
β7 Octoberβ | Floats (practicum) |
β14 Octoberβ | Interpolation (theory) Handing in practicum floatsβ |
β21 Octoberβ | LU-decomposition (theory) Interpolation (practicum) Floats (presentation) |
β28 Octoberβ | LU-decomposition (practicum) Handing in practicum interpolationβ |
β4 Novemberβ | Interpolation (presentation) Handing in practicum LU-decompositionβ |
β11 Novemberβ | Least-squares (theory) |
β18 Novemberβ | βQuadrature and random numbers (theory) Least-squares (practicum) LU-decomposition (presentation) |
β25 Novemberβ | Quadrature and random numbers (practicum) Handing in practicum least-squaresβ |
β2 Decemberβ | Least-squares (presentation) Handing in practicum quadrature and random numbersβ |
β9 Decemberβ | Quadrature and random numbers (presentation) |