Algemene informatie
| Vakcode | X_400042 |
|---|---|
| Studiepunten | 6 EC |
| Periode | P4+5 |
| Vakniveau | 100 |
| Onderwijstaal | Engels |
| Faculteit | Faculteit der Bètawetenschappen |
| Vakcoördinator | dr. I. Canakci |
| Examinator | dr. I. Canakci |
| Docenten |
dr. I. Canakci |
|
Onderdeel van opleiding(en)
Bachelor
Premaster
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Praktische informatie
Voor dit vak moet je zelf intekenen. De inteken- en afmeldtermijnen staan op VU.nl
| Onderwijsvorm | Werkcollege, Deeltentamen schriftelijk, Hoorcollege |
|---|
Doelgroepen
Dit vak is ook toegankelijk als:
Dit vak wordt in het Engels aangeboden. Omschrijvingen kunnen daardoor mogelijk alleen in het Engels worden weergegeven.
Doel vak
After successfully completing this course, the student- has a working knowledge of the concepts of matrix algebra
and finite-dimensional linear algebra, such as echelon form,
LU-decomposition, linear independence and determinants;
- is familiar with the general theory of finite-dimensional
vector spaces, in particular with the concepts of basis and dimension;
- is familiar with the concepts of eigenvalues and
eigenvectors, diagonalization and singular value decomposition
and can apply these concepts in basic applications in
discrete time dynamical systems;
- has working knowledge of the concepts of inner product spaces and
matrices acting in inner product spaces, including orthogonal
projections and diagonalization of symmetric matrices.
Inhoud vak
- systems of linear equations- linear (in)dependence
- linear transformations and matrices
- matrix operations
- determinants
- vector spaces and subspaces
- basis and dimension
- rank of a matrix, dimension theorem
- coordinate systems and change of basis
- eigenvalues and eigenvectors
- diagonalization of matrices
- inner product, length and orthogonality
- orthogonal bases and least-squares problems
- diagonalization of symmetric matrices
- singular value decomposition
Aanvullende informatie onderwijsvormen
2 lectures and 1 exercise class per weekToetsvorm
Four small tests (20 percent, only the best three are taken intoaccount), a midterm exam (40 percent) and a final exam (40 percent).
There is a resit. For students taking the resit the final grade is
determined by the maximum of 0.2 times the average of the best
three tests plus 0.8 times the result of the resit, and just the resit.
Literatuur
David C. Lay, Stephen R. Lay and Judi J. McDonald, Linear Algebra andits Applications, 5th edition, Pearson Global Edition, ISBN-13
9781292092232