Course: Mathematics 4 credits: 4
- Course code
- ELVH17AMATH4
- Name
- Mathematics 4
- Study year
- 2022-2023
- ECTS credits
- 4
- Language
- English
- Coordinator
- J.M. Wilson
- Modes of delivery
-
- Lecture
- Assessments
-
- Mathematics 4 - Written, organised by STAD examinations
Learning outcomes
The student can use partial derivatives to solve problems in error analysis and optimisation
The student can solve a linear system of equations using row operations and matrix inversion, including finding approximate solutions
The student can use homogeneous coordinates to perform combined affine transformations of vectors
The student can analyse a dynamical system using determinants to find eigenvalues and eigenvectors
The student can fit a low degree polynomial to data using the normal equations, thus finding a least squares solution.
The student can apply the singular value decomposition to a collection of vector valued data points to find the subspace containing most of the variance.
The student can solve a linear system of equations using row operations and matrix inversion, including finding approximate solutions
The student can use homogeneous coordinates to perform combined affine transformations of vectors
The student can analyse a dynamical system using determinants to find eigenvalues and eigenvectors
The student can fit a low degree polynomial to data using the normal equations, thus finding a least squares solution.
The student can apply the singular value decomposition to a collection of vector valued data points to find the subspace containing most of the variance.
Content
This course presents linear algebra and partial derivatives including some applications important to sensor engineers.
Included in programme(s)
School(s)
- Institute of Engineering