Entry requirements

Mathematical Analysis, Algebra DV1, Algorithms and Data Structures DV1 or the equivalent.

Aims

To give knowledge and skills in scientific

computing, linear algebra, and concerning basic

numerical methods for common computational

problems, to use mathematical software, and to

give training in project work, written and oral

presentations.

Content

Linear spaces: linear independence, basis,

dimension. Scalar product and orthogonality.

Euclidean spaces. Matrix computations, matrix

theorems, and classes of matrices. Basic

properties of linear algebraic systems. Column

space, row space and null spaces. Floating point

arithmetic, error propagation, stability,

condition, efficiency. Numerical methods for

linear systems of equations, and nonlinear

equations. Data-fitting with interpolation and

least squares approximation. Projection.

Gram-Schmidt's ON-process and overdetermined

systems of equations. Numerical methods for

integrals and derivatives. Ordinary differential

equations: numerical methods for initial value

problems. Computation of eigenvalues and

eigenvectors. Difference equations and Markov

processes. MATLAB programming. Project work

focussing on scientific computing applications.

Written and oral presentation.

Instruction

Lectures, lessons, laboratory work, seminars and compulsory assignments.

Assessment

Written examination and approved compulsory assignments and project work.