Valid from: Autumn 2013
Decided by: FN1/Anders Gustafsson
Date of establishment: 2014-05-13
Division: Numerical Analysis
Course type: Third-cycle course
Teaching language: English
The aim of the course is to teach the student theoretical and algorithmical aspects of modern iterative methods in computational linear algebra. This knowledge is important for all computationally intensive disciplines, e.g. fluid dynamics, image analysis, meteorolgy, automatic control etc. Furthermore, the aim is to confront the student with modern research questions in numerical linear algebra and their interrelation with numerics of partial differential equations in engineering and mathematical sciences.
Knowledge and Understanding
For a passing grade the doctoral student must have demonstrated substantially improved and more useful knowledge of numerical linear algebra than students who only have completed a regular basic course in scientific computing.
Competences and Skills
For a passing grade the doctoral student must
Judgement and Approach
For a passing grade the doctoral student must be able to judge and discuss different numerical methods within linear algebra
The course focuses on iterative methods for large scale, sparse linear problems. These problems occur mostly when discretizing partial differential equations in engineering sciences, physics and mathematics.
Saad, Y.: Iterative Methods for Sparse Linear Systems. SIAM, 2003.
Types of instruction: Seminars, project
Examination formats: Seminars given by participants, miscellaneous.
Talks, numerical experiments
Grading scale: Failed, pass
Assumed prior knowledge: Numerical Analysis courses as required for engineering programs F,Pi,E,D or mathematics/pysics master's program. Programming capabilities in at least one of the languages MATLAB/Python/C/C++/Fortran