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Numerical Analysis of Eigenproblems and Optimisation


At the end of this module, the student will have understood and be able to explain (main concepts) :
Eigenproblems :
- Some A= QR factorisation techniques, and Singular Value Decomposition (SVD)
- Different eigenproblems and their conditioning,
- Different methods for eigenvalue problems: power method, orthogonal iterations,
QR method and Krylov subspace methods.
The student will be able to :
Eigenproblems :
Understand the difficulties of a problem, and choose a method.

Needed prerequisite

- Precedent courses on the following subjects : linear algebra, numerical analysis.

Form of assessment

The evaluation of outcome prior learning is made as a continuous training during the semester. According ot the teaching, the assessment will be different: as a written exam, an oral exam, a record, a written report, peers review...