MATH-656 / 3 crédits

Enseignant(s): Drmac Zlatko, Kressner Daniel

Langue: Anglais


Only this year


The Dynamic Mode Decomposition (DMD) has become a tool of trade in computational data driven analysis of complex dynamical systems. The DMD is deeply connected with the Koopman spectral analysis of nonlinear dynamical systems. This course will present recent results in this area.



The lectures will take place during the first 4 weeks (March  4 - March 28), with 4 hours of lectures / week.
The work on the (mini)projects will be carried out from end of March until end of April.


dynamical systems, data driven analysis, model reduction, numerical linear algebra

Learning Prerequisites

Required courses

It is recommended that the participants have basic background in numerical analysis and dynamical systems. Programming skills (Matlab, Python or similar) are also required.

Learning Outcomes

By the end of the course, the student must be able to:

  • Identify and understand the state-of-the-art in data driven analysis
  • Apply DMD / Koopman operator analysis to complex dynamical systems



Lecture material and references will posted online in due time

Moodle Link

Dans les plans d'études

  • Forme de l'examen: Rapport de TP (session libre)
  • Matière examinée: Numerical linear algebra for Koopman and DMD
  • Cours: 16 Heure(s)
  • Projet: 52 Heure(s)

Semaine de référence