Number of hours
- Lectures 18.0
- Projects -
- Tutorials -
- Internship -
- Laboratory works 12.0
- Written tests -
ECTS
ECTS 3.0
Goal(s)
This course is an introduction to data assimilation and inverse methods. Mathematical formulation and algorithms of the major methods are presented, as well as application examples.
Responsible(s)
Arthur VIDARD
Content(s)
1) introduction, notations
2) mathematical tools (statistics, differential calculus, optimization with/without constraints, optimisation algorithms)
3) optimal linear statistical estimation
4) Kalman + particle filtering
5) variational methods
differential calculus, basic proba/stats, matrix theory, optimization, numerical analysis, partial differential equations
Test
- CC = attendance, involvement, homework
- final exam : oral + written report + practicals (TP)
N = exam
rattrapage possible
The exam is given in english only 
Calendar
The course exists in the following branches:
- Curriculum - Master 2 in Applied Mathematics - Semester 9 (this course is given in english only
) - Curriculum - Master 2 in Applied Mathematics - Semester 9 (this course is given in english only )
Additional Information
Course ID : WMM9AM06
Course language(s):
You can find this course among all other courses.
Bibliography
Documents and resources on the course webpage.