Number of hours
- Lectures 30.0
- Projects -
- Tutorials 30.0
- Internship -
- Laboratory works -
ECTS
ECTS 5.0
Goal(s)
Understand the concept of spectral representation of a signal and master the associated mathematical framework. Identify typical situations in engineering science where this representation is essential.
Understand the fundamental mathematical concepts for modeling and analyzing random phenomena. Be able to implement a suitable statistical model and infer model parameters from statistical data. Understand the challenges of this modeling: decision support, risk quantification, data science/AI.
Responsible(s)
Antoine VEZIER
Content(s)
• Fourier Analysis (Lebesgue Integral, Hilbert Space, Fourier Series, Fourier and Laplace Transforms)
• Probability and Statistics (Random Variables, Convergence of Random Variable Sequences, Central Limit Theorem, Law of Large Numbers, Parametric Estimation, Linear Regression)
Test
Continuous assessment : 2 ongoing assessment during the tutorial sessions
Calendar
The course exists in the following branches:
- Curriculum - Year 1 Engineering Bachelor Degree - Semester 5
Additional Information
Course ID : 3EUS1MAT
Course language(s): 
You can find this course among all other courses.
Bibliography
Daniel Li, Intégration et applications, Cours et exercices corrigés, Editions Ellipses, 2016.
Bernard Candelpergher, Théorie des probabilités, Edition Calvage et Mounet, 2013
Cours et exercices corrigés de statistiques inférentielles, Editions Ellipes, 2024
French State controlled diploma conferring a Master's degree
