4th year: speciality SET
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1) Intelligent distributed systems
Courses
Course 1: Fundamentals and theoretical concepts, Material.
Course 2: Distributed system for robotics, Material.
Practical works
PW 1: 3D calibration of a ultra-sound sensor system, Material
Tutorial: Theoretical study of SLAM algorithm, Material
Project: Visual SLAM, Material
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2) Navigation with sensor systems (CIRI)
Courses
Course (all): Material.
Practical works
PW 1: Study of multivariate Gaussian distribution, Material
PW 2: Kalman filter for a GNSS navigation problem, Material
Project: Radar Target Tracking, Material
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3) Hyperwave guided and unguided propagation
Courses
Course 1: Basics of transmission line theory, Material.
Course 2: Progressive and standing wave, Material.
Course 3: Introduction to unguided wave propagation, Material.
Practical works
TD 1: Transmission line equations, Material.
TD 2: Progressive and standing wave, Material.
PW : Theoretical and numerical study of channel equalization
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4) Model-based engineering
Courses
Course 1: Introduction to complex systems, Material.
Course 2: Complex system and object-oriented programming, Material.
Practical works
PW 1, Material, Correction
PW 2, Material.
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5th year : speciality SET
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1) Advanced Concepts in machine learning
Courses
Course 1 : Unsupervised learning aspects.
Course 2 : Supervised learning aspects.
Practical works
PW 1: EM algorithm implementation.
PW 2: Variational Autoencoder implementation.
Project: Recurrent neural network for character prediction.
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2) Signal processing for Radar array
Courses
Course 1: Array model and spatial filtering.
Course 2: DoA estimation.
Tutorials
Tuto 1: Signal model and beamforming.
Tuto 2: DoA estimation.
Practical works
Project: Study and implementation of beamforming and DoA estimation techniques.
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3) Estimation and identification
Courses
Course 1: Basic and fundamentals in statistical estimation.
Course 2: Monte-Carlo methods.
Course 3: Online estimation problem.
Tutorials
Tuto 1: Fundamentals of statistical estimation.
Practical works
PW 1: Monte-Carlo simulations.
PW 2: MCMC methods.
PW 3: Kitagawa model estimation with particle filtering.