School / Prep
ENSEIRB-MATMECA
ECTS
6 credits
Internal code
ET8B1
Description
Level of knowledge :
N1: beginner
N2: intermediate
N3: confirmed
N4: expert
The knowledge (skills) expected at the end of the course
Know how to model the imperfections involved in digital communications (time/frequency synchronization, multipath channel) (C2, N3).
Know the principles of synchronization, block approach and line approach, as well as the principles of propagation channel estimation (C3, N3).
Knowledge of the principles of supervised learning and deep neural networks (C2, N3).
Learning outcomes in terms of abilities, skills and attitudes expected at the end of the course
Ability to implement a synchronization and multipath channel estimation algorithm on simulated or real signals from software radios (C5, N3)
Ability to implement a convolutional neural network (C3, N3)
List of courses
Module - Engineering culture (elective)
Choice of 1 out of 10
Business Intelligence
Introduction to market finance
Technical sciences and society
Entrepreneurial path
Human, high-performance management
Digital and innovative project management
Management & health at work
Participation in a challenge/contest
S8 TOEIC (compulsory retake)
Introduction to research - PhD program
Supervised Machine Learning project
Channel estimation and synchronization in digital communications