Signal processing

5.00 crédits

30.0 h + 30.0 h

> Horaire

Enseignants

Jacques Laurent; Vandendorpe Luc;

Langue
d'enseignement

Anglais
> Facilités pour suivre le cours en français

Acquis
d'apprentissage

A la fin de cette unité d’enseignement, l’étudiant est capable de :
1	At the end of this learning unit, the student is able to : With respect to the AA referring system defined for the Master in Electrical Engineering, the course contributes to the development, mastery and assessment of the following skills : AA1.1, AA1.2, AA1.3 AA2.1, AA2.2 AA6.1 The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.

Contenu

Sampling: theorem, interpolation, sequence
Sampling rate change: downsampling and interpolation for low-pass signals and bandpass signals, complex envelope
Processing structures and graph theory: switching, transposition, direct and polyphase structures
Discrete Fourier transform, properties, convolution, truncation and window
Finite impulse response filters, phase linearity, types and properties of poles and zeros
Synthesis of FIR filters: window method, frequency response sampling, minimax synthesis and Remez method
Synthesis of IIR filters by impulse invariance and bilinear transformation
Bayesian filtering, Kalman filtering, particle filter, and variants
Theory of multiresolution and wavelet transforms (from the Haar system to other wavelets)
Compressive sensing: principles and algorithms
Numerical exercises in Python related to these topics

Méthodes d'enseignement

The course is composed of

lectures on the topics listed in the course content,
and practical sessions, both classical and numerical.

Lectures and practical sessions are given in the classroom exclusively.

Modes d'évaluation
des acquis des étudiants

Concerning the lectures, the students are individually evaluated with a (in-session) written exam, including problems solving, and questions on the theory.
Regarding the numerical exercises on Python, the students are individually evaluated off-session, over two distinct evaluations, in a computer room. Each of these two evaluations are organized only once during the semester.

The written exam and the in-session evaluations amount to 80% and 20% of the final grade, respectively. The mark obtained for the numerical exercises is acquired for all sessions of the academic year.

Ressources
en ligne

Moodle https://moodle.uclouvain.be/course/view.php?id=715

Bibliographie

Course and lecture notes available on Moodle
Slides and reference articles available on Moodle

First half of the course available as a podcast

Faculté ou entité
en charge

> ELEC

Programmes / formations proposant cette unité d'enseignement (UE)

Intitulé du programme

Sigle

Crédits

Prérequis

Acquis
d'apprentissage

Master [120] : ingénieur civil biomédical

GBIO2M

Master [120] : ingénieur civil électricien

ELEC2M

Master [120] : ingénieur civil en mathématiques appliquées

MAP2M