2023-2024 / PHYS0968-1

Signal processing

Duration

25h Th, 20h Pr

Number of credits

 Bachelor in chemistry4 crédits 
 Master in physics (120 ECTS)4 crédits 

Lecturer

Alejandro Silhanek

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The following topics will be raised
- Special functions and Dirac's delta distribution
- Linear filters and convolution
- Fourier transforms and applications
- Basics in probability and statistics
- Application to data reductions

Learning outcomes of the learning unit

Basics in signal processing and data reduction.

Prerequisite knowledge and skills

Basic knowledge in mathematical analysis, general physics, and crystalography

Planned learning activities and teaching methods

Data reductions of experimental signals on a computer. Statistical analysis of data on a computer. Exercices aiming to apply the concepts discussed in the theoretical course.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course


Additional information:

Theoretical lectures ex-cathedra and practical sessions (computer processing and resolution of exercices).

Recommended or required readings

Delivered at the start of the course.

Exam(s) in session

Any session

- In-person

written exam ( open-ended questions )


Additional information:

Written exam concerning the theoretical part: solving exercices and answering theoretical questions. In addition, there is a practical exam on the computer using the environment proposed during the course.

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Alejandro V. Silhanek

Département de Physique
Université de Liège
Bât. B5, R/53
Allée du 6 août, 19
B- 4000 Sart Tilman
BELGIUM
Tel : 04 366 36 32
Email: asilhanek@uliege.be

 

Thomas Ratz ( thomas.ratz@uliege.be )

Association of one or more MOOCs