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2025-2026 / PHYS0968-1

Signal processing

Duration

25h Th, 20h Pr

Number of credits

 Bachelor in chemistry4 crédits 
 Master in physics, research focus4 crédits 
 Master in physics, teaching focus (Réinscription uniquement, pas de nouvelle inscription)4 crédits 
 Master in physics, professional focus in medical radiophysics4 crédits 
 Master of education, Section 4: Physics5 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


Further information:

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

Course materials and recommended or required readings

Platform(s) used for course materials:
- eCampus


Further information:

The course materials and resources for practical work will be available on the eCampus platform. Recommended readings will be indicated during the first class.

Exam(s) in session

Any session

- In-person

written exam ( open-ended questions )


Further information:

Exam(s) during the session - in person

Assessment combining a digital project and an oral examination.

Additional information

24 hours before the exam, students receive a digital problem to prepare.

The project must be submitted at a specified time.

The oral exam assesses the understanding of theoretical concepts and the ability to defend the project.

Work placement(s)

Organisational remarks and main changes to the course

The practical work may be carried out in Python or IGOR (at the student's choice), either on their own computer or on a provided PC. It is recommended to install the necessary software before the first practical session, in accordance with the instructions available on eCampus.

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

 

Daniel Stoffels (Daniel.Stoffels@uliege.be)

Association of one or more MOOCs