| Course label : | BME215 Signal processing, Part 1 |
|---|---|
| Teaching departement : | MSO / Structures, Mechanisms and Construction |
| Teaching manager : | Mister OLIVIER MAYEUR |
| Education language : | |
| Potential ects : | 2 |
| Results grid : | |
| Code and label (hp) : | MR_BME_S2_MSO_SP1 - BME215 Signal processing,part1 |
Education team
Teachers : Mister OLIVIER MAYEUR
External contributors (business, research, secondary education): various temporary teachers
Summary
This course provides the knowledge of Physics required to follow the key points dealing with sensor-obtained Signal Processing It covers knowledge in the field of Sampling & Approximation theory, principal fundamental methods, statistical learning for signal processing
Educational goals
Course objectives - Learn some basic signal types and properties - Learn how to digitize a signal - First set of signal processing tools (frequency analysis, filtering, etc.) - Offline signal processing (Python + Jupyter Lab + scipy.signal) - Live signal processing/visualization (Python + pyqtgraph + scipy.signal)
Sustainable development goals
Knowledge control procedures
Continuous Assessment / Final Exam
Comments:
Online resources
LMS learning management system (Moodle) with all course documents, corrected exercises, publication, forum.
Pedagogy
Lectures, Practices, Homework, Examples and application based on illustrations and concrete situations from biomedical engineering and research.
Sequencing / learning methods
| Number of hours - Lectures : | 0 |
|---|---|
| Number of hours - Tutorial : | 0 |
| Number of hours - Practical work : | 0 |
| Number of hours - Seminar : | 24 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 0 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |