3.00 credits
20.0 h + 10.0 h
Q2
Teacher(s)
Lee John; Missal Marcus (coordinator);
Language
French
Prerequisites
The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Content
(1) Necessity of a theoretical approach in neurosciences. (2) History of neural networks. (3) Most important types of neural networks
At the end of this unit, the student should be able to justify mathematical modeling of the central nervous system. The student should be able to explain the general principles of neural networks and have the knowledge and skills to simulate the behavior of elementary neural networks using MATLAB NNTool GUI.
At the end of this unit, the student should be able to justify mathematical modeling of the central nervous system. The student should be able to explain the general principles of neural networks and have the knowledge and skills to simulate the behavior of elementary neural networks using MATLAB NNTool GUI.
Teaching methods
Lectures (physically, remotely or both/comodal dep. sanitary conditions) and critical paper readings.
Evaluation methods
Oral examination (switching to written or distancial depending on the class size and sanitary conditions).
Weighting of the final score: 50% for Marcus Missal's part, 50% for John Lee's part.
Weighting of the final score: 50% for Marcus Missal's part, 50% for John Lee's part.
Other information
Prerequisites: introduction to linear algebra and differential calculus.
Online resources
https://moodleucl.uclouvain.be/course/view.php?id=9189
Teaching materials
- https://moodleucl.uclouvain.be/course/view.php?id=9189
Faculty or entity
FASB
