Duration
25h Th, 20h Pr, 20h Proj.
Number of credits
| Master MSc. in Biomedical Engineering, professional focus | 5 crédits | |||
| Master Msc. in Electrical Engineering, professional focus in Neuromorphic Engineering | 5 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Neuromorphic engineering attempts to build physical realizations of neural systems using electronic circuits implemented in very large scale integration technology. This emerging field is characterized by its multidisciplinary nature and its focus on the physics of computation, driving innovations in theoretical neuroscience, device physics, electrical engineering, and computer science.
This course introduces the fundamental electronic, biological, and mathematical principles for designing neuromorphic electronic circuits. The focus is on the elementary components (the "building blocks") of neuronal circuits and systems: single neurons and synapses. The final part of the course dissects in details the functioning of event-based cameras, a prominent example of real-world engineering application of the design principles of neuromorphic engineering.
It is highly recommended to take this course together with the Brain Inspired Computing course as the two courses are thought to complement each other.
The course will cover the following table of contents:
0. Introduction to neuromorphic engineering, including a presentation of the new ULiege Neuromorphic Chip.
1. Review of subthreshold MOSFET characteristics.
2. Basic static subthreshold circuits and transconductance amplifiers.
3. Translinear circuits and current-mode circuits.
4. Linear filters: transconductance-based design, current-mode design.
5. Review of biological neuronal behaviors. Modeling biological neurons and synapses.
6. Neuromorphic synapses and basic synaptic plasticity.
7. Neuromorphic neurons: translinear mode and current mode.
8. The ULiege neuromorphic neuron, including a hand-on session in the Department Neuroengineering Lab focused on the new ULiege neuromorphic chip.
9. Photoreceptors and event-based cameras, including a hand-on session in the Department Neuroengineering Lab focused on iniVation DAVIS event-based cameras and Melexis 3D touch sensors.
10. (Optional) Elements of mixed-mode (analog-digital) VLSI design and learning in VLSI circuits.
Learning outcomes of the learning unit
Through theoretical lectures, Cadence simulations, and hand-on session, by the end of the semester students will be able to:
- Use the Cadence Virtuoso Studio environment.
- Design linear and nonlinear, static and dynamic, subthreshold MOSFET circuits and simulate them in Cadence Virtuoso Studio.
- Understand how single biological neurons and biological neuronal circuits and systems work, and how we can model them.
- Translate mathematical models of neurons and synapses into subthreshold MOSFET designs and simulate them in Cadence Virtuoso Studio.
- Understand and design event-based cameras and other kinds of neuromorphic sensors, and simulate the sensor design in Cadence Virtuoso Studio.
- Interested students will be able to learn the basics of CMOS layout design in Cadence Virtuoso Studio.
Prerequisite knowledge and skills
Basic microelectronics.
Some experience in the SPICE environment.
Some knowledge in basic linear and nonlinear dynamical systems and control theory can be useful.
Planned learning activities and teaching methods
The course includes theoretical lectures, exercise sessions, hardware hands-on-sessions in the Department Neuroengineering Lab, and project sessions.
For project development, students will be able to access hardware (event-based cameras, TurtleBots, VEX Robot hardware, neuromorpchi chips) and experimental data (Brain-on-Chip setup, in-vivo and in-vtro electrophysiology) from the Department Neuroengineering Lab.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Course materials and recommended or required readings
Shih-Chii Liu, Jorg Kramer, Giacomo Indiveri, Tobias Delbruck, Rodney Douglas - Analog VLSI Circuits and Principles - The MIT Press (2002)
Exam(s) in session
Any session
- In-person
written exam AND oral exam
Written work / report
Further information:
Weekly homeworks.
Final project.
Final project oral presentation
Work placement(s)
Organisational remarks and main changes to the course
Contacts
Alessio Franci.
https://sites.google.com/site/francialessioac/