227-1033-00L  Neuromorphic Engineering I

SemesterHerbstsemester 2019
DozierendeT. Delbrück, G. Indiveri, S.‑C. Liu
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarRegistration in this class requires the permission of the instructors. Class size will be limited to available lab spots.
Preference is given to students that require this class as part of their major.



Katalogdaten

KurzbeschreibungThis course covers analog circuits with emphasis on neuromorphic engineering: MOS transistors in CMOS technology, static circuits, dynamic circuits, systems (silicon neuron, silicon retina, silicon cochlea) with an introduction to multi-chip systems. The lectures are accompanied by weekly laboratory sessions.
LernzielUnderstanding of the characteristics of neuromorphic circuit elements.
InhaltNeuromorphic circuits are inspired by the organizing principles of biological neural circuits. Their computational primitives are based on physics of semiconductor devices. Neuromorphic architectures often rely on collective computation in parallel networks. Adaptation, learning and memory are implemented locally within the individual computational elements. Transistors are often operated in weak inversion (below threshold), where they exhibit exponential I-V characteristics and low currents. These properties lead to the feasibility of high-density, low-power implementations of functions that are computationally intensive in other paradigms. Application domains of neuromorphic circuits include silicon retinas and cochleas for machine vision and audition, real-time emulations of networks of biological neurons, and the development of autonomous robotic systems. This course covers devices in CMOS technology (MOS transistor below and above threshold, floating-gate MOS transistor, phototransducers), static circuits (differential pair, current mirror, transconductance amplifiers, etc.), dynamic circuits (linear and nonlinear filters, adaptive circuits), systems (silicon neuron, silicon retina and cochlea) and an introduction to multi-chip systems that communicate events analogous to spikes. The lectures are accompanied by weekly laboratory sessions on the characterization of neuromorphic circuits, from elementary devices to systems.
LiteraturS.-C. Liu et al.: Analog VLSI Circuits and Principles; various publications.
Voraussetzungen / BesonderesParticular: The course is highly recommended for those who intend to take the spring semester course 'Neuromorphic Engineering II', that teaches the conception, simulation, and physical layout of such circuits with chip design tools.

Prerequisites: Background in basics of semiconductor physics helpful, but not required.

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Jahreskurs mit 227-1032-00L Neuromorphic Engineering II (nächstes Semester)
ECTS Kreditpunkte12 KP
Leistungskontrolle als Semesterkurs (übrige Studiengänge)
ECTS Kreditpunkte6 KP
PrüfendeT. Delbrück, G. Indiveri, S.-C. Liu
FormSessionsprüfung
PrüfungsspracheEnglisch
RepetitionDie Leistungskontrolle wird in jeder Session angeboten. Die Repetition ist ohne erneute Belegung der Lerneinheit möglich.
Prüfungsmodusmündlich 20 Minuten
Zusatzinformation zum PrüfungsmodusEach student attends one lab session per week.

Mandatory labs and scores: We will drop your 3 lowest lab grades, but you must successfully complete the first 3 labs, which are mandatory. In addition, you are required to attend at least one of the last 2 labs.
Students, who don't fulfil these conditions, must deregister from the final exam, otherwise it would be decreed “broken off”.

The final grade is based 70% on exam and 30% on lab exercises.
Diese Angaben können noch zu Semesterbeginn aktualisiert werden; verbindlich sind die Angaben auf dem Prüfungsplan.

Lernmaterialien

 
HauptlinkInformation
Es werden nur die öffentlichen Lernmaterialien aufgeführt.

Lehrveranstaltungen

NummerTitelUmfangDozierende
227-1033-00 VNeuromorphic Engineering I
Bewilligung der Dozierenden für alle Studierenden notwendig.
**together with University of Zurich**
More information at: Link

Room: I44 H05
2 Std.
Mo13-15I44   »
T. Delbrück, G. Indiveri, S.‑C. Liu
227-1033-00 UNeuromorphic Engineering I
Bewilligung der Dozierenden für alle Studierenden notwendig.
**together with University of Zurich**
More information at: Link

Dates by arrangement.
Room to be announced.
3 Std.n. V.T. Delbrück, G. Indiveri, S.‑C. Liu

Gruppen

Keine Informationen zu Gruppen vorhanden.

Einschränkungen

AllgemeinBewilligung der Dozierenden für alle Studierenden notwendig

Angeboten in

StudiengangBereichTyp
Biomedical Engineering MasterWahlfächer der VertiefungWInformation
Biomedical Engineering MasterWahlfächer der VertiefungWInformation
Computational Biology and Bioinformatics MasterVertiefungsfächerWInformation
DAS in Data ScienceNeural Information ProcessingWInformation
Data Science MasterInterdisziplinäre WahlfächerWInformation
Elektrotechnik und Informationstechnologie MasterKernfächerWInformation
Elektrotechnik und Informationstechnologie MasterVertiefungsfächerWInformation
MAS in MedizinphysikWahlfächerWInformation
MAS in MedizinphysikWahlfächerWInformation
Neural Systems and Computation MasterNeurotechnologie und Neuromorphe IngenieurwissenschaftenWInformation
Physik MasterAuswahl: NeuroinformatikWInformation
Rechnergestützte Wissenschaften BachelorWahlfächerWInformation
Rechnergestützte Wissenschaften MasterWahlfächerWInformation