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Neuromorphic Engineering II
Last Updated: 2026-06-01 11:33:02
Abstract
This course teaches the basics of analog chip design and layout with an emphasis on neuromorphic circuits, which are introduced in the fall semester course "Neuromorphic Engineering I".
Objective
Design of a neuromorphic circuit for implementation with CMOS technology.
Content
This course teaches the basics of analog chip design and layout with an emphasis on neuromorphic circuits, which are introduced in the autumn semester course "Neuromorphic Engineering I". The principles of CMOS processing technology are presented. Using a set of inexpensive software tools for simulation, layout and verification, suitable for neuromorphic circuits, participants learn to simulate circuits on the transistor level and to make their layouts on the mask level. Important issues in the layout of neuromorphic circuits will be explained and illustrated with examples. In the latter part of the semester students simulate and layout a neuromorphic chip. Schematics of basic building blocks will be provided. The layout will then be fabricated and will be tested by students during the following fall semester.
Resources
Literature
S.-C. Liu et al.: Analog VLSI Circuits and Principles; software documentation.
General Information
- Language
- English
- Levels
- BSC , MSC , WBZ
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 20 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Neuromorphic Engineering II
**together with University of Zurich**
More information at:
Lecture: 13:00 - 15:00
Exercises: 15:00 - 18:00
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5 h weekly |
Offered In
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Wahlfächer (Von den angebotenen Wahlfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden.)
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Biomedical Engineering Master (Es können nur Kurse angerechnet werden, die unter der Kategorie "GESS – Wissenschaft im Kontext (SiP)" aufgeführt werden. Siehe Reiter "Angeboten in" in der Kursübersicht. Für mehr Information, siehe )
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Kernfächer der Vertiefung (Während des Studiums müssen mindestens 12 KP aus Kernfächern einer Vertiefung (Track) erreicht werden.)
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Wahlfächer (Von den angebotenen Wahlfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden.)
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Vertiefung: Signal Processing and Machine Learning (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Signal Processing and Machine Learning ", see . The individual study plan is subject to the tutor's approval.)
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Vertiefungsfächer (These specialization courses are particularly recommended for the area of "Signal Processing and Machine Learning", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialization courses during the MSc EEIT.)
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Fächer der Vertiefung (A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval. Semester / Research Projects are not allowed in this category.)
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