Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

227-1033-00L  Neuromorphic Engineering I

SemesterAutumn Semester 2016
LecturersT. Delbrück, G. Indiveri, S.‑C. Liu
Periodicityyearly recurring course
Language of instructionEnglish
CommentRegistration 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.

Catalogue data

AbstractThis 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.
ObjectiveUnderstanding of the characteristics of neuromorphic circuit elements.
ContentNeuromorphic 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.
LiteratureS.-C. Liu et al.: Analog VLSI Circuits and Principles; various publications.
Prerequisites / NoticeParticular: 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.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a two-semester course together with 227-1032-00L Neuromorphic Engineering II (next semester)
ECTS credits12 credits
Performance assessment as a semester course (other programmes)
ECTS credits6 credits
ExaminersT. Delbrück, G. Indiveri, S.-C. Liu
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 20 minutes
Additional information on mode of examinationSuccessful completion of lab exercises.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

Main linkInformation
Only public learning materials are listed.


227-1033-00 VNeuromorphic Engineering I
Permission from lecturers required for all students.
**together with the Uni Zurich**
More informations at:
2 hrs
Mon13-15I21 D 68a »
T. Delbrück, G. Indiveri, S.‑C. Liu
227-1033-00 UNeuromorphic Engineering I
Permission from lecturers required for all students.
**together with the Uni Zurich**
More informations at:
3 hrsby appt.T. Delbrück, G. Indiveri, S.‑C. Liu


No information on groups available.


GeneralPermission from lecturers required for all students

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