Suchergebnis: Katalogdaten im Frühjahrssemester 2020

Neural Systems and Computation Master Information
Wahlfächer
NummerTitelTypECTSUmfangDozierende
227-0147-00LVLSI II: Design of Very Large Scale Integration Circuits Information W6 KP5GF. K. Gürkaynak, L. Benini
KurzbeschreibungThis second course in our VLSI series is concerned with how to turn digital circuit netlists into safe, testable and manufacturable mask layout, taking into account various parasitic effects. Low-power circuit design is another important topic. Economic aspects and management issues of VLSI projects round off the course.
LernzielKnow how to design digital VLSI circuits that are safe, testable, durable, and make economic sense.
InhaltThe second course begins with a thorough discussion of various technical aspects at the circuit and layout level before moving on to economic issues of VLSI. Topics include:
- The difficulties of finding fabrication defects in large VLSI chips.
- How to make integrated circuit testable (design for test).
- Synchronous clocking disciplines compared, clock skew, clock distribution, input/output timing.
- Synchronization and metastability.
- CMOS transistor-level circuits of gates, flip-flops and random access memories.
- Sinks of energy in CMOS circuits.
- Power estimation and low-power design.
- Current research in low-energy computing.
- Layout parasitics, interconnect delay, static timing analysis.
- Switching currents, ground bounce, IR-drop, power distribution.
- Floorplanning, chip assembly, packaging.
- Layout design at the mask level, physical design verification.
- Electromigration, electrostatic discharge, and latch-up.
- Models of industrial cooperation in microelectronics.
- The caveats of virtual components.
- The cost structures of ASIC development and manufacturing.
- Market requirements, decision criteria, and case studies.
- Yield models.
- Avenues to low-volume fabrication.
- Marketing considerations and case studies.
- Management of VLSI projects.

Exercises are concerned with back-end design (floorplanning, placement, routing, clock and power distribution, layout verification). Industrial CAD tools are being used.
SkriptH. Kaeslin: "Top-Down Digital VLSI Design, from Gate-Level Circuits to CMOS Fabrication", Lecture Notes Vol.2 , 2015.

All written documents in English.
LiteraturH. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303.
Voraussetzungen / BesonderesHighlight:
Students are offered the opportunity to design a circuit of their own which then gets actually fabricated as a microchip! Students who elect to participate in this program register for a term project at the Integrated Systems Laboratory in parallel to attending the VLSI II course.

Prerequisites:
"VLSI I: from Architectures to Very Large Scale Integration Circuits and FPGAs" or equivalent knowledge.

Further details:
Link
227-0395-00LNeural SystemsW6 KP2V + 1U + 1AR. Hahnloser, M. F. Yanik, B. Grewe
KurzbeschreibungThis course introduces principles of information processing in neural systems. It covers basic neuroscience for engineering students, experiment techniques used in animal research and methods for inferring neural mechanisms. Students learn about neural information processing and basic principles of natural intelligence and their impact on artificially intelligent systems.
LernzielThis course introduces
- Basic neurophysiology and mathematical descriptions of neurons
- Methods for dissecting animal behavior
- Neural recordings in intact nervous systems and information decoding principles
- Methods for manipulating the state and activity in selective neuron types
- Neuromodulatory systems and their computational roles
- Reward circuits and reinforcement learning
- Imaging methods for reconstructing the synaptic networks among neurons
- Birdsong and language
- Neurobiological principles for machine learning.
InhaltFrom active membranes to propagation of action potentials. From synaptic physiology to synaptic learning rules. From receptive fields to neural population decoding. From fluorescence imaging to connectomics. Methods for reading and manipulation neural ensembles. From classical conditioning to reinforcement learning. From the visual system to deep convolutional networks. Brain architectures for learning and memory. From birdsong to computational linguistics.
Voraussetzungen / BesonderesBefore taking this course, students are encouraged to complete "Bioelectronics and Biosensors" (227-0393-10L).

As part of the exercises for this class, students are expected to complete a programming or literature review project to be defined at the beginning of the semester.
227-1032-00LNeuromorphic Engineering II Information
Information für UZH Studierende:
Die Lerneinheit kann nur an der ETH belegt werden. Die Belegung des Moduls INI405 ist an der UZH nicht möglich.

Beachten Sie die Einschreibungstermine an der ETH für UZH Studierende: Link
W6 KP5GS.‑C. Liu, T. Delbrück, G. Indiveri
KurzbeschreibungThis 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".
LernzielDesign of a neuromorphic circuit for implementation with CMOS technology.
InhaltThis 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.
LiteraturS.-C. Liu et al.: Analog VLSI Circuits and Principles; software documentation.
Voraussetzungen / BesonderesPrerequisites: Neuromorphic Engineering I strongly recommended
227-1046-00LComputer Simulations of Sensory Systems Information
Findet dieses Semester nicht statt.
W3 KP3G
KurzbeschreibungThis course deals with computer simulations of the human auditory, visual, and balance system. The lecture will cover the physiological and mechanical mechanisms of these sensory systems. And in the exercises, the simulations will be implemented with Python. The simulations will be such that their output could be used as input for actual neuro-sensory prostheses.
LernzielOur sensory systems provide us with information about what is happening in the world surrounding us. Thereby they transform incoming mechanical, electromagnetic, and chemical signals into “action potentials”, the language of the central nervous system.
The main goal of this lecture is to describe how our sensors achieve these transformations, how they can be reproduced with computational tools. For example, our auditory system performs approximately a “Fourier transformation” of the incoming sound waves; our early visual system is optimized for finding edges in images that are projected onto our retina; and our balance system can be well described with a “control system” that transforms linear and rotational movements into nerve impulses.
In the exercises that go with this lecture, we will use Python to reproduce the transformations achieved by our sensory systems. The goal is to write programs whose output could be used as input for actual neurosensory prostheses: such prostheses have become commonplace for the auditory system, and are under development for the visual and the balance system. For the corresponding exercises, at least some basic programing experience is required!!
InhaltThe following topics will be covered:
• Introduction into the signal processing in nerve cells.
• Introduction into Python.
• Simplified simulation of nerve cells (Hodgkins-Huxley model).
• Description of the auditory system, including the application of Fourier transforms on recorded sounds.
• Description of the visual system, including the retina and the information processing in the visual cortex. The corresponding exercises will provide an introduction to digital image processing.
• Description of the mechanics of our balance system, and the “Control System”-language that can be used for an efficient description of the corresponding signal processing (essentially Laplace transforms and control systems).
SkriptFor each module additional material will be provided on the e-learning platform "moodle". The main content of the lecture is also available as a wikibook, under Link
LiteraturOpen source information is available as wikibook Link

For good overviews I recommend:

• Principles of Neural Science (5th Ed, 2012), by Eric Kandel, James Schwartz, Thomas Jessell, Steven Siegelbaum, A.J. Hudspeth
ISBN 0071390111 / 9780071390118
THE standard textbook on neuroscience.

• L. R. Squire, D. Berg, F. E. Bloom, Lac S. du, A. Ghosh, and N. C. Spitzer. Fundamental Neuroscience, Academic Press - Elsevier, 2012 [ISBN: 9780123858702].
This book covers the biological components, from the functioning of an individual ion channels through the various senses, all the way to consciousness. And while it does not cover the computational aspects, it nevertheless provides an excellent overview of the underlying neural processes of sensory systems.

• G. Mather. Foundations of Sensation and Perception, 2nd Ed Psychology Press, 2009 [ISBN: 978-1-84169-698-0 (hardcover), oder 978-1-84169-699-7 (paperback)]
A coherent, up-to-date introduction to the basic facts and theories concerning human sensory perception.

• The best place to get started with Python programming are the Link
Voraussetzungen / Besonderes• Since I have to gravel from Linz, Austria, to Zurich to give this lecture, I plan to hold this lecture in blocks (every 2nd week).
• In addition to the lectures, this course includes external lab visits to institutes actively involved in research on the relevant sensory systems.
402-0673-00LPhysics in Medical Research: From Humans to CellsW6 KP2V + 1UB. K. R. Müller
KurzbeschreibungThe aim of this lecture series is to introduce the role of physics in state-of-the-art medical research and clinical practice. Topics to be covered range from applications of physics in medical implant technology and tissue engineering, through imaging technology, to its role in interventional and non-interventional therapies.
LernzielThe lecture series is focused on applying knowledge from physics in diagnosis, planning, and therapy close to clinical practice and fundamental medical research. Beside a general overview, the lectures give a deep insight into a very few selected techniques, which will help the students to apply the knowledge to a broad range of related techniques.

In particular, the lectures will elucidate the physics behind the X-ray imaging currently used in clinical environment and contemporary high-resolution developments. It is the goal to visualize and quantify (sub-)microstructures of human tissues and implants as well as their interface.

Ultrasound is not only used for diagnostic purposes but includes therapeutic approaches such as the control of the blood-brain barrier under MR-guidance.

Physicists in medicine are working on modeling and simulation. Based on the vascular structure in cancerous and healthy tissues, the characteristic approaches in computational physics to develop strategies against cancer are presented. In order to deliberately destroy cancerous tissue, heat can be supplied or extracted in different manner: cryotherapy (heat conductivity in anisotropic, viscoelastic environment), radiofrequency treatment (single and multi-probe), laser application, and proton therapy.

Medical implants play an important role to take over well-defined tasks within the human body. Although biocompatibility is here of crucial importance, the term is insufficiently understood. The aim of the lectures is the understanding of biocompatibility performing well-defined experiments in vitro and in vivo. Dealing with different classes of materials (metals, ceramics, polymers) the influence of surface modifications (morphology and surface coatings) are key issues for implant developments, which might be bio-inspired.

Mechanical stimuli can drastically influence soft and hard tissue behavior. The students should realize that a physiological window exists, where a positive tissue response is expected and how the related parameter including strain, frequency, and resting periods can be selected and optimized for selected tissues such as bone.

For the treatment of severe incontinence, we are developing artificial smart muscles. The students should have a critical look at promising solutions and the selection procedure as well as realize the time-consuming and complex way to clinical practice.

The course will be completed by relating the numerous examples and a common round of questions.
InhaltThis lecture series will cover the following topics:
Introduction: Imaging the human body down to individual cells and beyond
Development of artificial muscles for incontinence treatment
X-ray-based computed tomography in clinics and related medical research
High-resolution micro computed tomography
Phase tomography using hard X-rays in biomedical research
Metal-based implants and scaffolds
Natural and synthetic ceramics for implants and regenerative medicine
Biomedical simulations
Polymers for medical implants
From open surgery to non-invasive interventions - Physical approaches in medical imaging
Dental research
Focused Ultrasound and its clinical use
Applying physics in medicine: Benefitting patients
SkriptLink

login and password to be provided during the lecture
Voraussetzungen / BesonderesStudents from other departments are very welcome to join and gain insight into a variety of sophisticated techniques for the benefit of patients.
No special knowledge is required. Nevertheless, gaps in basic physical knowledge will require additional efforts.
701-1418-00LModelling Course in Population and Evolutionary Biology Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 20.

Priority is given to MSc Biology and Environmental Sciences students.
W4 KP6PS. Bonhoeffer, V. Müller
KurzbeschreibungDieser Kurs ist eine praktische Einfuehrung in die mathematische/computerorientierte Modellierung biologischer Prozesse mit Schwerpunkt auf evolutionsbiologischen und populationsbiologischen Fragestellungen. Die Modelle werden in der Open Source software R entwickelt.
LernzielDen Teilnehmern soll der Nutzen der Modellierung als ein Hilfsmittel zur Untersuchung biologischer Fragestellungen vermittelt werden. Die einfacheren Module orientieren sich mehrheitlich an Beispielen aus der ehemaligen Vorlesung "Oekologie und Evolution: Populationen" (Skript von der Kurswebseite zugaenglich). Die fortgeschrittenen Module orientieren sich an aktuellen Forschungsthemen. Hierbei werden auch Fragestellungen untersucht, die zwar konzeptionell und methodisch auf Evolutions- und Populations-biologischen Ansaetzen beruhen, aber sich mit anderen Bereichen der Biologie befassen.
Inhaltsiehe Link
SkriptDetaillierte Handouts für alle Module sind an der Webseite des Kurses zu finden. Zusaetzlich ist das Skript für die frühere Vorlesung "Oekologie und Evolution: Populationen" auch zugaenglich, und enthaelt weitere relevante Informationen.
Voraussetzungen / BesonderesDer Kurs basiert auf der Open Source Software R. Programmiererfahrung in R ist nuetzlich, aber keine Voraussetzung. Ebenso ist der Kurs 701-1708-00L Infectious Disease Dynamics nützlich, aber keine Voraussetzung.
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