Suchergebnis: Katalogdaten im Frühjahrssemester 2015
|Doktorat Departement Informationstechnologie und Elektrotechnik |
Mehr Informationen unter: http://www.ethz.ch/doctorate/programmes
| Lehrangebot Doktorat und Postdoktorat|
A minimum of 12 ECTS credit points must be obtained during doctoral studies.
The courses on offer below are but a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.
|227-0126-00L||Advanced Topics in Networked Embedded Systems |
Number of participants limited to 12.
|W||2 KP||1S||O. Saukh, J. Beutel, L. Thiele|
|Kurzbeschreibung||The seminar will cover advanced topics in networked embedded systems. A particular focus are cyber-physical systems and sensor networks in various application domains.|
|Lernziel||The goal is to get a deeper understanding on leading edge technologies in the discipline, on classes of applications, and on current as well as future research directions.|
|Inhalt||The seminar enables Master students, PhDs and Postdocs to learn about latest breakthroughs in wireless sensor networks, networked embedded systems and devices, and energy-harvesting in several application domains, including environmental monitoring, tracking, smart buildings and control. Participants are requested to actively participate in the organization and preparation of the seminar.|
|227-0146-00L||Analog-to-Digital Converters||W||6 KP||2V + 2U||Q. Huang, T. Burger|
|Kurzbeschreibung||This course provides a thorough treatment of integrated data conversion systems from system level specifications and trade-offs, over architecture choice down to circuit implementation.|
|Lernziel||Data conversion systems are substantial sub-parts of many electronic systems, e.g. the audio conversion system of a home-cinema systems or the base-band front-end of a wireless modem. Data conversion systems usually determine the performance of the overall system in terms of dynamic range and linearity. The student will learn to understand the basic principles behind data conversion and be introduced to the different methods and circuit architectures to implement such a conversion. The conversion methods such as successive approximation or algorithmic conversion are explained with their principle of operation accompanied with the appropriate mathematical calculations, including the effects of non-idealties in some cases. After successful completion of the course the student should understand the concept of an ideal ADC, know all major converter architectures, their principle of operation and what governs their performance.|
|Inhalt||- Introduction: information representation and communication; abstraction, categorization and symbolic representation; basic conversion algorithms; data converter application; tradeoffs among key parameters; ADC taxonomy.|
- Dual-slope & successive approximation register (SAR) converters: dual slope principle & converter; SAR ADC operating principle; SAR implementation with a capacitive array; range extension with segmented array.
- Algorithmic & pipelined A/D converters: algorithmic conversion principle; sample & hold stage; pipe-lined converter; multiplying DAC; flash sub-ADC and n-bit MDAC; redundancy for correction of non-idealties, error correction.
- Performance metrics and non-linearity: ideal ADC; offset, gain error, differential and integral non-linearities; capacitor mismatch; impact of capacitor mismatch on SAR ADC's performance.
- Flash, folding an interpolating analog-to-digital converters: flash ADC principle, thermometer to binary coding, sparkle correction; limitations of flash converters; the folding principle, residue extraction; folding amplifiers; cascaded folding; interpolation for folding converters; cascaded folding and interpolation.
- Noise in analog-to-digital converters: types of noise; noise calculation in electronic circuit, kT/C-noise, sampled noise; noise analysis in switched-capacitor circuits; aperture time uncertainty and sampling jitter.
- Delta-sigma A/D-converters: linearity and resolution; from delta-modulation to delta-sigma modulation; first-oder delta-sigma modulation, circuit level implementation; clock-jitter & SNR in delta-sigma modulators; second-order delta-sigma modulation, higher-order modulation, design procedure for a single-loop modulator.
- Digital-to-analog converters: introduction; current scaling D/A converter, current steering DAC, calibration for improved performance.
|Skript||Handouts of the slides will be distributed.|
|Literatur||- B. Razavi, Principles of Data Conversion System Design, IEEE Press, 1994|
- M. Gustavsson et. al., CMOS Data Converters for Communications, Springer, 2010
- R.J. van de Plassche, CMOS Integrated Analog-to-Digital and Digital-to-Analog Converters, Springer, 2010
|Voraussetzungen / Besonderes||It is highly recommended to attend the course "Analog Integrated Circuits" of Prof. Huang as a preparation for this course.|
|227-0159-00L||Quantum Transport in Nanoscale Devices||W||6 KP||2V + 2U||M. Luisier|
|Kurzbeschreibung||This class offers an introduction into quantum transport theory, a rigorous approach to electron transport at the nanoscale. It covers different topics such as bandstructure, Wave Function and Non-equilibrium Green's Function formalisms, and electron interactions with their environment. Matlab exercises accompany the lectures where students learn how to develop their own transport simulator.|
|Lernziel||The continuous scaling of electronic devices has given rise to structures whose dimensions do not exceed a few atomic layers. At this size, electrons do not behave as particle any more, but as propagating waves and the classical representation of electron transport as the sum of drift-diffusion processes fails. The purpose of this class is to explore and understand the displacement of electrons through nanoscale device structures based on state-of-the-art quantum transport methods and to get familiar with the underlying equations by developing his own nanoelectronic device simulator.|
|Inhalt||The following topics will be addressed:|
- Introduction to quantum transport modeling
- Bandstructure representation and effective mass approximation
- Open vs closed boundary conditions to the Schrödinger equation
- Comparison of the Wave Function and Non-equilibrium Green's Function formalisms as solution to the Schrödinger equation
- Self-consistent Schödinger-Poisson simulations
- Quantum transport simulations of resonant tunneling diodes and quantum well nano-transistors
- Top-of-the-barrier simulation approach to nano-transistor
- Electron interactions with their environment (phonon, roughness, impurity,...)
- Multi-band transport models
|Skript||Lecture slides are distributed every week and can be found at|
|Literatur||Recommended textbook: "Electronic Transport in Mesoscopic Systems", Supriyo Datta, Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, 1997|
|Voraussetzungen / Besonderes||Basic knowledge of semiconductor device physics and quantum mechanics|
|227-0207-00L||Nonlinear Systems and Control |
Voraussetzung: Control Systems (227-0103-00L)
|W||6 KP||4G||E. Gallestey Alvarez, P. F. Al Hokayem|
|Kurzbeschreibung||Vermittlung von den Grundlagen für die Modellierung und Analyse von Nichtlineare Systeme,sowie eine Übersicht der verschiedene nichtlinearen Reglerentwurfsmethoden.|
|Lernziel||Die Studenten kennen die unterschiede zwischen lineare und nichtlineare Systeme, die Mathematische Grundlagen für deren Modellierung und Analyse, und kene auch die verschiedene Möglichkeiten, einen Regler für das nichtlineares System zu entwerfen.|
|Inhalt||Fast alle in der Praxis auftretenden Regelprobleme zeichnen sich durch einen mehr oder weniger ausgeprägten nichtlinearen Charakter aus. In manchen Fällen genügt die Anwendung linearer Regelverfahren. In vielen anderen Fällen kann befriedigendes Regelverhalten lediglich durch Einsatz nichtlinearer Methoden erreicht werden. In den vergangenen Jahrzehnten sind auf dem Gebiet der nichtlinearen Regelung ausgereifte Methoden zur Bearbeitung praktischer nichtlinearer Regelungsprobleme entwickelt worden.|
Diese Vorlesung versteht sich als Einführung in das Gebiet der nichtlinearen Systemen und Regelung. Es werden keine Grundkenntnisse in nichtlinearer Regelung vorausgesetzt. Es wird aber angenommen, dass die Hörer mit Grundkonzepten der linearen Regelung vertraut sind, wie sie zum Beispiel im Kernfach "Regelsysteme" vermittelt werden.
|Skript||Ein Skript in englischer Sprache wird während der Vorlesung auf dem Homepage zur Verfügung gestellt.|
|Literatur||H.K. Khalil: Nonlinear Systems, Prentice Hall, 2001.|
|Voraussetzungen / Besonderes||Voraussetzungen: Regelsysteme oder äquivalente Vorlesung.|
|227-0221-00L||Model Predictive Control |
Eintrag auf Einschreibeliste erforderlich (siehe "Besonderes").
|W||6 KP||4G||M. Morari|
|Kurzbeschreibung||System complexity and demanding performance render traditional control inadequate. Applications from the process industry to the communications sector increasingly use MPC. The last years saw tremendous progress in this interdisciplinary area. The course first gives an overview of basic concepts and then uses them to derive MPC algorithms. There are exercises and invited speakers from industry.|
|Lernziel||Increased system complexity and more demanding performance requirements have rendered traditional control laws inadequate regardless if simple PID loops are considered or robust feedback controllers designed according to some H2/infinity criterion. Applications ranging from the process industries to the automotive and the communications sector are making increased use of Model Predictive Control (MPC), where a fixed control law is replaced by on-line optimization performed over a receding horizon. The advantage is that MPC can deal with almost any time-varying process and specifications, limited only by the availability of real-time computer power.|
In the last few years we have seen tremendous progress in this interdisciplinary area where fundamentals of systems theory, computation and optimization interact. For example, methods have emerged to handle hybrid systems, i.e. systems comprising both continuous and discrete components. Also, it is now possible to perform most of the computations off-line thus reducing the control law to a simple look-up table.
The first part of the course is an overview of basic concepts of system theory and optimization, including hybrid systems and multi-parametric programming. In the second part we show how these concepts are utilized to derive MPC algorithms and to establish their properties. On the last day, speakers from various industries talk about a wide range of applications where MPC was used with great benefit.
There will be exercise sessions throughout the course where the students can test their understanding of the material. We will make use of the MPC Toolbox for Matlab that is distributed by MathWorks.
Day 1: Linear Systems I
Fundamentals of linear system theory – Review (system representations, poles, zeros, stability, controllability & observability, stochastic system descriptions, modeling of noise).
Day 2: Linear Systems II
Optimal control and filtering for linear systems (linear quadratic regulator, linear observer, Kalman Filter, separation principle, Riccati Difference Equation).
Days 3 and 4: Basics on Optimization
Fundamentals of optimization (linear programming, quadratic programming, mixed integer linear/quadratic programming, duality theory, KKT conditions, constrained optimization solvers).
Day 5: Introduction to MPC
MPC – concept and formulation, finite horizon optimal control, receding horizon control, stability and feasibility, computation.
Day 6: Numerical methods for MPC
Unconstrained Optimization, Constrained Optimization, Software applications
Day 7: Practical Aspects, Explicit & Hybrid MPC
- Reference tracking and soft constraints
- Explicit solution to MPC for linear constrained systems. Motivation. Introduction to (multi)-parametric programming through a simple example. Multi-parametric linear and quadratic programming: geometric algorithm. Formulation of MPC for linear constrained systems as a multi-parametric linear/quadratic program. A brief introduction to Multi-parametric Toolbox.
- MPC for discrete-time hybrid systems. Introduction to hybrid systems. Models of hybrid systems (MLD, DHA, PWA, etc.). Equivalence between different models. Modelling using HYSDEL. MLD systems. MPC based on MILP/MIQP. Explicit solution: mpMILP. Short introduction into dynamic programming (DP). Computation of the explicit MPC for PWA systems based on DP. Exercises.
Day 8: Applications
Invited speakers from industry and academia, different case studies
|Skript||Script / lecture notes will be provided.|
|Voraussetzungen / Besonderes||Prerequisites:|
One semester course on automatic control, Matlab, linear algebra.
As participation is limited, a reservation (e-mail: firstname.lastname@example.org) is required. Please give information on your "Studienrichtung", semester, institute, etc.
After your reservation has been confirmed, please register online at www.mystudies.ethz.ch.
Interested persons from outside ETH:
It is not possible/needed to enrol as external auditor for this course. Please contact Alain Bolle to register for the course (email@example.com).
We have only a limited number of places in the course, it is "first come, first served"!
|227-0418-00L||Algebra and Error Correcting Codes||W||6 KP||4G||H.‑A. Loeliger|
|Kurzbeschreibung||The course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course is also an introduction to "abstract" algebra and some of its applications in coding and signal processing.|
|Lernziel||The course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course is also an introduction to "abstract" algebra and some of its applications in coding and signal processing.|
|Inhalt||Coding: coding and modulation, linear codes, Hamming space codes, Euclidean space codes, trellises and Viterbi decoding, convolutional codes, factor graphs and message passing algorithms, low-density parity check codes, turbo codes, polar codes, Reed-Solomon codes.|
Algebra: groups, rings, homomorphisms, ideals, fields, finite fields, vector spaces, polynomials, Chinese Remainder Theorem.
|Skript||Lecture Notes (english)|
|227-0420-00L||Information Theory II||W||6 KP||2V + 2U||S. M. Moser|
|Kurzbeschreibung||This course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory.|
|Lernziel||The course has two objectives: to introduce the students to the key information theoretic results that underlay the design of communication systems and to equip the students with the tools that are needed to conduct research in Information Theory.|
|Inhalt||Differential entropy, maximum entropy, the Gaussian channel and water filling, the entropy-power inequality, Sanov's Theorem, Fisher information, the broadcast channel, the multiple-access channel, Slepian-Wolf coding, and the Gelfand-Pinsker problem.|
|Literatur||T.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006|
|227-0434-00L||Harmonic Analysis: Theory and Applications in Advanced Signal Processing||W||6 KP||2V + 2U||H. Bölcskei|
|Kurzbeschreibung||This course is an introduction to the field of applied harmonic analysis with emphasis on applications in signal processing such as transform coding, inverse problems, imaging, signal recovery, and inpainting. We will consider theoretical, applied, and algorithmic aspects.|
|Lernziel||This course is an introduction to the field of applied harmonic analysis with emphasis on applications in signal processing such as transform coding, inverse problems, imaging, signal recovery, and inpainting. We will consider theoretical, applied, and algorithmic aspects.|
|Inhalt||Frame theory: Frames in finite-dimensional spaces, frames for Hilbert spaces, sampling theorems as frame expansions|
Spectrum-blind sampling: Sampling of multi-band signals with known support set, density results by Beurling and Landau, unknown support sets, multi-coset sampling, the modulated wideband converter, reconstruction algorithms
Sparse signals and compressed sensing: Uncertainty principles, recovery of sparse signals with unknown support set, recovery of sparsely corrupted signals, orthogonal matching pursuit, basis pursuit, the multiple measurement vector problem
High-dimensional data and dimension reduction: Random projections, the Johnson-Lindenstrauss Lemma, the Restricted Isometry Property, concentration inequalities, covering numbers, Kashin widths
|Skript||Lecture notes, problem sets with documented solutions.|
|Literatur||S. Mallat, ''A wavelet tour of signal processing: The sparse way'', 3rd ed., Elsevier, 2009|
I. Daubechies, ''Ten lectures on wavelets'', SIAM, 1992
O. Christensen, ''An introduction to frames and Riesz bases'', Birkhäuser, 2003
K. Gröchenig, ''Foundations of time-frequency analysis'', Springer, 2001
M. Elad, ''Sparse and redundant representations -- From theory to applications in signal and image processing'', Springer, 2010
|Voraussetzungen / Besonderes||The course is heavy on linear algebra, operator theory, and functional analysis. A solid background in these areas is beneficial. We will, however, try to bring everybody on the same page in terms of the mathematical background required, mostly through reviews of the mathematical basics in the discussion sessions. Moreover, the lecture notes contain detailed material on the advanced mathematical concepts used in the course. If you are unsure about the prerequisites, please contact C. Aubel or H. Bölcskei.|
|227-0438-00L||Fundamentals of Wireless Communication |
Findet dieses Semester nicht statt.
|W||6 KP||2V + 2U||H. Bölcskei|
|Kurzbeschreibung||The class focuses on fundamental communication-theoretic aspects of modern wireless communication systems. The main topics covered are the system-theoretic characterization of wireless channels, the principle of diversity, information theoretic aspects of communication over fading channels, and the basics of multi-user communication theory and cellular systems.|
|Lernziel||After attending this lecture, participating in the discussion sessions, and working on the homework problem sets, students should be able to|
- understand the nature of the fading mobile radio channel and its implications for the design of communication systems
- analyze existing communication systems
- apply the fundamental principles to new wireless communication systems, especially in the design of diversity techniques and coding schemes
|Inhalt||The goal of this course is to study the fundamental principles of wireless communication, enabling students to analyze and design current and future wireless systems. The outline of the course is as follows:|
What differentiates wireless communication from wired communication is the nature of the communication channel. Motion of the transmitter and the receiver, the environment, multipath propagation, and interference render the channel model more complex. This part of the course deals with modeling issues, i.e., the process of finding an accurate and mathematically tractable formulation of real-world wireless channels. The model will turn out to be that of a randomly time-varying linear system. The statistical characterization of such systems is given by the scattering function of the channel, which in turn leads us to the definition of key propagation parameters such as delay spread and coherence time.
In a wireless channel, the time varying destructive and constructive addition of multipath components leads to signal fading. The result is a significant performance degradation if the same signaling and coding schemes as for the (static) additive white Gaussian noise (AWGN) channel are used. This problem can be mitigated by diversity techniques. If several independently faded copies of the transmitted signal can be combined at the receiver, the probability of all copies being lost--because the channel is bad--decreases. Hence, the performance of the system will be improved. We will look at different means to achieve diversity, namely through time, frequency, and space. Code design for fading channels differs fundamentally from the AWGN case. We develop criteria for designing codes tailored to wireless channels. Finally, we ask the question of how much diversity can be obtained by any means over a given wireless channel.
Information Theory of Wireless Channels
Limited spectral resources make it necessary to utilize the available bandwidth to its maximum extent. Information theory answers the fundamental question about the maximum rate that can reliably be transmitted over a wireless channel. We introduce the basic information theoretic concepts needed to analyze and compare different systems. No prior experience with information theory is necessary.
Multiple-Input Multiple-Output (MIMO) Wireless Systems
The major challenges in future wireless communication system design are increased spectral efficiency and improved link reliability. In recent years the use of spatial (or antenna) diversity has become very popular, which is mostly due to the fact that it can be provided without loss in spectral efficiency. Receive diversity, that is, the use of multiple antennas on the receive side of a wireless link, is a well-studied subject. Driven by mobile wireless applications, where it is difficult to deploy multiple antennas in the handset, the use of multiple antennas on the transmit side combined with signal processing and coding has become known under the name of space-time coding. The use of multiple antennas at both ends of a wireless link (MIMO technology) has been demonstrated to have the potential of achieving extraordinary data rates. This chapter is devoted to the basics of MIMO wireless systems.
Cellular Systems: Multiple Access and Interference Management
This chapter deals with the basics of multi-user communication. We start by exploring the basic principles of cellular systems and then take a look at the fundamentals of multi-user channels. We compare code-division multiple-access (CDMA) and frequency-division multiple access (FDMA) schemes from an information-theoretic point of view. In the course of this comparison an important new concept, namely that of multiuser diversity, will emerge. We conclude with a discussion of the idea of opportunistic communication and by assessing this concept from an information-theoretic point of view.
|Skript||Lecture notes will be handed out during the lectures.|
|Literatur||A set of handouts covering digital communication basics and mathematical preliminaries is available on the website. For further reading, we recommend|
- J. M. Wozencraft and I. M. Jacobs, "Principles of Communication Engineering," Wiley, 1965
- A. Papoulis and S. U. Pillai, "Probability, Random Variables, and Stochastic Processes," McGraw Hill, 4th edition, 2002
- G. Strang, "Linear Algebra and its Applications," Harcourt, 3rd edition, 1988
- T.M. Cover and J. A. Thomas, "Elements of Information Theory," Wiley, 1991
|Voraussetzungen / Besonderes||This class will be taught in English. The oral exam will be in German (unless you wish to take it in English, of course).|
A prerequisite for this course is a working knowledge in digital communications, random processes, and detection theory.
|227-0558-00L||Principles of Distributed Computing||W||6 KP||2V + 2U + 1A||R. Wattenhofer|
|Kurzbeschreibung||We study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques.|
|Lernziel||Distributed computing is essential in modern computing and communications systems. Examples are on the one hand large-scale networks such as the Internet, and on the other hand multiprocessors such as your new multi-core laptop. This course introduces the principles of distributed computing, emphasizing the fundamental issues underlying the design of distributed systems and networks: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing. We will cover a fresh topic every week.|
|Inhalt||Distributed computing models and paradigms, e.g. message passing, shared memory, synchronous vs. asynchronous systems, time and message complexity, peer-to-peer systems, small-world networks, social networks, sorting networks, wireless communication, and self-organizing systems.|
Distributed algorithms, e.g. leader election, coloring, covering, packing, decomposition, spanning trees, mutual exclusion, store and collect, arrow, ivy, synchronizers, diameter, all-pairs-shortest-path, wake-up, and lower bounds
|Skript||Available. Our course script is used at dozens of other universities around the world.|
|Literatur||Lecture Notes By Roger Wattenhofer. These lecture notes are taught at about a dozen different universities through the world.|
Distributed Computing: Fundamentals, Simulations and Advanced Topics
Hagit Attiya, Jennifer Welch.
McGraw-Hill Publishing, 1998, ISBN 0-07-709352 6
Introduction to Algorithms
Thomas Cormen, Charles Leiserson, Ronald Rivest.
The MIT Press, 1998, ISBN 0-262-53091-0 oder 0-262-03141-8
Disseminatin of Information in Communication Networks
Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, Walter Unger.
Springer-Verlag, Berlin Heidelberg, 2005, ISBN 3-540-00846-2
Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes
Frank Thomson Leighton.
Morgan Kaufmann Publishers Inc., San Francisco, CA, 1991, ISBN 1-55860-117-1
Distributed Computing: A Locality-Sensitive Approach
Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8
|Voraussetzungen / Besonderes||Course pre-requisites: Interest in algorithmic problems. (No particular course needed.)|
|227-0559-00L||Seminar in Distributed Computing||W||2 KP||2S||R. Wattenhofer|
|Kurzbeschreibung||In this seminar participating students present and discuss recent research papers in the area of distributed computing. The seminar consists of algorithmic as well as systems papers in distributed computing theory, peer-to-peer computing, ad hoc and sensor networking, or multi-core computing.|
|Lernziel||In the last two decades, we have experienced an unprecedented growth in the area of distributed systems and networks; distributed computing now encompasses many of the activities occurring in today's computer and communications world. This course introduces the basics of distributed computing, highlighting common themes and techniques. We study the fundamental issues underlying the design of distributed systems: communication, coordination, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques. |
In this seminar, students present the latest work in this domain.
Seminar language: English
|Inhalt||Different each year. For details see: www.disco.ethz.ch/courses.html|
|Skript||Slides of presentations will be made available.|
The actual paper selection can be found on www.disco.ethz.ch/courses.html.
|227-0662-00L||Organic and Nanostructured Optics and Electronics||W||6 KP||4G||V. Wood|
|Kurzbeschreibung||This course examines the optical and electronic properties of excitonic materials that can be leveraged to create thin-film light emitting devices and solar cells. Laboratory sessions provide students with experience in synthesis and optical characterization of nanomaterials as well as fabrication and characterization of thin film devices.|
|Lernziel||Gain the knowledge and practical experience to begin research with organic or nanostructured materials and understand the key challenges in this rapidly emerging field.|
|Inhalt||0-Dimensional Excitonic Materials (organic molecules and colloidal quantum dots)|
Energy Levels and Excited States (singlet and triplet states, optical absorption and luminescence).
Excitonic and Polaronic Processes (charge transport, Dexter and Förster energy transfer, and exciton diffusion).
Devices (photodetectors, solar cells, and light emitting devices).
|Literatur||Lecture notes and reading assignments from current literature to be posted on website.|
|Voraussetzungen / Besonderes||Course grade will be based on a final project.|
|227-0946-00L||Molecular Imaging - Basic Principles and Biomedical Applications||W||2 KP||2V||M. Rudin|
|Kurzbeschreibung||Concept: What is molecular imaging.|
Discussion/comparison of the various imaging modalities used in molecular imaging.
Design of target specific probes: specificity, delivery, amplification strategies.
|Lernziel||Molecular Imaging is a rapidly emerging discipline that translates concepts developed in molecular biology and cellular imaging to in vivo imaging in animals and ultimatly in humans. Molecular imaging techniques allow the study of molecular events in the full biological context of an intact organism and will therefore become an indispensable tool for biomedical research.|
|Inhalt||Concept: What is molecular imaging.|
Discussion/comparison of the various imaging modalities used in molecular imaging.
Design of target specific probes: specificity, delivery, amplification strategies.
|227-0974-00L||TNU Colloquium||W||0 KP||2K||K. Stephan|
|Kurzbeschreibung||This colloquium for MSc and PhD students at D-ITET discusses current research topics in Translational Neuromodeling, a new discipline concerned with the development of mathematical models for diagnostics of brain diseases. The range of topics is broad, incl. statistics and computational modeling, experimental paradigms (fMRI, EEG, behaviour), and clinical questions.|
|252-0312-00L||Ubiquitous Computing||W||3 KP||2V||F. Mattern|
|Kurzbeschreibung||Ubiquitous computing integrates tiny wirelessly connected computers and sensors into the environment and everyday objects. Main topics: The vision of ubiquitous computing, trends in technology, smart cards, RFID, Personal Area Networks (Bluetooth), sensor networks, location awareness, privacy and security, application areas, economic and social impact.|
|Lernziel||The vision of ubiquitous computing, trends in technology, smart cards, RFID, Personal Area Networks (Bluetooth), sensor networks, location awareness, privacy and security, application areas, economic and social impact.|
|Skript||Copies of slides will be made available|
|Literatur||Will be provided in the lecture. To put you in the mood:|
Mark Weiser: The Computer for the 21st Century. Scientific American, September 1991, pp. 94-104
|252-0407-00L||Cryptography||W||7 KP||3V + 2U + 1A||U. Maurer|
|Kurzbeschreibung||Fundamentals and applications of cryptography. Cryptography as a mathematical discipline: reductions, constructive cryptography paradigm, security proofs. The discussed primitives include cryptographic functions, pseudo-randomness, symmetric encryption and authentication, public-key encryption, key agreement, and digital signature schemes. Selected cryptanalytic techniques.|
|Lernziel||The goals are:|
(1) understand the basic theoretical concepts and scientific thinking in cryptography;
(2) understand and apply some core cryptographic techniques and security proof methods;
(3) be prepared and motivated to access the scientific literature and attend specialized courses in cryptography.
|Inhalt||See course description.|
|Voraussetzungen / Besonderes||Familiarity with the basic cryptographic concepts as treated for|
example in the course "Information Security" is required but can
in principle also be acquired in parallel to attending the course.
|402-0577-00L||Quantum Systems for Information Technology||W||8 KP||2V + 2U||A. Wallraff|
|Kurzbeschreibung||Introduction to experimental quantum information processing (QIP). Quantum bits. Coherent Control. Quantum Measurement. Decoherence. Microscopic and macroscopic quantum systems. Nuclear magnetic resonance (NMR) in molecules and solids. Ions and neutral atoms in electromagnetic traps. Charges and spins in quantum dots. Charges and flux quanta in superconducting circuits. Novel hybrid systems.|
|Lernziel||In recent years the realm of quantum mechanics has entered the domain of information technology. Enormous progress in the physical sciences and in engineering and technology has allowed us to envisage building novel types of information processors based on the concepts of quantum physics. In these processors information is stored in the quantum state of physical systems forming quantum bits (qubits). The interaction between qubits is controlled and the resulting states are read out on the level of single quanta in order to process information. Realizing such challenging tasks may allow constructing an information processor much more powerful than a classical computer. The aim of this class is to give a thorough introduction to physical implementations pursued in current research for realizing quantum information processors. The field of quantum information science is one of the fastest growing and most active domains of research in modern physics.|
|Inhalt||A syllabus will be provided on the class web server at the beginning of the term (see section 'Besonderes'/'Notice').|
|Skript||Electronically available lecture notes will be published on the class web server (see section 'Besonderes'/'Notice').|
|Literatur||Quantum computation and quantum information / Michael A. Nielsen & Isaac L. Chuang. Reprinted. Cambridge : Cambridge University Press ; 2001.. 676 p. : ill.. .|
Additional literature and reading material will be provided on the class web server (see section 'Besonderes'/'Notice').
|Voraussetzungen / Besonderes||The class will be taught in English language.|
Basic knowledge of quantum mechanics is required, prior knowledge in atomic physics, quantum electronics, and solid state physics is advantageous.
More information on this class can be found on the web site: http://www.qudev.ethz.ch
|» Auswahl aus sämtlichen Lehrveranstaltungen der ETH Zürich|
|227-0690-06L||Advanced Topics in Control (Spring 2015) |
New topics are introduced every year.
|W||4 KP||2V + 2U||F. Dörfler|
|Kurzbeschreibung||This class will introduce students to advanced, research level topics in the area of automatic control. Coverage varies from semester to semester, repetition for credit is possible, upon consent of the instructor. During the Spring Semester 2015 the class will concentrate on distributed systems and control.|
|Lernziel||The intent is to introduce students to advanced research level topics in the area of automatic control. The course is jointly organized by Prof. R. D'Andrea, L. Guzzella, J. Lygeros, M. Morari, R. Smith, and F. Dörfler. Coverage and instructor varies from semester to semester. Repetition for credit is possible, upon consent of the instructor. During the Spring Semester 2015 the class will be taught by F. Dörfler and will focus on distributed systems and control.|
|Inhalt||Distributed control systems include large-scale physical systems, engineered multi-agent systems, as well as their interconnection in cyber-physical systems. Representative examples are the electric power grid, camera networks, and robotic sensor networks. The challenges associated with these systems arise due to their coupled, distributed, and large-scale nature, and due to limited sensing, communication, and control capabilities. This course covers modeling, analysis, and design of distributed control systems.|
Topics covered in the course include:
- the theory of graphs (with an emphasis on algebraic and spectral graph theory);
- basic models of multi-agent and interconnected dynamical systems;
- continuous-time and discrete-time distributed averaging algorithms (consensus);
- coordination algorithms for rendezvous, formation, flocking, and deployment;
- applications in robotic coordination, coupled oscillators, social networks, sensor networks, electric power grids, epidemics, and positive systems.
|Skript||A set of self-contained set of lecture nodes will be made available on the course website.|
|Literatur||Relevant papers and books will be made available through the course website.|
|Voraussetzungen / Besonderes||Control systems (227-0216-00L), Linear system theory (227-0225-00L), or equivalents, as well as sufficient mathematical maturity.|
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