Suchergebnis: Katalogdaten im Frühjahrssemester 2012

Doktorat Departement Informationstechnologie und Elektrotechnik Information
Lehrangebot Doktorat und Postdoktorat
NummerTitelTypECTSUmfangDozierende
227-0146-00LAnalog-to-Digital Converters
früher "Data Conversion Systems"
W6 KP2V + 2UQ. Huang, T. Burger
KurzbeschreibungThis course provides a thorough treatment of integrated data conversion systems from system level specifications and trade-offs, over architecture choice down to circuit implementation.
LernzielData conversion systems are substantial subparts 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 analyze and design such systems base on integrated circuits. The lecture follows a top down approach, starting at system level specification and design. Then, all necessary system components are discussed, commencing again with specifications, followed by architecture considerations and then going down to the design of the key building blocks. System components covered are active RC-filters, voltage reference, current steering and charge domain DACs, flash and folding ADCs, pipelined ADCs, and delta-sigma oversampled ADCs. Issues arising from circuit imperfections and methods for design improvement are discussed as well.
Inhalt- Introduction to data conversion systems. Fundamental specification and system design. Design trade-offs: oversampling. Dithering for linearity improvement.
- Integrated filter design: Filter specification. Approaches to filter synthesis. Passive and active RC filter implementation. Use of unit element. RC-Tuning.
- Op-amp design for active RC-filters. Op-amp feedback networks and stability analysis. Non-ideality issues. Miller amplifier. RC compensation. Noise considerations.
- Digital-to-analog converters. Reference generation: voltage, current and charge domain. Precision and performance considerations.
- Analog-to-digital converters. Basic principles and overview. Sampling circuits.
- Flash- and folding-converters. Architecture and design considerations. Building block design: comparators, folding and interpolating stages
- Pipe-lined converters. Architecture and design considerations. Error correction in 1.5b stages. Building block design: multiplying DAC stage.
- Delta-sigma-converters. Operation principle. Single loop delta-sigma converters. Stability considerations and non-idealities. 3rd order design example. Multi-stage converters.
- Clocking considerations and issues. Clock generation distribution circuits.
SkriptHandouts 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 / BesonderesIt is highly recommended to attend the course "Analog Integrated Circuits" of Prof. Huang as a preparation for this course.
227-0159-00LQuantum Transport for Engineers Information W6 KP2V + 2UM. Luisier
KurzbeschreibungThis 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.
LernzielThe 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.
InhaltThe 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
SkriptLecture slides are distributed every week and can be found at
Link
LiteraturRecommended textbook: "Electronic Transport in Mesoscopic Systems", Supriyo Datta, Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, 1997
Voraussetzungen / BesonderesBasic knowledge of semiconductor device physics and quantum mechanics
227-0207-00LNonlinear Systems and ControlW6 KP4GE. Gallestey Alvarez, A. Paice
KurzbeschreibungVermittlung von den Grundlagen für die Modellierung und Analyse von Nichtlineare Systeme,sowie eine Übersicht der verschiedene nichtlinearen Reglerentwurfsmethoden.
LernzielDie 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.
InhaltFast 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.
SkriptEin Skript in englischer Sprache wird während der Vorlesung auf dem Homepage zur Verfügung gestellt.
LiteraturH.K. Khalil: Nonlinear Systems, Prentice Hall, 2001.
Voraussetzungen / BesonderesVoraussetzungen: Regelsysteme oder äquivalente Vorlesung.
227-0221-00LModel Predictive Control Belegung eingeschränkt - Details anzeigen
Eintrag auf Einschreibeliste erforderlich (siehe "Besonderes").
W6 KP4GM. Morari
KurzbeschreibungSystem 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.
LernzielIncreased 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 the MathWorks.
InhaltTentative Program

Day 1
Fundamentals of linear system theory – Review (system representations, poles, zeros, stability, controllability & observability, stochastic system descriptions, modeling of noise).

Day 2
Optimal control and filtering for linear systems (linear quadratic regulator, linear observer, Kalman Filter, separation principle, Riccati Difference Equation).

Days 3 and 4
Fundamentals of optimization (linear programming, quadratic programming, mixed integer linear/quadratic programming, duality theory, KKT conditions, constrained optimization solvers).
Exercises.

Day 5
MPC – formulation, finite horizon optimal control, receding horizon control, stability and feasibility, computation.
Exercises.

Day 6
MPC Toolbox for Matlab: Graphical user interface and Simulink library, classroom Matlab exercises. Introduction to Multi Parametric Toolbox.

Day 7
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. Illustrative example: double integrator. Demonstration of the performance on "ball-and-plate". A brief introduction to Multi-parametric Toolbox. Exercises.

Day 8 - MPC for discrete time hybrid systems
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.


Day 9
Applications / case studies
Voraussetzungen / BesonderesPrerequisites:
One semester course on automatic control, Matlab, linear algebra.

ETH students:
As participation is limited, a reservation (e-mail: Link) is required. Please give information on your "Studienrichtung", semester, institute, etc.
After your reservation has been confirmed, please register online at Link.

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 (Link).

We have only a limited number of places in the course, it is "first come, first served"!
227-0418-00LAlgebra and Error Correcting CodesW6 KP4GH.‑A. Loeliger
KurzbeschreibungThe 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.
LernzielThe 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.
InhaltCoding: 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, Reed-Solomon codes.
Algebra: groups, rings, homomorphisms, ideals, fields, finite fields, vector spaces, polynomials, Chinese Remainder Theorem.
SkriptLecture Notes (english)
227-0420-00LInformation Theory II Information
Findet dieses Semester nicht statt.
W6 KP2V + 2UA. Lapidoth
KurzbeschreibungThis course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory.
LernzielThe 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.
InhaltDifferential 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.
Skriptn/a
LiteraturT.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006
227-0434-00LHarmonic Analysis: Theory and Applications in Advanced Signal Processing
Findet dieses Semester nicht statt.
W6 KP2V + 2UH. Bölcskei
KurzbeschreibungEinführung in die Grundlagen der harmonischen Analyse mit Anwendungen in der Signalverarbeitung und in der Informationstheorie.
LernzielEinführung in die Grundlagen der harmonischen Analyse mit Anwendungen in der Signalverarbeitung und in der Informationstheorie.
InhaltElemente der linearen Algebra, Fourier Theorie und Abtasttheoreme, Hilberträume, lineare Operatoren, Frame Theorie, Approximationstheorie, Wavelets, Kurzzeit Fourier Transformation, Gaborentwicklungen, Filterbänke, Transformationskodierung, spärliche Signale, Unschärferelationen, komprimierte Abtastung.
SkriptVorlesungsskript, Übungsaufgaben mit dokumentierten Lösungen.
LiteraturS. Mallat, "A wavelet tour of signal processing", 2n ed., Academic Press, 1999 M. Vetterli and J. Kovacevic, "Wavelets and subband coding", Prentice Hall, 1995 I. Daubechies, "Ten lectures on wavelets", SIAM, 1992 O. Christensen, "An introduction to frames and Riesz bases", Birkhäuser, 2003 M. A. Pinksy, "Introduction to Fourier analysis and wavelets", Brooks/ Cole Series in Advanced Mathematics, 2002.
227-0438-00LFundamentals of Wireless CommunicationW6 KP2V + 2UH. Bölcskei
KurzbeschreibungThe class focuses on fundamental communication-theoretic aspects of modern wireless communication systems. Main topics covered are the system-theoretic characterization of wireless channels, the principle of diversity and various diversity techniques, and information theoretic aspects of communication over fading channels like the notions of ergodic and outage capacity.
LernzielAfter attending this lecture, participating in the discussion sections 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
InhaltThe goal of this course is to study the fundamental principles of wireless communications, enabling students to analyze and design current and future wireless systems. The outline of the course is as follows:

Wireless Channels
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 parameters such as delay spread and coherence time.

Diversity
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 will 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 be reliably 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 will start by exploring the basic principles of cellular systems and then take a fundamental look at multi-user channels. We will then 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 will conclude with a discussion of the idea of opportunistic communication and by assessing this concept from an information-theoretic point of view.
SkriptA draft version of the lecture notes is available and will be handed out during the lectures
LiteraturA 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 / BesonderesThis 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.
227-0558-00LPrinciples of Distributed Computing Information W6 KP2V + 2U + 1AR. Wattenhofer
KurzbeschreibungWe 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.
LernzielDistributed 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, e.g. message passing, shared memory, multi-core, synchronous and asynchronous systems, altruistic/selfish/faulty/malicious behavior
• distributed network algorithms such as leader election, coloring, covering, packing, decomposition, spanning tree computation, and lower bounds
• distributed shared memory algorithms such as agreement or snapshot, shared objects and variables
• peer-to-peer systems, small-world networks, sorting networks, self-organizing systems
SkriptAvailable
LiteraturLecture Notes By Roger Wattenhofer

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
David Peleg.
Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8
Voraussetzungen / BesonderesCourse pre-requisites: Interest in algorithmic problems. (No particular course needed.)
227-0559-00LSeminar in Distributed Computing Information W2 KP2SR. Wattenhofer
KurzbeschreibungIn 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.
LernzielIn 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
InhaltDifferent each year. For details see: Link
SkriptSlides of presentations will be made available.
LiteraturPapers.
The actual paper selection can be found on Link.
227-0662-00LOrganic and Nanostructured Optics and Electronics Information W6 KP4GV. Wood
KurzbeschreibungThis course examines the optical and electronic properties of excitonic materials that can be leveraged to create thin-film lasers, light emitting devices, solar cells, and transistors. Laboratory sessions will provide students with experience in fabrication and characterization of devices with organic thin film active layers.
LernzielGain the knowledge and practical experience to begin research with organic or nanostructured materials and understand the key challenges in this rapidly emerging field.
InhaltExcitonic Materials (organic molecules, polymers, colloidal quantum dots, and nanowires).

Energy Levels and Excited States (phonon interactions, singlet and triplet states, optical absorption, luminescence, and lasing).

Polaronic and Excitonic Processes (charge transport, Dexter and Förster energy transfer, and exciton diffusion).

Devices (photodetectors, photovoltaics, light emitting devices, transistors, and memory cells).
LiteraturLecture notes and reading assignments from current literature to be posted on website.
Voraussetzungen / BesonderesGraded Work:
6 homework assignments
15 minute final presentation
227-0684-00LControl Methods in Systems BiologyW4 KP2V + 1UH. Köppl
KurzbeschreibungMathematical and control-theoretical methods are introduced and their application in computational systems biology discussed. For more information see Link
LernzielAfter successful completion of the course the student will be able to derive computational models from experimental facts; he will be acquainted with the basics of molecular cell biology; he will know what model formulation to chose that best fits the experimental situation.
Inhalt1. Basics of molecular cell biology.

2. Basics in probability theory.

3. Basics of nonlinear differential equations, and population models, Lyapunov stability, stoichiometric formulation, stoichiometry analysis.

4. Stochastic analysis: Markov process basics, Master equation, Omega expansions, Fokker-Planck equation, linear noise approximation, moment closures, Langevin, simulation algorithms, Gillespie, tau-leaping, SDE integration.

5. Spatial simulations: Smoluchowski diffusion model, Compartment models, spatial Gillespie, Greens functions reaction dynamics, mesh methods.

6. Parameter inference, system identification: ODE identification, Markov process inference, Markov Chain Monte Carlo methods, sequential Monte Carlo, optimal experimental design.

7. Computer science models: Petri nets, rule-based models, finite state automata, hybrid automata, boolean models.
LiteraturDarren Wilkinson (2011) Stochastic Modelling for Systems Biology, second edition, Chapman & Hall/CRC.
227-0690-03LAdvanced Topics in Control (Spring 2012) Information
New topics are introduced every year.
W4 KP2V + 2UR. Smith, P. J. Goulart
KurzbeschreibungThis 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 2012 the class will concentrate on robust control and convex optimization.
LernzielThe 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 and M. Morari. Coverage and instructor varies from semester to semester. Repetition for credit is possible, upon consent of the instructor. During the Spring Semester 2012 the class will be taught by R. Smith and P. Goulart and will focus on robust control and convex optimization.
InhaltAn optimization based approach to robust control theory and applications. Topics will include: H-infinity and H-2 control design; structured-singular value analysis and synthesis; model reduction; convex optimization; semi-definite programming; and interior-point methods.
SkriptCopies of the projection slides are available for downloading via the course website.
LiteraturRelevant papers will be made available through the course website.
Voraussetzungen / BesonderesControl systems (227-0216-00L), Linear system theory (227-0225-00L), or equivalents, as well as sufficient mathematical maturity.
227-0946-00LMolecular Imaging - Basic Principles and Biomedical ApplicationsW2 KP2VM. Rudin
KurzbeschreibungConcept: What is molecular imaging.
Discussion/comparison of the various imaging modalities used in molecular imaging.
Design of target specific probes: specificity, delivery, amplification strategies.
Biomedical Applications.
LernzielMolecular 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.
InhaltConcept: What is molecular imaging.
Discussion/comparison of the various imaging modalities used in molecular imaging.
Design of target specific probes: specificity, delivery, amplification strategies.
Biomedical Applications.
252-0312-00LUbiquitous ComputingW3 KP2VF. Mattern
KurzbeschreibungUbiquitous 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, Bluetooth, sensor networks, location awareness, application areas and business issues, privacy.
LernzielThe vision of ubiquitous computing, trends in technology, smart cards, RFID, Bluetooth, sensor networks, location awareness, application areas and business issues, privacy.
SkriptCopies of slides will be made available
LiteraturWill 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
401-3904-00LConvex Optimization Information W6 KP2V + 1UM. Baes
KurzbeschreibungThe course "Convex optimization" encompasses in a balanced manner theory (convex analysis, duality theory, optimality conditions), applications, and algorithms for convex optimization.
LernzielThe aim of this course is to give to mathematicians and practitioners an overview of useful concepts and techniques in convex optimization. A particular attention is given to convex modeling and to algorithms for solving convex optimization problems. Some exercise sessions are devoted to an initiation to a convex optimization solver.

In summary, we will discuss one of the most challenging research areas of nonlinear optimization for which there are many interesting open questions both in theory and practice.

Here is a brief syllabus of the course.
* Mathematical background (6 lectures)
Introduction, convex sets, Semidefinite cone, separation theorems,
Duality, Farkas Lemma, Optimality conditions, Lagrangian duality,
Subgradients, conjugate functions, KKT conditions and applications.

*Applications, convex modeling (3 lectures)
Conic Optimization and applications,
Applications of Semidefinite Optimization
Applications of Convex Optimization to Data Fitting and Statistical
Estimation.

*Algorithms (5 lectures)
Black-box methods, Self-concordant functions,
Interior-point methods, Primal-dual interior-point methods.
InhaltConvexity plays a central role in the design and analysis of modern and highly successful algorithms for solving real-world optimization problems. The lecture (in English) on convex optimization will treat in a balanced manner theory (convex analysis, optimality conditions), modeling issues, and algorithms for convex optimization. Beginning with basic concepts and results about the structure of convex sets, continuity and differentiability of convex functions (including conjugate functions), the lecture will cover separation theorems and their important consequences: the theory of Lagrange multipliers, the duality theory and some min-max theorems.

On the algorithmic part, the course will study some simple first and second-order algorithms, as well as some efficient interior-point methods in the framework of self-concordant functions.
SkriptThe slides of the course are available online, on the course website. An important reference book for the lecture is "S. Boyd, L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004", available online for free.
Literatur* A. Barvinok, A Course in Convexity. American Mathematical Society, 2003.
* A. Ben-Tal and A. Nemirovski, Lectures on Modern Convex Optimization - Analysis, Algorithms, and Engineering Applications, MPS-SIAM Series on Optimization, MPS-SIAM.
* D. P. Bertsekas, A. Nedic and A. E. Ozdaglar, Convex Analysis and Optimization, Athena Scientific, 2003.
* D. Bertsimas and J. N. Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, 1997.
* S. Boyd, L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004.
* S. Boyd, L. El Ghaoui, E. Feron and V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory. SIAM, 1994.
* E. de Klerk, Aspects of Semidefinite Programming: Interior Point Algorithms and Selected Applications, Book Series: APPLIED OPTIMIZATION, Vol. 65. Kluwer Academic Publishers.
* Y. Nesterov, Introductory Lectures on Convex Optimization: A Basic Course, Book Series: APPLIED OPTIMIZATION, Vol. 87. Kluwer Academic Publishers,
* R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, 1985.
* J. Renegar, A Mathematical View of Interior-Point Methods in Convex Optimization, MPS-SIAM Series on Optimization.
* H. Wolkowicz, R. Saigal and L. Vandenberghe, Handbook of Semidefinite Programming: Theory, Algorithms, and Applications, Kluwer Academic Publishers.
* A. Nemirovski and D. Yudin, Problem complexity and method efficiency in optimization, Wiley, 1983.
402-0577-00LQuantum Systems for Information TechnologyW8 KP2V + 2US. Filipp
KurzbeschreibungIntroduction 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.
LernzielIn 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.
InhaltA syllabus will be provided on the class web server at the beginning of the term (see section 'Besonderes'/'Notice').
SkriptElectronically available lecture notes will be published on the class web server (see section 'Besonderes'/'Notice').
LiteraturQuantum computation and quantum information / Michael A. Nielsen & Isaac L. Chuang. Reprinted. Cambridge : Cambridge University Press ; 2001.. 676 p. : ill.. [004153791].

Additional literature and reading material will be provided on the class web server (see section 'Besonderes'/'Notice').
Voraussetzungen / BesonderesThe 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: Link
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