Search result: Catalogue data in Spring Semester 2015
|Electrical Engineering and Information Technology Master|
| Major Courses|
A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval.
| Core Subjects|
These core subjects are particularly recommended for the field of "Communications".
|227-0111-00L||Communication Electronics||W||6 credits||2V + 2U||Q. Huang|
|Abstract||Electronics for communications systems, with emphasis on realization. Low noise amplifiers, modulators and demodulators, transmit amplifiers and oscillators are discussed in the context of wireless communications. Wireless receiver, transmitter and frequency synthesizer will be described. Importance of and trade offs among sensitivity, linearity and selectivity are discussed extensively.|
|Objective||Foundation course for understanding modern electronic circuits for communication applications. We learn how theoretical communications principles are reduced to practice using transistors, switches, inductors, capacitors and resistors. The harsh environment such communication electronics will be exposed to and the resulting requirements on the sensitivity, linearity and selectivity help explain the design trade offs encountered in every circuit block found in a modern transceiver.|
|Content||Accounting for more than two trillion dollars per year, communications is one of the most important drivers for advanced economies of our time. Wired networks have been a key enabler to the internet age and the proliferation of search engines, social networks and electronic commerce, whereas wireless communications, cellular networks in particular, have liberated people and increased productivity in developed and developing nations alike. Integrated circuits that make such communications devices light weight and affordable have played a key role in the proliferation of communications. |
This course introduces our students to the key components that realize the tangible products in electronic form. We begin with an introduction to wireless communications, and describe the harsh environment in which a transceiver has to work reliably. In this context we highlight the importance of sensitivity or low noise, linearity, selectivity, power consumption and cost, that are all vital to a competitive device in such applications.
We shall review bipolar and MOS devices from a designer's prospectives, before discussing basic amplifier structures - common emitter/source, common base/gate configurations, their noise performance and linearity, impedance matching, and many other things one needs to know about a low noise amplifier.
We will discuss modulation, and the mixer that enables its implementation. Noise and linearity form an inseparable part of the discussion of its design, but we also introduce the concept of quadrature demodulator, image rejection, and the effects of mismatch on performance.
When mixers are used as a modulator the signals they receive are usually large and the natural linearity of transistors becomes insufficient. The concept of feedback will be introduced and its function as an improver of linearity studied in detail.
Amplifiers in the transmit path are necessary to boost the power level before the signal leaves an integrated circuit to drive an even more powerful amplifier (PA) off chip. Linearized pre-amplifiers will be studied as part of the transmitter.
A crucial part of a mobile transceiver terminal is the generation of local oscillator signals at the desired frequencies that are required for modulation and demodulation. Oscillators will be studied, starting from stability criteria of an electronic system, then leading to criteria for controlled instability or oscillation. Oscillator design will be discussed in detail, including that of crystal controlled oscillators which provide accurate time base.
An introduction to phase-locked loops will be made, illustrating how it links a variable frequency oscillator to a very stable fixed frequency crystal oscillator, and how phase detector, charge pump and programmable dividers all serve to realize an agile frequency synthesizer that is very stable in each frequency synthesized.
|Lecture notes||Script with slides and notes is available.|
|Prerequisites / Notice||The course Analog Integrated Circuits is recommended as preparation for this course.|
|227-0418-00L||Algebra and Error Correcting Codes||W||6 credits||4G||H.‑A. Loeliger|
|Abstract||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.|
|Objective||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.|
|Content||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.
|Lecture notes||Lecture Notes (english)|
|227-0420-00L||Information Theory II||W||6 credits||2V + 2U||S. M. Moser|
|Abstract||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.|
|Objective||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.|
|Content||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.|
|Literature||T.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006|
|227-0436-00L||Digital Communication and Signal Processing||W||6 credits||2V + 2U||A. Wittneben|
|Abstract||A comprehensive presentation of modern digital modulation, detection and synchronization schemes and relevant aspects of signal processing enables the student to analyze, simulate, implement and research the physical layer of advanced digital communication schemes. The course both covers the underlying theory and provides problem solving and hands-on experience.|
|Objective||Digital communication systems are characterized by ever increasing requirements on data rate, spectral efficiency and reliability. Due to the huge advances in very large scale integration (VLSI) we are now able to implement extremely complex digital signal processing algorithms to meet these challenges. As a result the physical layer (PHY) of digital communication systems has become the dominant function in most state-of-the-art system designs. In this course we discuss the major elements of PHY implementations in a rigorous theoretical fashion and present important practical examples to illustrate the application of the theory. In Part I we treat discrete time linear adaptive filters, which are a core component to handle multiuser and intersymbol interference in time-variant channels. Part II is a seminar block, in which the students develop their analytical and experimental (simulation) problem solving skills. After a review of major aspects of wireless communication we discuss, simulate and present the performance of novel cooperative and adaptive multiuser wireless communication systems. As part of this seminar each students has to give a 15 minute presentation and actively attends the presentations of the classmates. In Part III we cover parameter estimation and synchronization. Based on the classical discrete detection and estimation theory we develop maximum likelihood inspired digital algorithms for symbol timing and frequency synchronization.|
|Content||Part I: Linear adaptive filters for digital communication|
• Finite impulse response (FIR) filter for temporal and spectral shaping
• Wiener filters
• Method of steepest descent
• Least mean square adaptive filters
Part II: Seminar block on cooperative wireless communication
• review of the basic concepts of wireless communication
• multiuser amplify&forward relaying
• performance evaluation of adaptive A&F relaying schemes and student presentations
Part III: Parameter estimation and synchronization
• Discrete detection theory
• Discrete estimation theory
• Synthesis of synchronization algorithms
• Frequency estimation
• Timing adjustment by interpolation
|Lecture notes||Lecture notes.|
|Literature|| Oppenheim, A. V., Schafer, R. W., "Discrete-time signal processing", Prentice-Hall, ISBN 0-13-754920-2.|
 Haykin, S., "Adaptive filter theory", Prentice-Hall, ISBN 0-13-090126-1.
 Van Trees, H. L., "Detection , estimation and modulation theory", John Wiley&Sons, ISBN 0-471-09517-6.
 Meyr, H., Moeneclaey, M., Fechtel, S. A., "Digital communication receivers: synchronization, channel estimation and signal processing", John Wiley&Sons, ISBN 0-471-50275-8.
|Prerequisites / Notice||Formal prerequisites: none|
Recommended: Communication Systems or equivalent
|227-0438-00L||Fundamentals of Wireless Communication |
Does not take place this semester.
|W||6 credits||2V + 2U||H. Bölcskei|
|Abstract||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.|
|Objective||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
|Content||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.
|Lecture notes||Lecture notes will be handed out during the lectures.|
|Literature||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
|Prerequisites / Notice||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 credits||2V + 2U + 1A||R. Wattenhofer|
|Abstract||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.|
|Objective||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.|
|Content||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
|Lecture notes||Available. Our course script is used at dozens of other universities around the world.|
|Literature||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
|Prerequisites / Notice||Course pre-requisites: Interest in algorithmic problems. (No particular course needed.)|
|252-0407-00L||Cryptography||W||7 credits||3V + 2U + 1A||U. Maurer|
|Abstract||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.|
|Objective||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.
|Content||See course description.|
|Prerequisites / Notice||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.
| Recommended Subjects|
These courses are recommended, but you are free to choose courses from any other special field. Please consult your tutor.
|227-0116-00L||VLSI I: From Architectures to VLSI Circuits and FPGAs||W||7 credits||5G||H. Kaeslin, N. Felber|
|Abstract||This first course in a series that extends over three consecutive terms is concerned with tailoring algorithms and with devising high performance hardware architectures for their implementation as ASIC or with FPGAs. The focus is on front end design using HDLs and automatic synthesis for producing industrial-quality circuits.|
|Objective||Understand Very-Large-Scale Integrated Circuits (VLSI chips), Application-Specific Integrated Circuits (ASIC), and Field-Programmable Gate-Arrays (FPGA). Know their organization and be able to identify suitable application areas. Become fluent in front-end design from architectural conception to gate-level netlists. How to model digital circuits with VHDL or SystemVerilog. How to ensure they behave as expected with the aid of simulation, testbenches, and assertions. How to take advantage of automatic synthesis tools to produce industrial-quality VLSI and FPGA circuits. Gain practical experience with the hardware description language VHDL and with industrial Electronic Design Automation (EDA) tools.|
|Content||This course is concerned with system-level issues of VLSI design and FPGA implementations. Topics include:|
- Overview on design methodologies and fabrication depths.
- Levels of abstraction for circuit modeling.
- Organization and configuration of commercial field-programmable components.
- VLSI and FPGA design flows.
- Dedicated and general purpose architectures compared.
- How to obtain an architecture for a given processing algorithm.
- Meeting throughput, area, and power goals by way of architectural transformations.
- Hardware Description Languages (HDL) and the underlying concepts.
- VHDL and SystemVerilog compared.
- VHDL (IEEE standard 1076) for simulation and synthesis.
- A suitable nine-valued logic system (IEEE standard 1164).
- Register Transfer Level (RTL) synthesis and its limitations.
- Building blocks of digital VLSI circuits.
- Functional verification techniques and their limitations.
- Modular and largely reusable testbenches.
- Assertion-based verification.
- Synchronous versus asynchronous circuits.
- The case for synchronous circuits.
- Periodic events and the Anceau diagram.
- Case studies, ASICs compared to microprocessors, DSPs, and FPGAs.
During the exercises, students learn how to model digital ICs with VHDL. They write testbenches for simulation purposes and synthesize gate-level netlists for VLSI chips and FPGAs. Only commercial EDA software by leading vendors is being used.
|Lecture notes||Textbook and all further documents in English.|
|Literature||H. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303.|
|Prerequisites / Notice||Prerequisites: |
Basics of digital circuits.
In written form following the course semester (spring term). Problems are given in English, answers will be accepted in either English oder German.
|227-0148-00L||VLSI III: Test and Fabrication of VLSI Circuits||W||6 credits||4G||N. Felber, H. Kaeslin|
|Abstract||This last course in our VLSI series is concerned with the manufacturing of integrated circuits (IC) in CMOS technology, with defects that may occur during the process, and ---above all--- with the methods and tools for detecting design flaws and fabrication defects.|
|Objective||Know how to apply methods, software tools and equipment for designing testable VLSI circuits, for testing fabricated ICs, and for physical analysis in the occurrence of defective parts. A basic understanding of modern semiconductor technologies.|
|Content||This final course in a series of three focusses on manufacturing, testing, physical analysis, and packaging of VLSI circuits. Future prospects of micro- and nanoelectronics are also being discussed. Topics include: |
- Effects of fabrication defects.
- Abstraction from physical to transistor- and gate-level fault models.
- Fault grading in the occurrence of large ASICs.
- Generation of efficient test vector sets.
- Enhancement of testability with built-in self test.
- Organisation and application of automated test equipment.
- Physical analysis of devices.
- Packaging problems and solutions.
- Today's nanometer CMOS fabrication processes (HKMG).
- Optical and post optical Photolithography.
- Potential alternatives to CMOS technology and MOSFET devices.
- Evolution paths for design methodology.
- Industrial roadmaps for the future evolution of semiconductor technology (ITRS).
Exercises teach students how to use CAE/CAD software and automated equipment for testing ASICs after fabrication. Students that have submitted a design for manufacturing at the end of the 7th term do so on their own circuits. Physical analysis methods with professional equipment (AFM, DLTS) complement this training.
|Lecture notes||English lecture notes.|
All written documents in English.
|Prerequisites / Notice||Prerequisites: |
Basics of digital design.
|227-0216-00L||Control Systems II||W||6 credits||4G||R. Smith|
|Abstract||Introduction to basic and advanced concepts of modern feedback control.|
|Objective||Introduction to basic and advanced concepts of modern feedback control.|
|Content||This course is designed as a direct continuation of the course "Regelsysteme" (Control Systems). The primary goal is to further familiarize students with various dynamic phenomena and their implications for the analysis and design of feedback controllers. Simplifying assumptions on the underlying plant that were made in the course "Regelsysteme" are relaxed, and advanced concepts and techniques that allow the treatment of typical industrial control problems are presented. Topics include control of systems with multiple inputs and outputs, control of uncertain systems (robustness issues), limits of achievable performance, and controller implementation issues.|
|Lecture notes||The slides of the lecture are available to download|
|Literature||Skogestad, Postlethwaite: Multivariable Feedback Control - Analysis and Design. Second Edition. John Wiley, 2005.|
|Prerequisites / Notice||Prerequisites:|
Control Systems or equivalent
|227-0366-00L||Introduction to Computational Electromagnetics||W||6 credits||4G||C. Hafner, J. Leuthold, J. Smajic|
|Abstract||An overview over the most prominent methods for the simulation of electromagnetic fields is given This includes domain methods such as finite differences and finite elements, method of moments, and boundary methods. Both time domain and frequency domain techniques are considered.|
|Objective||Overview of numerical methods for the simulation of electromagnetic fields and hands-on experiments with selected methods.|
|Content||Overview of concepts of the main numerical methods for the simulation of electromagnetic fields: Finite Difference Method, Finite Element Method, Transmission Line Matrix Method, Matrix Methods, Multipole Methods, Image Methods, Method of Moments, Integral Equation Methods, Beam Propagation Method, Mode Matching Technique, Spectral Domain Analysis, Method of Lines. Applications: Problems in electrostatic and magnetostatic, guided waves and free-space propagation problems, antennas, resonators, inhomogeneous transmissionlLines, nanotechnic, optics etc.|
|Lecture notes||Download from: http://alphard.ethz.ch/hafner/Vorles/lect.htm|
|Prerequisites / Notice||First half of the semester: lectures; second half of the semester: exercises in form of small projects|
|227-0434-00L||Harmonic Analysis: Theory and Applications in Advanced Signal Processing||W||6 credits||2V + 2U||H. Bölcskei|
|Abstract||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.|
|Objective||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.|
|Content||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
|Lecture notes||Lecture notes, problem sets with documented solutions.|
|Literature||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
|Prerequisites / Notice||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.|
|227-0441-00L||Mobile Communications: Technology and Quality of Service||W||6 credits||4G||M. Kuhn|
|Abstract||Based on an introduction to wireless communications, the lecture course covers: WLAN and cellular networks, PHY technologies, MAC schemes, mechanisms supporting QoS in wireless networks, QoS measurements and evaluation, benchmarking.|
|Objective||Introduction to mobile wireless communications, including characteristics of the wireless channel, PHY layer technologies (for example MIMO, OFDM etc.) and MAC layer schemes; comparison of different cellular standards; definition of QoS and support of QoS in wireless networks; understanding QoS measurements, their evaluation and benchmarking in cellular networks.|
|Content||- Introduction |
- Wireless channel, propagation of electromagnetic waves, antenna structures
- Mobile communication, modulation techniques, OFDM, MIMO
- Wireless networks (cellular networks, access networks)
- Wireless standards (e.g. UMTS, LTE, IEEE 802.11)
- Services in wireless networks
- Quality of service (QoS) in wireless networks (definitions, Key Performance Indicators, mechanisms used to support QoS)
- QoS measurements (e.g. voice quality, coverage, delay) and their statistical evaluation
- Benchmarking (methodology, statistical methods and models)
Weekly exercises included in the lecture
|Lecture notes||Lecture slides are available.|
|Literature||Will be announced in the lecture.|
|Prerequisites / Notice||English|
|227-0456-00L||High Frequency and Microwave Electronics I |
Does not take place this semester.
|W||6 credits||4G||C. Bolognesi|
|Abstract||Understanding of basic building blocks of microwave electronics technology, with a focus on active semiconductor devices.|
|Objective||Understanding the fundamentals of microwave electronics technology, with emphasis on active components.|
|Content||Introduction, microstrip transmission lines, matching, semiconductors, pn-junction, noise, PIN-diode and applications, Schottky diodes and detectors, bipolar transistors and heterojunction bipolar transistors, MESFET physics and properties, high-electron mobility transistors, microwave amplifiers.|
|Lecture notes||Script: Mikrowellentechnik and Mikrowellenelektronik, by Werner Bächtold|
|Prerequisites / Notice||The lectures will be held in English.|
|227-0468-00L||Analog Signal Processing and Filtering |
Suitable for Master Students as well as Doctoral Students.
This course will be offered in Autumn Semester from HS 2015 on.
It won't be offered in Spring 2016 anymore.
|W||6 credits||2V + 2U||H. Schmid|
|Abstract||This lecture provides a wide overview over analogue (mostly integrated) filters (continuous-time and discrete-time), amplifiers, and sigma-delta converters, and gives examples with sensor interfaces and class-D audio drivers. All circuits are treated using a signal-flow view. The lecture is suitable for both analog and digital designers.|
|Objective||This lecture provides a wide overview over analogue (mostly integrated) filters (continuous-time and discrete-time), amplifiers, and sigma-delta converters, and gives examples with sensor interfaces and class-D audio drivers. All these circuits are treated using a signal-flow view. The lecture is suitable for both analog and digital designers. The way the exam is done allows for the different interests of the two groups.|
The learning goal is that the students can apply signal-flow graphs and can understand the signal flow in such circuits and systems (including non-ideal effects) well enough to enable them to gain an understanding of further circuits and systems by themselves.
|Content||At the beginning, signal-flow graphs in general and driving-point signal-flow graphs in particular are introduced. We will use them during the whole term to analyze circuits and understand how signals propagate through them. The theory and CMOS implementation of active Filters is then discussed in detail using the example of Gm-C filters. Theory and implementation of opamps, current conveyors, and inductor simulators follow. The link to the practical design of circuits and systems is done with an overview over different quality measures and figures of merit used in scientific literature and datasheets. Finally, an introduction to switched-capacitor filters and circuits is given, including sensor read-out amplifiers, correlated double sampling, and chopping. These topics form the basis for the longest part of the lecture: the discussion of sigma-delta A/D and D/A converters, which are portrayed as mixed analog-digital (MAD) filters in this lecture.|
|Lecture notes||The base for these lectures are lecture notes and two or three published scientific papers. From these papers we will together develop the technical content.|
Some material is protected by password; students from ETHZ who are interested can write to email@example.com to ask for the password even if they do not attend the lecture.
|Prerequisites / Notice||Prerequisites: Recommended (but not required): Stochastic models and signal processing, Communication Electronics, Analog Integrated Circuits, Transmission Lines and Filters.|
Knowledge of the Laplace Transform (transfer functions, poles and zeros, bode diagrams, stability criteria ...) and of the main properties of linear systems is necessary.
|227-0478-00L||Acoustics II||W||6 credits||4G||K. Heutschi|
|Abstract||Advanced knowledge of the functioning and application of electro-acoustic transducers.|
|Objective||Advanced knowledge of the functioning and application of electro-acoustic transducers.|
|Content||Electrical, mechanical and acoustical analogies. Transducers, microphones and loudspeakers, acoustics of musical instruments, sound recording, sound reproduction, digital audio.|
|227-0678-00L||Speech Processing II |
"Speech Processing II" takes place for the last time in spring 2015.
|W||6 credits||2V + 2U||B. Pfister|
|Abstract||Interdisciplinary approaches to text-to-speech synthesis and speech recognition (continuation of course speech processing I).|
|Objective||In this course selected concepts and interdisciplinary approaches to text-to-speech synthesis and speech recognition are presented.|
|Content||Fundamentals of representation and application of linguistic knowledge: Introduction of the theory of formal languages, the Chomsky hierarchy, word analysis, finite state machines, parsing.|
Speech synthesis: Natural language analysis (for words and sentences), lexicon, grammar for natural language; generation of the abstract representation of pronunciation (phone sequence, accents, phrases). Additionally, the ETH text-to-speech system SVOX is discussed.
Speech recognition: The statistical approach to speech recognition with hidden Markov models is detailed: Basic algorithms (forward, Viterbi and Baum-Welch algorithm), problems of implementation, HMM training, whole vs. subword modeling, isolated word recognition, continuous speech recognition, statistical and rule-based language models.
|Lecture notes||The following textbook will be used: "Sprachverarbeitung - Grundlagen und Methoden der Sprachsynthese und Spracherkennung", B. Pfister und T. Kaufmann, Springer Verlag, ISBN: 978-3-540-75909-6|
|Prerequisites / Notice||Prerequisites: |
Speech Processing I.
|227-1032-00L||Neuromorphic Engineering II||W||6 credits||5G||T. Delbrück, G. Indiveri, S.‑C. Liu|
|Abstract||This course teaches the basics of analog chip design and layout with an emphasis on neuromorphic circuits, which are introduced in the fall semester course "Neuromorphic Engineering I".|
|Objective||Design of a neuromorphic circuit for implementation with CMOS technology.|
|Content||This course teaches the basics of analog chip design and layout with an emphasis on neuromorphic circuits, which are introduced in the autumn semester course "Neuromorphic Engineering I".|
The principles of CMOS processing technology are presented. Using a set of inexpensive software tools for simulation, layout and verification, suitable for neuromorphic circuits, participants learn to simulate circuits on the transistor level and to make their layouts on the mask level. Important issues in the layout of neuromorphic circuits will be explained and illustrated with examples. In the latter part of the semester students simulate and layout a neuromorphic chip. Schematics of basic building blocks will be provided. The layout will then be fabricated and will be tested by students during the following fall semester.
|Literature||S.-C. Liu et al.: Analog VLSI Circuits and Principles; software documentation.|
|Prerequisites / Notice||Prerequisites: Neuromorphic Engineering I strongly recommended|
|252-0526-00L||Statistical Learning Theory||W||4 credits||2V + 1U||J. M. Buhmann|
|Abstract||The course covers advanced methods of statistical learning :|
PAC learning and statistical learning theory;variational methods and optimization, e.g., maximum entropy techniques, information bottleneck, deterministic and simulated annealing; clustering for vectorial, histogram and relational data; model selection; graphical models.
|Objective||The course surveys recent methods of statistical learning. The fundamentals of machine learning as presented in the course "Introduction to Machine Learning" are expanded and in particular, the theory of statistical learning is discussed.|
|Content||# Boosting: A state-of-the-art classification approach that is sometimes used as an alternative to SVMs in non-linear classification.|
# Theory of estimators: How can we measure the quality of a statistical estimator? We already discussed bias and variance of estimators very briefly, but the interesting part is yet to come.
# Statistical learning theory: How can we measure the quality of a classifier? Can we give any guarantees for the prediction error?
# Variational methods and optimization: We consider optimization approaches for problems where the optimizer is a probability distribution. Concepts we will discuss in this context include:
* Maximum Entropy
* Information Bottleneck
* Deterministic Annealing
# Clustering: The problem of sorting data into groups without using training samples. This requires a definition of ``similarity'' between data points and adequate optimization procedures.
# Model selection: We have already discussed how to fit a model to a data set in ML I, which usually involved adjusting model parameters for a given type of model. Model selection refers to the question of how complex the chosen model should be. As we already know, simple and complex models both have advantages and drawbacks alike.
# Reinforcement learning: The problem of learning through interaction with an environment which changes. To achieve optimal behavior, we have to base decisions not only on the current state of the environment, but also on how we expect it to develop in the future.
|Lecture notes||no script; transparencies of the lectures will be made available.|
|Literature||Duda, Hart, Stork: Pattern Classification, Wiley Interscience, 2000.|
Hastie, Tibshirani, Friedman: The Elements of Statistical Learning, Springer, 2001.
L. Devroye, L. Gyorfi, and G. Lugosi: A probabilistic theory of pattern recognition. Springer, New York, 1996
|Prerequisites / Notice||Requirements: |
basic knowledge of statistics, interest in statistical methods.
It is recommended that Introduction to Machine Learning (ML I) is taken first; but with a little extra effort Statistical Learning Theory can be followed without the introductory course.
|227-0120-00L||Communication Networks||W||6 credits||4G||B. Plattner, B. L. H. Ager, P. Georgopoulos, K. A. Hummel, L. Vanbever|
|Abstract||The students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used in networks, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience.|
|Objective||The students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used to networks work, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience.|
|Prerequisites / Notice||Prerequisites: A layered model of communication systems (represented by the OSI Reference Model) has previously been introduced.|
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