Search result: Catalogue data in Autumn Semester 2020
|Electrical Engineering and Information Technology Bachelor|
| 5th Semester: Third Year Core Courses|
Can be freely combined, a list of recommendations is available under https://ee.ethz.ch/studies/bachelor/third-year/core-courses.html
|227-0101-00L||Discrete-Time and Statistical Signal Processing||W||6 credits||4G||H.‑A. Loeliger|
|Abstract||The course introduces some fundamental topics of digital signal processing with a bias towards applications in communications: discrete-time linear filters, inverse filters and equalization, DFT, discrete-time stochastic processes, elements of detection theory and estimation theory, LMMSE estimation and LMMSE filtering, LMS algorithm, Viterbi algorithm.|
|Objective||The course introduces some fundamental topics of digital signal processing with a bias towards applications in communications. The two main themes are linearity and probability. In the first part of the course, we deepen our understanding of discrete-time linear filters. In the second part of the course, we review the basics of probability theory and discrete-time stochastic processes. We then discuss some basic concepts of detection theory and estimation theory, as well as some practical methods including LMMSE estimation and LMMSE filtering, the LMS algorithm, and the Viterbi algorithm. A recurrent theme throughout the course is the stable and robust "inversion" of a linear filter.|
|Content||1. Discrete-time linear systems and filters:|
state-space realizations, z-transform and spectrum,
decimation and interpolation, digital filter design,
stable realizations and robust inversion.
2. The discrete Fourier transform and its use for digital filtering.
3. The statistical perspective:
probability, random variables, discrete-time stochastic processes;
detection and estimation: MAP, ML, Bayesian MMSE, LMMSE;
Wiener filter, LMS adaptive filter, Viterbi algorithm.
|Lecture notes||Lecture Notes|
|227-0102-00L||Discrete Event Systems||W||6 credits||4G||L. Thiele, L. Vanbever, R. Wattenhofer|
|Abstract||Introduction to discrete event systems. We start out by studying popular models of discrete event systems. In the second part of the course we analyze discrete event systems from an average-case and from a worst-case perspective. Topics include: Automata and Languages, Specification Models, Stochastic Discrete Event Systems, Worst-Case Event Systems, Verification, Network Calculus.|
|Objective||Over the past few decades the rapid evolution of computing, communication, and information technologies has brought about the proliferation of new dynamic systems. A significant part of activity in these systems is governed by operational rules designed by humans. The dynamics of these systems are characterized by asynchronous occurrences of discrete events, some controlled (e.g. hitting a keyboard key, sending a message), some not (e.g. spontaneous failure, packet loss). |
The mathematical arsenal centered around differential equations that has been employed in systems engineering to model and study processes governed by the laws of nature is often inadequate or inappropriate for discrete event systems. The challenge is to develop new modeling frameworks, analysis techniques, design tools, testing methods, and optimization processes for this new generation of systems.
In this lecture we give an introduction to discrete event systems. We start out the course by studying popular models of discrete event systems, such as automata and Petri nets. In the second part of the course we analyze discrete event systems. We first examine discrete event systems from an average-case perspective: we model discrete events as stochastic processes, and then apply Markov chains and queuing theory for an understanding of the typical behavior of a system. In the last part of the course we analyze discrete event systems from a worst-case perspective using the theory of online algorithms and adversarial queuing.
2. Automata and Languages
3. Smarter Automata
4. Specification Models
5. Stochastic Discrete Event Systems
6. Worst-Case Event Systems
7. Network Calculus
|Literature||[bertsekas] Data Networks |
Dimitri Bersekas, Robert Gallager
Prentice Hall, 1991, ISBN: 0132009161
[borodin] Online Computation and Competitive Analysis
Allan Borodin, Ran El-Yaniv.
Cambridge University Press, 1998
[boudec] Network Calculus
J.-Y. Le Boudec, P. Thiran
[cassandras] Introduction to Discrete Event Systems
Christos Cassandras, Stéphane Lafortune.
Kluwer Academic Publishers, 1999, ISBN 0-7923-8609-4
[fiat] Online Algorithms: The State of the Art
A. Fiat and G. Woeginger
[hochbaum] Approximation Algorithms for NP-hard Problems (Chapter 13 by S. Irani, A. Karlin)
[schickinger] Diskrete Strukturen (Band 2: Wahrscheinlichkeitstheorie und Statistik)
T. Schickinger, A. Steger
Springer, Berlin, 2001
[sipser] Introduction to the Theory of Computation
PWS Publishing Company, 1996, ISBN 053494728X
|227-0103-00L||Control Systems||W||6 credits||2V + 2U||F. Dörfler|
|Abstract||Study of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems.|
|Objective||Study of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems.|
|Content||Process automation, concept of control. Modelling of dynamical systems - examples, state space description, linearisation, analytical/numerical solution. Laplace transform, system response for first and second order systems - effect of additional poles and zeros. Closed-loop control - idea of feedback. PID control, Ziegler - Nichols tuning. Stability, Routh-Hurwitz criterion, root locus, frequency response, Bode diagram, Bode gain/phase relationship, controller design via "loop shaping", Nyquist criterion. Feedforward compensation, cascade control. Multivariable systems (transfer matrix, state space representation), multi-loop control, problem of coupling, Relative Gain Array, decoupling, sensitivity to model uncertainty. State space representation (modal description, controllability, control canonical form, observer canonical form), state feedback, pole placement - choice of poles. Observer, observability, duality, separation principle. LQ Regulator, optimal state estimation.|
|Literature||K. J. Aström & R. Murray. Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press, 2010.|
R. C. Dorf and R. H. Bishop. Modern Control Systems. Prentice Hall, New Jersey, 2007.
G. F. Franklin, J. D. Powell, and A. Emami-Naeini. Feedback Control of Dynamic Systems. Addison-Wesley, 2010.
J. Lunze. Regelungstechnik 1. Springer, Berlin, 2014.
J. Lunze. Regelungstechnik 2. Springer, Berlin, 2014.
|Prerequisites / Notice||Prerequisites: Signal and Systems Theory II. |
MATLAB is used for system analysis and simulation.
|227-0110-00L||Advanced Electromagnetic Waves||W||6 credits||2V + 2U||P. Leuchtmann, U. Koch|
|Abstract||This course provides advanced knowledge of electromagnetic waves in linear materials including negative index and other non classical materials.|
|Objective||The behavior of electromagnetic waves both in free space and in selected environments including stratified media, material interfaces and waveguides is understood. Material models in the time harmonic regime including negative index and plasmonic materials are clarified.|
|Content||Description of generic time harmonic electromagnetic fields; the role of the material in Maxwell's equations; energy transport and power loss mechanism; EM-waves in homogeneous space: ordinary and evanescent plane waves, cylindrical and spherical waves, "complex origin"-waves and beams; Scattering at coated surfaces; EM-waves in stratified media; generic guiding mechanism for EM waves; classical wave guides, dielectric wave guides.|
|Lecture notes||A script including animated wave representations as well as the view graphs are provided in electronic form.|
|Literature||See literature list in the script.|
|Prerequisites / Notice||The lecture is taught in German while both the script and the view graphs are in English.|
|227-0112-00L||High-Speed Signal Propagation |
Does not take place this semester.
|W||6 credits||2V + 2U||C. Bolognesi|
|Abstract||Understanding of high-speed signal propagation in microwave cables and integrated circuits and printed circuit boards. |
As clock frequencies rise in the GHz domain, there is a need grasp signal propagation to maintain good signal integrity in the face of symbol interference and cross-talk.
The course is of high value to all interested in high-speed analog (RF, microwave) or digital systems.
|Objective||Understanding of high-speed signal propagation in interconnects, microwave cables and integrated transmission lines such as microwave integrated circuits and/or printed circuit boards.|
As system clock frequencies continuously rise in the GHz domain, a need urgently develops to understand high-speed signal propagation in order to maintain good signal integrity in the face of phenomena such as inter-symbol interference (ISI) and cross-talk.
Concepts such as Scattering parameters (or S-parameters) are key to the characterization of networks over wide bandwidths. At high frequencies, all structures effectively become "transmission lines." Unless care is taken, it is highly probable that one ends-up with a bad transmission line that causes the designed system to malfunction.
Filters will also be considered because it turns out that some of the problems associated by lossy transmission channels (lines, cables, etc) can be corrected by adequate filtering in a process called "equalization."
|Content||Transmission line equations of the lossless and lossy TEM-transmission line. Introduction of current and voltage waves. Representation of reflections in the time and frequency domain. Application of the Smith chart. Behavior of low-loss transmission lines. Attenuation and impulse distortion due to skin effect. Transmission line equivalent circuits. Group delay and signal dispersion. Coupled transmission lines. Scattering parameters.|
Butterworth-, Chebychev- and Bessel filter approximations: filter synthesis from low-pass filter prototypes.
|Lecture notes||Script: Leitungen und Filter (In German).|
|Prerequisites / Notice||Exercises will be held in English.|
|227-0113-00L||Power Electronics||W||6 credits||4G||J. W. Kolar|
|Abstract||Fields of application of power electronic systems. Principle of operation of basic pulse-width modulated and line-commutated power electronic converters, analysis of the operating behavior and of the control oriented behavior, converter design. Reduction of effects of line-commutated rectifiers on the mains, electromagnetic compatibility.|
|Objective||Fields of application of power electronic systems. Principle of operation of basic pulse-width modulated and line-commutated power electronic converters, analysis of the operating behavior and of the controloriented behavior, converter design. Reduction of effects of line-commutated rectifiers on the mains, electromagnetic compatibility.|
|Content||Basic structure of power electronic systems, applications. DC/DC converters, high frequency isolation, control oriented modeling / state-space averaging and PWM switch model. Power semiconductors, non-idealities, cooling. Magnetic components, skin and proximity effect, design. Electromagnetic compatibility. Single-phase diode bridge with capacitive smoothing, effects on the mains, power factor correction / PWM rectifier. Pulse-width modulated single-phase and three-phase full bridge converter with impressed DC voltage, modulation schemes, space vector calculus. Line-commutated single-phase full bridge with impressed output current, commutation, phase-control, inverter operation, commutation failure. Line-commutated three-phase full bridge converter, impressed output voltage, impressed output current / phase-control. Parallel connection of three-phase line-commutated thyristor circuits, inter-phase transformer. Anti-parallel connection of three-phase line-commutated thyristor bridge circuits, four-quadrant DC motor drive. Load-resonant converters, state plane analysis.|
|Lecture notes||Lecture notes and associated exercises including correct answers, simulation program for interactive self-learning including visualization/animation features.|
|Prerequisites / Notice||Prerequisites: Basic knowledge of electric circuit analysis and signal theory.|
|227-0116-00L||VLSI I: From Architectures to VLSI Circuits and FPGAs||W||6 credits||5G||F. K. Gürkaynak, L. Benini|
|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 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 SystemVerilog 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.
- 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.
- 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 FPGAs with SystemVerilog. They write testbenches for simulation purposes and synthesize gate-level netlists for FPGAs. Commercial EDA software by leading vendors is being used throughout.
|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.
|227-0121-00L||Communication Systems||W||6 credits||2V + 2U||A. Wittneben|
|Abstract||Information Theory, Signal Space Analysis, Baseband Transmission, Passband Transmission, Example und Channel, Data Link Layer, MAC, Example Layer 2, Layer 3, Internet|
|Objective||Introduction into the fundamentals of digital communication systems. Selected examples on the application of the fundamental principles in existing and upcoming communication systems|
|Content||Covered are the lower three layer of the OSI reference model: the physical, the data link, and the network layer. The basic terms of information theory are introduced. After this, we focus on the methods for the point to point communication, which may be addressed elegantly and coherently in the signal space. Methods for error detection and correction as well as protocols for the retransmission of perturbed data will be covered. Also the medium access for systems with shared medium will be discussed. Finally, algorithms for routing and flow control will be treated.|
The application of the basic methods will be extensively explained using existing and future wireless and wired systems.
|Lecture notes||Lecture Slides|
|Literature|| Simon Haykin, Communication Systems, 4. Auflage, John Wiley & Sons, 2001|
 Andrew S. Tanenbaum, Computernetzwerke, 3. Auflage, Pearson Studium, 2003
 M. Bossert und M. Breitbach, Digitale Netze, 1. Auflage, Teubner, 1999
|227-0124-00L||Embedded Systems||W||6 credits||4G||L. Thiele|
|Abstract||An embedded system is some combination of computer hardware and software, either fixed in capability or programmable, that is designed for a specific function or for specific functions within a larger system. The course covers theoretical and practical aspects of embedded system design and includes a series of lab sessions.|
|Objective||Understanding specific requirements and problems arising in embedded system applications.|
Understanding architectures and components, their hardware-software interfaces, the memory architecture, communication between components, embedded operating systems, real-time scheduling theory, shared resources, low-power and low-energy design as well as hardware architecture synthesis.
Using the formal models and methods in embedded system design in practical applications using the programming language C, the operating system FreeRTOS, a commercial embedded system platform and the associated design environment.
|Content||An embedded system is some combination of computer hardware and software, either fixed in capability or programmable, that is designed for a specific function or for specific functions within a larger system. For example, they are part of industrial machines, agricultural and process industry devices, automobiles, medical equipment, cameras, household appliances, airplanes, sensor networks, internet-of-things, as well as mobile devices.|
The focus of this lecture is on the design of embedded systems using formal models and methods as well as computer-based synthesis methods. Besides, the lecture is complemented by laboratory sessions where students learn to program in C, to base their design on the embedded operating systems FreeRTOS, to use a commercial embedded system platform including sensors, and to edit/debug via an integrated development environment.
Specifically the following topics will be covered in the course: Embedded system architectures and components, hardware-software interfaces and memory architecture, software design methodology, communication, embedded operating systems, real-time scheduling, shared resources, low-power and low-energy design, hardware architecture synthesis.
More information is available at https://www.tec.ee.ethz.ch/education/lectures/embedded-systems.html .
|Lecture notes||The following information will be available: Lecture material, publications, exercise sheets and laboratory documentation at https://www.tec.ee.ethz.ch/education/lectures/embedded-systems.html .|
|Literature||P. Marwedel: Embedded System Design, Springer, ISBN 978-3-319-56045-8, 2018.|
G.C. Buttazzo: Hard Real-Time Computing Systems. Springer Verlag, ISBN 978-1-4614-0676-1, 2011.
Edward A. Lee and Sanjit A. Seshia: Introduction to Embedded Systems, A Cyber-Physical Systems Approach, Second Edition, MIT Press, ISBN 978-0-262-53381-2, 2017.
M. Wolf: Computers as Components – Principles of Embedded System Design. Morgan Kaufman Publishers, ISBN 978-0-128-05387-4, 2016.
|Prerequisites / Notice||Prerequisites: Basic knowledge in computer architectures and programming.|
|227-0145-00L||Solid State Electronics and Optics||W||6 credits||4G||N. Yazdani, V. Wood|
|Abstract||"Solid State Electronics" is an introductory condensed matter physics course covering crystal structure, electron models, classification of metals, semiconductors, and insulators, band structure engineering, thermal and electronic transport in solids, magnetoresistance, and optical properties of solids.|
|Objective||Understand the fundamental physics behind the mechanical, thermal, electric, magnetic, and optical properties of materials.|
|Prerequisites / Notice||Recommended background:|
Undergraduate physics, mathematics, semiconductor devices
|227-0166-00L||Analog Integrated Circuits||W||6 credits||2V + 2U||T. Jang|
|Abstract||This course provides a foundation in analog integrated circuit design based on bipolar and CMOS technologies.|
|Objective||Integrated circuits are responsible for much of the progress in electronics in the last 50 years, particularly the revolutions in the Information and Communications Technologies we witnessed in recent years. Analog integrated circuits play a crucial part in the highly integrated systems that power the popular electronic devices we use daily. Understanding their design is beneficial to both future designers and users of such systems.|
The basic elements, design issues and techniques for analog integrated circuits will be taught in this course.
|Content||Review of bipolar and MOS devices and their small-signal equivalent circuit models; Building blocks in analog circuits such as current sources, active load, current mirrors, supply independent biasing etc; Amplifiers: differential amplifiers, cascode amplifier, high gain structures, output stages, gain bandwidth product of op-amps; stability; comparators; second-order effects in analog circuits such as mismatch, noise and offset; data converters; frequency synthesizers; switched capacitors.|
The exercise sessions aim to reinforce the lecture material by well guided step-by-step design tasks. The circuit simulator SPECTRE is used to facilitate the tasks. There is also an experimental session on op-amp measurements.
|Lecture notes||Handouts of presented slides. No script but an accompanying textbook is recommended.|
|Literature||Behzad Razavi, Design of Analog CMOS Integrated Circuits (Irwin Electronics & Computer Engineering) 1st or 2nd edition, McGraw-Hill Education|
|227-0385-10L||Biomedical Imaging||W||6 credits||5G||S. Kozerke, K. P. Prüssmann|
|Abstract||Introduction and analysis of medical imaging technology including X-ray procedures, computed tomography, nuclear imaging techniques using single photon and positron emission tomography, magnetic resonance imaging and ultrasound imaging techniques.|
|Objective||To understand the physical and technical principles underlying X-ray imaging, computed tomography, single photon and positron emission tomography, magnetic resonance imaging, ultrasound and Doppler imaging techniques. The mathematical framework is developed to describe image encoding/decoding, point-spread function/modular transfer function, signal-to-noise ratio, contrast behavior for each of the methods. Matlab exercises are used to implement and study basic concepts.|
|Content||- X-ray imaging |
- Computed tomography
- Single photon emission tomography
- Positron emission tomography
- Magnetic resonance imaging
- Ultrasound/Doppler imaging
|Lecture notes||Lecture notes and handouts|
|Literature||Webb A, Smith N.B. Introduction to Medical Imaging: Physics, Engineering and Clinical Applications; Cambridge University Press 2011|
|Prerequisites / Notice||Analysis, Linear Algebra, Physics, Basics of Signal Theory, Basic skills in Matlab programming|
|227-0393-10L||Bioelectronics and Biosensors||W||6 credits||2V + 2U||J. Vörös, M. F. Yanik, T. Zambelli|
|Abstract||The course introduces the concepts of bioelectricity and biosensing. The sources and use of electrical fields and currents in the context of biological systems and problems are discussed. The fundamental challenges of measuring biological signals are introduced. The most important biosensing techniques and their physical concepts are introduced in a quantitative fashion.|
|Objective||During this course the students will:|
- learn the basic concepts in biosensing and bioelectronics
- be able to solve typical problems in biosensing and bioelectronics
- learn about the remaining challenges in this field
|Content||L1. Bioelectronics history, its applications and overview of the field|
- Volta and Galvani dispute
- BMI, pacemaker, cochlear implant, retinal implant, limb replacement devices
- Fundamentals of biosensing
- Glucometer and ELISA
L2. Fundamentals of quantum and classical noise in measuring biological signals
L3. Biomeasurement techniques with photons
L4. Acoustics sensors
- Differential equation for quartz crystal resonance
- Acoustic sensors and their applications
L5. Engineering principles of optical probes for measuring and manipulating molecular and cellular processes
L6. Optical biosensors
- Differential equation for optical waveguides
- Optical sensors and their applications
- Plasmonic sensing
L7. Basic notions of molecular adsorption and electron transfer
- Quantum mechanics: Schrödinger equation energy levels from H atom to crystals, energy bands
- Electron transfer: Marcus theory, Gerischer theory
L8. Potentiometric sensors
- Fundamentals of the electrochemical cell at equilibrium (Nernst equation)
- Principles of operation of ion-selective electrodes
L9. Amperometric sensors and bioelectric potentials
- Fundamentals of the electrochemical cell with an applied overpotential to generate a faraday current
- Principles of operation of amperometric sensors
- Ion flow through a membrane (Fick equation, Nernst equation, Donnan equilibrium, Goldman equation)
L10. Channels, amplification, signal gating, and patch clamp Y4
L11. Action potentials and impulse propagation
L12. Functional electric stimulation and recording
- MEA and CMOS based recording
- Applying potential in liquid - simulation of fields and relevance to electric stimulation
L13. Neural networks memory and learning
|Literature||Plonsey and Barr, Bioelectricity: A Quantitative Approach (Third edition)|
|Prerequisites / Notice||The course requires an open attitude to the interdisciplinary approach of bioelectronics. |
In addition, it requires undergraduate entry-level familiarity with electric & magnetic fields/forces, resistors, capacitors, electric circuits, differential equations, calculus, probability calculus, Fourier transformation & frequency domain, lenses / light propagation / refractive index, Michaelis-Menten equation, pressure, diffusion AND basic knowledge of biology and chemistry (e.g. understanding the concepts of concentration, valence, reactants-products, etc.).
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