# Search result: Catalogue data in Autumn Semester 2017

Electrical Engineering and Information Technology Master | ||||||

Major Courses A total of 42 CP must be achieved during the Master Program. The individual study plan is subject to the tutor's approval. | ||||||

Communication | ||||||

Core Subjects These core subjects are particularly recommended for the field of "Communication". | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |
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227-0147-00L | VLSI II: Design of Very Large Scale Integration Circuits Does not take place this semester. | W | 6 credits | 5G | L. Benini | |

Abstract | This second course in our VLSI series is concerned with how to turn digital circuit netlists into safe, testable and manufacturable mask layout, taking into account various parasitic effects. Low-power circuit design is another important topic. Economic aspects and management issues of VLSI projects round off the course. | |||||

Learning objective | Know how to design digital VLSI circuits that are safe, testable, durable, and make economic sense. | |||||

Content | The second course begins with a thorough discussion of various technical aspects at the circuit and layout level before moving on to economic issues of VLSI. Topics include: - The difficulties of finding fabrication defects in large VLSI chips. - How to make integrated circuit testable (design for test). - Synchronous clocking disciplines compared, clock skew, clock distribution, input/output timing. - Synchronization and metastability. - CMOS transistor-level circuits of gates, flip-flops and random access memories. - Sinks of energy in CMOS circuits. - Power estimation and low-power design. - Current research in low-energy computing. - Layout parasitics, interconnect delay, static timing analysis. - Switching currents, ground bounce, IR-drop, power distribution. - Floorplanning, chip assembly, packaging. - Layout design at the mask level, physical design verification. - Electromigration, electrostatic discharge, and latch-up. - Models of industrial cooperation in microelectronics. - The caveats of virtual components. - The cost structures of ASIC development and manufacturing. - Market requirements, decision criteria, and case studies. - Yield models. - Avenues to low-volume fabrication. - Marketing considerations and case studies. - Management of VLSI projects. Exercises are concerned with back-end design (floorplanning, placement, routing, clock and power distribution, layout verification). Industrial CAD tools are being used. | |||||

Lecture notes | H. Kaeslin: "Top-Down Digital VLSI Design, from Gate-Level Circuits to CMOS Fabrication", Lecture Notes Vol.2 , 2015. All written 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 | Highlight: Students are offered the opportunity to design a circuit of their own which then gets actually fabricated as a microchip! Students who elect to participate in this program register for a term project at the Integrated Systems Laboratory in parallel to attending the VLSI II course. Prerequisites: "VLSI I: from Architectures to Very Large Scale Integration Circuits and FPGAs" or equivalent knowledge. Further details: https://iis-students.ee.ethz.ch/lectures/vlsi-ii/ | |||||

227-0417-00L | Information Theory I | W | 6 credits | 4G | A. Lapidoth | |

Abstract | This course covers the basic concepts of information theory and of communication theory. Topics covered include the entropy rate of a source, mutual information, typical sequences, the asymptotic equi-partition property, Huffman coding, channel capacity, the channel coding theorem, the source-channel separation theorem, and feedback capacity. | |||||

Learning objective | The fundamentals of Information Theory including Shannon's source coding and channel coding theorems | |||||

Content | The entropy rate of a source, Typical sequences, the asymptotic equi-partition property, the source coding theorem, Huffman coding, Arithmetic coding, channel capacity, the channel coding theorem, the source-channel separation theorem, feedback capacity | |||||

Literature | T.M. Cover and J. Thomas, Elements of Information Theory (second edition) | |||||

227-0427-00L | Signal and Information Processing: Modeling, Filtering, Learning | W | 6 credits | 4G | H.‑A. Loeliger | |

Abstract | Fundamentals in signal processing, detection/estimation, and machine learning. I. Linear signal representation and approximation: Hilbert spaces, LMMSE estimation, regularization and sparsity. II. Learning linear and nonlinear functions and filters: kernel methods, neural networks. III. Structured statistical models: hidden Markov models, factor graphs, Kalman filter, parameter estimation. | |||||

Learning objective | The course is an introduction to some basic topics in signal processing, detection/estimation theory, and machine learning. | |||||

Content | Part I - Linear Signal Representation and Approximation: Hilbert spaces, least squares and LMMSE estimation, projection and estimation by linear filtering, learning linear functions and filters, L2 regularization, L1 regularization and sparsity, singular-value decomposition and pseudo-inverse, principal-components analysis. Part II - Learning Nonlinear Functions: fundamentals of learning, neural networks, kernel methods. Part III - Structured Statistical Models and Message Passing Algorithms: hidden Markov models, factor graphs, Gaussian message passing, Kalman filter and recursive least squares, Monte Carlo methods, parameter estimation, expectation maximization, sparse Bayesian learning. | |||||

Lecture notes | Lecture notes. | |||||

Prerequisites / Notice | Prerequisites: - local bachelors: course "Discrete-Time and Statistical Signal Processing" (5. Sem.) - others: solid basics in linear algebra and probability theory | |||||

227-0439-00L | Wireless Access SystemsDoes not take place this semester. | W | 6 credits | 2V + 2U | A. Wittneben | |

Abstract | Wireless access systems support locally constrained wireless connectivity and mobile access to a backbone network (typically the Internet). In this course the student develops a comprehensive understanding of existing and upcoming wireless access technologies (including WiFi, Bluetooth, RFID, NFC, VANET) and related Physical Layer and Medium Access Control Layer problems and opportunities. | |||||

Learning objective | The course consists of two tracks. The track "Technology&Systems" is structured as regular lecture. In the introduction we will discuss the challenges and potential of pervasive wireless access and study some fundamentals of short/medium range wireless communications. The main body of this track is devoted to existing and upcoming systems. A comprehensive survey of Ultrawide band (UWB) as the promising transmission technology for pervasive wireless access completes this track. In the track "Simulate&Practice" we form student teams that implement and analyze functional blocks of the physical layer of various advanced wireless access systems based on MATLAB simulations. The track includes combination tasks where different teams combine their functional blocks (e.g. transmitter, receiver) in order to simulate the complete physical layer. | |||||

Content | 1. Short range wireless communication : fundamental Physical Layer challenges and solutions 2. Wireless Local Area Network (WLAN) 3. Vehicular Networks (VANET) 4. Ultra-Wideband (UWB) technology: fundamental principles, promises and solutions 5. Wireless Body Area Networks (WBAN) 6. Wireless Personal Area Networks (Bluetooth, Zigbee) 7. Radio Frequency Identification (RFID) and Near Field Communication (NFC) | |||||

Lecture notes | Lecture Slides and handouts. | |||||

Literature | Selected Books | |||||

Prerequisites / Notice | Requirements: Knowledge of fundamental principles of digital communication systems (e.g. 227-0121-00 G Kommunikationssysteme) is helpful but not mandatory. Lecture is given in English. | |||||

Recommended Subjects These courses are recommended, but you are free to choose courses from any other special field. Please consult your tutor. | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

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. | |||||

Learning 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. | |||||

Content | 1. Introduction 2. Automata and Languages 3. Smarter Automata 4. Specification Models 5. Stochastic Discrete Event Systems 6. Worst-Case Event Systems 7. Network Calculus | |||||

Lecture notes | Available | |||||

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 Springer, 2001 [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) D. Hochbaum [schickinger] Diskrete Strukturen (Band 2: Wahrscheinlichkeitstheorie und Statistik) T. Schickinger, A. Steger Springer, Berlin, 2001 [sipser] Introduction to the Theory of Computation Michael Sipser. 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. | |||||

Learning 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. | |||||

227-0112-00L | High-Speed Signal Propagation | 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. | |||||

Learning 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 German, but assistants also speak English. | |||||

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. | |||||

Learning 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. 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. Examination: In written form following the course semester (spring term). Problems are given in English, answers will be accepted in either English oder German. Further details: https://iis-students.ee.ethz.ch/lectures/vlsi-i/ | |||||

227-0148-00L | VLSI III: Test and Fabrication of VLSI Circuits Does not take place this semester. | W | 6 credits | 4G | L. Benini | |

Abstract | In this course, we will cover how modern microchips are fabricated, and we will focus on methods and tools to uncover fabrication defects, if any, in these microchips. As part of the exercises, students will get to work on an industrial 1 million dollar automated test equipment. | |||||

Learning objective | Learn about modern IC manufacturing methodologies, understand the problem of IC testing. Cover the basic methods, algorithms and techniques to test circuits in an efficient way. Learn about practical aspects of IC testing and apply what you learn in class using a state-of-the art tester. | |||||

Content | In this course we will deal with modern integrated circuit (IC) manufacturing technology and cover topics such as: - 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). If you want to earn money by selling ICs, you will have to deliver a product that will function properly with a very large probability. The main emphasis of the lecture will be discussing how this can be achieved. We will discuss fault models and practical techniques to improve testability of VLSI circuits. At the IIS we have a state-of-the-art automated test equipment (Advantest SoC V93000) that we will make available for in class exercises and projects. At the end of the lecture you will be able to design state-of-the art digital integrated circuits such as to make them testable and to use automatic test equipment (ATE) to carry out the actual testing. During the first weeks of the course there will be weekly practical exercises where you will work in groups of two. For the last 5 weeks of the class students will be able to choose a class project that can be: - The test of their own chip developed during a previous semester thesis - Developing new setups and measurement methods in C++ on the tester - Helping to debug problems encountered in previous microchips by IIS. Half of the oral exam will consist of a short presentation on this class project. | |||||

Lecture notes | Main course book: "Essentials of Electronic Testing for Digital, Memory and Mixed-Signal VLSI Circuits" by Michael L. Bushnell and Vishwani D. Agrawal, Springer, 2004. This book is available online within ETH through http://link.springer.com/book/10.1007%2Fb117406 | |||||

Prerequisites / Notice | Although this is the third part in a series of lectures on VLSI design, you can follow this course even if you have not visited VLSI I and VLSI II lectures. An interest in integrated circuit design, and basic digital circuit knowledge is required though. Course website: https://iis-students.ee.ethz.ch/lectures/vlsi-iii/ | |||||

227-0166-00L | Analog Integrated Circuits | W | 6 credits | 2V + 2U | Q. Huang | |

Abstract | This course provides a foundation in analog integrated circuit design based on bipolar and CMOS technologies. | |||||

Learning 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; A/D and D/A converters; Introduction to switched capacitor circuits. 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 measurments. | |||||

Lecture notes | Handouts of presented slides. No script but an accompanying textbook is recommended. | |||||

Literature | Gray, Hurst, Lewis, Meyer, "Analysis and Design of Analog Integrated Circuits", 5th Ed. Wiley, 2010. | |||||

227-0301-00L | Optical Communication Fundamentals | W | 6 credits | 2V + 1U + 1P | J. Leuthold | |

Abstract | The path of an analog signal in the transmitter to the digital world in a communication link and back to the analog world at the receiver is discussed. The lecture covers the fundamentals of all important optical and optoelectronic components in a fiber communication system. This includes the transmitter, the fiber channel and the receiver with the electronic digital signal processing elements. | |||||

Learning objective | An in-depth understanding on how information is transmitted from source to destination. Also the mathematical framework to describe the important elements will be passed on. Students attending the lecture will further get engaged in critical discussion on societal, economical and environmental aspects related to the on-going exponential growth in the field of communications. | |||||

Content | * Chapter 1: Introduction: Analog/Digital conversion, The communication channel, Shannon channel capacity, Capacity requirements. * Chapter 2: The Transmitter: Components of a transmitter, Lasers, The spectrum of a signal, Optical modulators, Modulation formats. * Chapter 3: The Optical Fiber Channel: Geometrical optics, The wave equations in a fiber, Fiber modes, Fiber propagation, Fiber losses, Nonlinear effects in a fiber. * Chapter 4: The Receiver: Photodiodes, Receiver noise, Detector schemes (direct detection, coherent detection), Bit-error ratios and error estimations. * Chapter 5: Digital Signal Processing Techniques: Digital signal processing in a coherent receiver, Error detection teqchniques, Error correction coding. * Chapter 6: Pulse Shaping and Multiplexing Techniques: WDM/FDM, TDM, OFDM, Nyquist Multiplexing, OCDMA. * Chapter 7: Optical Amplifiers : Semiconductor Optical Amplifiers, Erbium Doped Fiber Amplifiers, Raman Amplifiers. | |||||

Lecture notes | Lecture notes are handed out. | |||||

Literature | Govind P. Agrawal; "Fiber-Optic Communication Systems"; Wiley, 2010 | |||||

Prerequisites / Notice | Fundamentals of Electromagnetic Fields & Bachelor Lectures on Physics. | |||||

227-0377-00L | Physics of Failure and Failure Analysis of Electronic Devices and Equipment | W | 3 credits | 2V | U. Sennhauser | |

Abstract | Failures have to be avoided by proper design, material selection and manufacturing. Properties, degradation mechanisms, and expected lifetime of materials are introduced and the basics of failure analysis and analysis equipment are presented. Failures will be demonstrated experimentally and the opportunity is offered to perform a failure analysis with advanced equipment in the laboratory. | |||||

Learning objective | Introduction to the degradation and failure mechanisms and causes of electronic components, devices and systems as well as to methods and tools of reliability testing, characterization and failure analysis. | |||||

Content | Summary of reliability and failure analysis terminology; physics of failure: materials properties, physical processes and failure mechanisms; failure analysis of ICs, PCBs, opto-electronics, discrete and other components and devices; basics and properties of instruments; application in circuit design and reliability analysis | |||||

Lecture notes | Comprehensive copy of transparencies | |||||

227-0447-00L | Image Analysis and Computer Vision | W | 6 credits | 3V + 1U | L. Van Gool, O. Göksel, E. Konukoglu | |

Abstract | Light and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation and deformable shape matching. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition. | |||||

Learning objective | Overview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises. | |||||

Content | The first part of the course starts off from an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First it is investigated how the parameters of the electromagnetic waves are related to our perception. Also the interaction of light with matter is considered. The most important hardware components of technical vision systems, such as cameras, optical devices and illumination sources are discussed. The course then turns to the steps that are necessary to arrive at the discrete images that serve as input to algorithms. The next part describes necessary preprocessing steps of image analysis, that enhance image quality and/or detect specific features. Linear and non-linear filters are introduced for that purpose. The course will continue by analyzing procedures allowing to extract additional types of basic information from multiple images, with motion and depth as two important examples. The estimation of image velocities (optical flow) will get due attention and methods for object tracking will be presented. Several techniques are discussed to extract three-dimensional information about objects and scenes. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed. | |||||

Lecture notes | Course material Script, computer demonstrations, exercises and problem solutions | |||||

Prerequisites / Notice | Prerequisites: Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Linux and C. The course language is English. | |||||

227-0455-00L | Terahertz: Technology & ApplicationsDoes not take place this semester. | W | 3 credits | 2V | K. Sankaran | |

Abstract | This course will provide a solid foundation for understanding physical principles of THz applications. We will discuss various building blocks of THz technology - components dealing with generation, manipulation, and detection of THz electromagnetic radiation. We will introduce THz applications in the domain of imaging, communications, and energy harvesting. | |||||

Learning objective | This is an introductory course on Terahertz (THz) technology and applications. Devices operating in THz frequency range (0.1 to 10 THz) have been increasingly studied in the recent years. Progress in nonlinear optical materials, ultrafast optical and electronic techniques has strengthened research in THz application developments. Due to unique interaction of THz waves with materials, applications with new capabilities can be developed. In theory, they can penetrate somewhat like X-rays, but are not considered harmful radiation, because THz energy level is low. They should be able to provide resolution as good or better than magnetic resonance imaging (MRI), possibly with simpler equipment. Imaging, very-high bandwidth communication, and energy harvesting are the most widely explored THz application areas. We will study the basics of THz generation, manipulation, and detection. Our emphasis will be on the physical principles and applications of THz in the domain of imaging, communication and energy harvesting. | |||||

Content | INTRODUCTION Chapter 1: Introduction to THz Physics Chapter 2: Components of THz Technology THz TECHNOLOGY MODULES Chapter 3: THz Generation Chapter 4: THz Detection Chapter 5: THz Manipulation APPLICATIONS Chapter 6: THz Imaging Chapter 7: THz Communication Chapter 8: THz Energy Harvesting | |||||

Literature | - Yun-Shik Lee, Principles of Terahertz Science and Technology, Springer 2009 - Ali Rostami, Hassan Rasooli, and Hamed Baghban, Terahertz Technology: Fundamentals and Applications, Springer 2010 Whenever we deviate from the main material discussed in these books, softcopy of lectures notes will be provided. | |||||

Prerequisites / Notice | Good foundation in electromagnetics & knowledge of microwave or optical communication is helpful. | |||||

227-0468-00L | Analog Signal Processing and Filtering Suitable for Master Students as well as Doctoral Students. | W | 6 credits | 2V + 2U | H. Schmid | |

Abstract | This lecture provides a wide overview over analog filters (continuous-time and discrete-time), signal-processing systems, and sigma-delta conversion, and gives examples with sensor interfaces and class-D audio drivers. All systems and circuits are treated using a signal-flow view. The lecture is suitable for both analog and digital designers. | |||||

Learning objective | This lecture provides a wide overview over analog filters (continuous-time and discrete-time), signal-processing systems, and sigma-delta conversion, and gives examples with sensor interfaces and class-D audio drivers. All systems and 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 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 and active-RC filters. The ideal and nonideal behaviour of opamps, current conveyors, and inductor simulators follows. 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 discrete-time and mixed-domain filters and circuits is given, including sensor read-out amplifiers, correlated double sampling, and chopping, and an introduction to sigma-delta A/D and D/A conversion on a system level. | |||||

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. Details: https://people.ee.ethz.ch/~haschmid/asfwiki/ Some material is protected by password; students from ETHZ who are interested can write to haschmid@ethz.ch 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 and z transform and their interpretation (transfer functions, poles and zeros, bode diagrams, stability criteria ...) and of the main properties of linear systems is necessary. | |||||

227-0477-00L | Acoustics I | W | 6 credits | 4G | K. Heutschi | |

Abstract | Introduction to the fundamentals of acoustics in the area of sound field calculations, measurement of acoustical events, outdoor sound propagation and room acoustics of large and small enclosures. | |||||

Learning objective | Introduction to acoustics. Understanding of basic acoustical mechanisms. Survey of the technical literature. Illustration of measurement techniques in the laboratory. | |||||

Content | Fundamentals of acoustics, measuring and analyzing of acoustical events, anatomy and properties of the ear. Outdoor sound propagation, absorption and transmission of sound, room acoustics of large and small enclosures, architectural acoustics, noise and noise control, calculation of sound fields. | |||||

Lecture notes | yes | |||||

227-0778-00L | Hardware/Software Codesign | W | 6 credits | 2V + 2U | L. Thiele | |

Abstract | The course provides advanced knowledge in the design of complex computer systems, in particular embedded systems. Models and methods are discussed that are fundamental for systems that consist of software and hardware components. | |||||

Learning objective | The course provides advanced knowledge in the design of complex computer systems, in particular embedded systems. Models and methods are discussed that are fundamental for systems that consist of software and hardware components. | |||||

Content | The course covers the following subjects: (a) Models for describing hardware and software components (specification), (b) Hardware-Software Interfaces (instruction set, hardware and software components, reconfigurable computing, heterogeneous computer architectures, System-on-Chip), (c) Application specific instruction sets, code generation and retargetable compilation, (d) Performance analysis and estimation techniques, (e) System design (hardware-software partitioning and design space exploration). | |||||

Lecture notes | Material for exercises, copies of transparencies. | |||||

Literature | Peter Marwedel, Embedded System Design, Springer, ISBN-13 978-94-007-0256-1, 2011. Wayne Wolf. Computers as Components. Morgan Kaufmann, ISBN-13: 978-0123884367, 2012. | |||||

Prerequisites / Notice | Prerequisites for the course is a basic knowledge in the following areas: computer architecture, digital design, software design, embedded systems | |||||

252-0535-00L | Machine Learning | W | 8 credits | 3V + 2U + 2A | J. M. Buhmann | |

Abstract | Machine learning algorithms provide analytical methods to search data sets for characteristic patterns. Typical tasks include the classification of data, function fitting and clustering, with applications in image and speech analysis, bioinformatics and exploratory data analysis. This course is accompanied by practical machine learning projects. | |||||

Learning objective | Students will be familiarized with the most important concepts and algorithms for supervised and unsupervised learning; reinforce the statistics knowledge which is indispensible to solve modeling problems under uncertainty. Key concepts are the generalization ability of algorithms and systematic approaches to modeling and regularization. A machine learning project will provide an opportunity to test the machine learning algorithms on real world data. | |||||

Content | The theory of fundamental machine learning concepts is presented in the lecture, and illustrated with relevant applications. Students can deepen their understanding by solving both pen-and-paper and programming exercises, where they implement and apply famous algorithms to real-world data. Topics covered in the lecture include: - Bayesian theory of optimal decisions - Maximum likelihood and Bayesian parameter inference - Classification with discriminant functions: Perceptrons, Fisher's LDA and support vector machines (SVM) - Ensemble methods: Bagging and Boosting - Regression: least squares, ridge and LASSO penalization, non-linear regression and the bias-variance trade-off - Non parametric density estimation: Parzen windows, nearest nieghbour - Dimension reduction: principal component analysis (PCA) and beyond | |||||

Lecture notes | No lecture notes, but slides will be made available on the course webpage. | |||||

Literature | C. Bishop. Pattern Recognition and Machine Learning. Springer 2007. R. Duda, P. Hart, and D. Stork. Pattern Classification. John Wiley & Sons, second edition, 2001. T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning: Data Mining, Inference and Prediction. Springer, 2001. L. Wasserman. All of Statistics: A Concise Course in Statistical Inference. Springer, 2004. | |||||

Prerequisites / Notice | The course requires solid basic knowledge in analysis, statistics and numerical methods for CSE as well as practical programming experience for solving assignments. Students should at least have followed one previous course offered by the Machine Learning Institute (e.g., CIL or LIS) or an equivalent course offered by another institution. | |||||

263-4640-00L | Network Security | W | 6 credits | 2V + 1U + 2A | A. Perrig, S. Frei | |

Abstract | Some of today's most damaging attacks on computer systems involve exploitation of network infrastructure, either as the target of attack or as a vehicle to attack end systems. This course provides an in-depth study of network attack techniques and methods to defend against them. | |||||

Learning objective | - Students are familiar with fundamental network security concepts. - Students can assess current threats that Internet services and networked devices face, and can evaluate appropriate countermeasures. - Students can identify and assess known vulnerabilities in a software system that is connected to the Internet (through analysis and penetration testing tools). - Students have an in-depth understanding of a range of important security technologies. - Students learn how formal analysis techniques can help in the design of secure networked systems. | |||||

Content | The course will cover topics spanning five broad themes: (1) network defense mechanisms such as secure routing protocols, TLS, anonymous communication systems, network intrusion detection systems, and public-key infrastructures; (2) network attacks such as denial of service (DoS) and distributed denial-of-service (DDoS) attacks; (3) analysis and inference topics such as network forensics and attack economics; (4) formal analysis techniques for verifying the security properties of network architectures; and (5) new technologies related to next-generation networks. | |||||

Prerequisites / Notice | This lecture is intended for students with an interest in securing Internet communication services and network devices. Students are assumed to have knowledge in networking as taught in a Communication Networks lecture. The course will involve a course project and some smaller programming projects as part of the homework. Students are expected to have basic knowledge in network programming in a programming language such as C/C++, Go, or Python. | |||||

401-3055-64L | Algebraic Methods in Combinatorics | W | 6 credits | 2V + 1U | B. Sudakov | |

Abstract | Combinatorics is a fundamental mathematical discipline as well as an essential component of many mathematical areas, and its study has experienced an impressive growth in recent years. This course provides a gentle introduction to Algebraic methods, illustrated by examples and focusing on basic ideas and connections to other areas. | |||||

Learning objective | ||||||

Content | Combinatorics is a fundamental mathematical discipline as well as an essential component of many mathematical areas, and its study has experienced an impressive growth in recent years. While in the past many of the basic combinatorial results were obtained mainly by ingenuity and detailed reasoning, the modern theory has grown out of this early stage and often relies on deep, well-developed tools. One of the main general techniques that played a crucial role in the development of Combinatorics was the application of algebraic methods. The most fruitful such tool is the dimension argument. Roughly speaking, the method can be described as follows. In order to bound the cardinality of of a discrete structure A one maps its elements to vectors in a linear space, and shows that the set A is mapped to linearly independent vectors. It then follows that the cardinality of A is bounded by the dimension of the corresponding linear space. This simple idea is surprisingly powerful and has many famous applications. This course provides a gentle introduction to Algebraic methods, illustrated by examples and focusing on basic ideas and connections to other areas. The topics covered in the class will include (but are not limited to): Basic dimension arguments, Spaces of polynomials and tensor product methods, Eigenvalues of graphs and their application, the Combinatorial Nullstellensatz and the Chevalley-Warning theorem. Applications such as: Solution of Kakeya problem in finite fields, counterexample to Borsuk's conjecture, chromatic number of the unit distance graph of Euclidean space, explicit constructions of Ramsey graphs and many others. The course website can be found at https://moodle-app2.let.ethz.ch/course/view.php?id=3770 |

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