# Search result: Catalogue data in Autumn Semester 2020

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

Master Studies (Programme Regulations 2008) | ||||||

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

Computers and Networks | ||||||

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 | |
---|---|---|---|---|---|---|

227-0101-00L | 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 | |||||

227-0103-00L | 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. | |||||

227-0116-00L | 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. - SystemVerilog - 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. 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/ | |||||

227-2210-00L | Computer Architecture | W | 8 credits | 6G + 1A | O. Mutlu | |

Abstract | Computer architecture is the science & art of designing and optimizing hardware components and the hardware/software interface to create a computer that meets design goals. This course covers basic components of a modern computing system (processors, memory, interconnects, accelerators). The course takes a hardware/software cooperative approach to understanding and designing computing systems. | |||||

Objective | We will learn the fundamental concepts of the different parts of modern computing systems, as well as the latest trends by exploring the recent research in Industry and Academia. We will extensively cover memory technologies (including DRAM and new Non-Volatile Memory technologies), memory scheduling, parallel computing systems (including multicore processors and GPUs), heterogeneous computing, processing-in-memory, interconnection networks, specialized systems for major data-intensive workloads (e.g. graph processing, bioinformatics, machine learning), etc. | |||||

Content | The principles presented in the lecture are reinforced in the laboratory through 1) the design and implementation of a cycle-accurate simulator, where we will explore different components of a modern computing system (e.g., pipeline, memory hierarchy, branch prediction, prefetching, caches, multithreading), and 2) the extension of state-of-the-art research simulators (e.g., Ramulator) for more in-depth understanding of specific system components (e.g., memory scheduling, prefetching). | |||||

Lecture notes | All the materials (including lecture slides) will be provided on the course website: https://safari.ethz.ch/architecture/ The video recordings of the lectures are expected to be made available after lectures. | |||||

Literature | We will provide required and recommended readings in every lecture. They will mainly consist of research papers presented in major Computer Architecture and related conferences and journals. | |||||

Prerequisites / Notice | Digital Design and Computer Architecture. | |||||

227-2211-00L | Seminar in Computer Architecture Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | O. Mutlu, M. H. K. Alser, J. Gómez Luna | |

Abstract | This seminar course covers fundamental and cutting-edge research papers in computer architecture. It consists of multiple components that are aimed at improving students' (1) technical skills in computer architecture, (2) critical thinking and analysis abilities on computer architecture concepts, as well as (3) technical presentation of concepts and papers in both spoken and written forms. | |||||

Objective | The main objective is to learn how to rigorously analyze and present papers and ideas on computer architecture. We will have rigorous presentation and discussion of selected papers during lectures and a written report delivered by each student at the end of the semester. This course is for those interested in computer architecture. Registered students are expected to attend every meeting, participate in the discussion, and create a synthesis report at the end of the course. | |||||

Content | Topics will center around computer architecture. We will, for example, discuss papers on hardware security; accelerators for key applications like machine learning, graph processing and bioinformatics; memory systems; interconnects; processing in memory; various fundamental and emerging paradigms in computer architecture; hardware/software co-design and cooperation; fault tolerance; energy efficiency; heterogeneous and parallel systems; new execution models; predictable computing, etc. | |||||

Lecture notes | All materials will be posted on the course website: https://safari.ethz.ch/architecture_seminar/ Past course materials, including the synthesis report assignment, can be found in the Spring 2020 website for the course: https://safari.ethz.ch/architecture_seminar/spring2020/doku.php?id=start | |||||

Literature | Key papers and articles, on both fundamentals and cutting-edge topics in computer architecture will be provided and discussed. These will be posted on the course website. | |||||

Prerequisites / Notice | Digital Design and Computer Architecture. Students should (1) have done very well in Digital Design and Computer Architecture and (2) show a genuine interest in Computer Architecture. | |||||

227-0377-10L | Physics of Failure and Reliability of Electronic Devices and Systems | W | 3 credits | 2V | I. Shorubalko, M. Held | |

Abstract | Understanding the physics of failures and failure mechanisms enables reliability analysis and serves as a practical guide for electronic devices design, integration, systems development and manufacturing. The field gains additional importance in the context of managing safety, sustainability and environmental impact for continuously increasing complexity and scaling-down trends in electronics. | |||||

Objective | Provide an understanding of the physics of failure and reliability. Introduce the degradation and failure mechanisms, basics of failure analysis, methods and tools of reliability testing. | |||||

Content | Summary of reliability and failure analysis terminology; physics of failure: materials properties, physical processes and failure mechanisms; failure analysis; basics and properties of instruments; quality assurance of technical systems (introduction); introduction to stochastic processes; reliability analysis; component selection and qualification; maintainability analysis (introduction); design rules for reliability, maintainability, reliability tests (introduction). | |||||

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

Literature | Reliability Engineering: Theory and Practice, 8th Edition, Springer 2017, DOI 10.1007/978-3-662-54209-5 Reliability Engineering: Theory and Practice, 8th Edition (2017), DOI 10.1007/978-3-662-54209-5 | |||||

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

Abstract | Light and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition. Deep learning and Convolutional Neural Networks. | |||||

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 | This course aims at offering a self-contained account of computer vision and its underlying concepts, including the recent use of deep learning. The first part starts with 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 the interaction of light with matter is considered. The most important hardware components such as cameras and illumination sources are also discussed. The course then turns to image discretization, necessary to process images by computer. The next part describes necessary pre-processing steps, 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 3D shape as two important examples. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed. A major part at the end is devoted to deep learning and AI-based approaches to image analysis. Its main focus is on object recognition, but also other examples of image processing using deep neural nets are given. | |||||

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 Python and Linux. The course language is English. | |||||

227-0555-00L | Distributed Systems Enrolled students will be notified by e-mail about the lecture start. | W | 4 credits | 3G + 1A | R. Wattenhofer | |

Abstract | This course introduces the fundamentals of distributed systems. We study different protocols and algorithms that allow for fault-tolerant operation, and discuss practical systems that implement these techniques. | |||||

Objective | The objective of the course is for students to understand the theoretical principles and practical considerations of distributed systems. This includes the main models of fault-tolerant distributed systems (crash failures, byzantine failures, and selfishness), and the most important algorithms, protocols and impossibility results. By the end of the course, students should be able to reason about various concepts such as consistency, durability, availability, fault tolerance, and replication. | |||||

Content | We discuss the following concepts related to fault-tolerant distributed systems: client-server, serialization, two-phase protocols, three-phase protocols, paxos, two generals problem, crash failures, impossibility of consensus, byzantine failures, agreement, termination, validity, byzantine agreement, king algorithm, asynchronous byzantine agreement, authentication, signatures, reliable and atomic broadcast, eventual consistency, blockchain, cryptocurrencies such as bitcoin and ethereum, proof-of-work, proof-of-*, smart contracts, quorum systems, fault-tolerant protocols such as piChain or pbft, distributed storage, distributed hash tables, physical and logical clocks, causality, selfishness, game theoretic models, mechanism design. | |||||

Lecture notes | A script is available on the web page. | |||||

Literature | The script is self-contained, but links to additional material are available on the web page. | |||||

Prerequisites / Notice | This lecture takes place in roughly the second half of the semester, as the lecture is the second part of the lecture "Computer Systems" (252-0217-00). Students may attend at most one of the two lectures, NOT both. | |||||

227-0559-10L | Seminar in Communication Networks: Learning, Reasoning and Control Does not take place this semester. Number of participants limited to 24. | W | 2 credits | 2S | L. Vanbever | |

Abstract | In this seminar participating students review, present, and discuss (mostly recent) research papers in the area of computer networks. During the fall semester of 2019, the seminar will focus on topics blending networks with machine learning and control theory. | |||||

Objective | The two main goals of this seminar are: 1) learning how to read and review scientific papers; and 2) learning how to present and discuss technical topics with an audience of peers. Students are required to attend the entire seminar, choose a paper to present from a given list, prepare and give a presentation on that topic, and lead the follow-up discussion. To ensure the talks' quality, each student will be mentored by a teaching assistant. In addition to presenting one paper, every student is also required to submit one (short) review for one of the two papers presented every week in-class (12 reviews in total). The students will be evaluated based on their submitted reviews, their presentation, their leadership in animating the discussion for their own paper, and their participation in the discussions of other papers. | |||||

Content | The seminar will start with two introductory lectures in week 1 and week 2. Starting from week 3, participating students will start reviewing, presenting, and discussing research papers. Each week will see two presentations, for a total of 24 papers. The course content will vary from semester to semester. During the fall semester of 2019, the seminar will focus on topics blending networks with machine learning and control theory. For details, please see: https://seminar-net.ethz.ch | |||||

Lecture notes | The slides of each presentation will be made available on the website. | |||||

Literature | The paper selection will be made available on the course website: https://seminar-net.ethz.ch | |||||

Prerequisites / Notice | Communication Networks (227-0120-00L) or equivalents. For fall 2019, it is expected that students have prior knowledge in machine learning and control theory, for instance by having attended appropriate courses. | |||||

227-0627-00L | Applied Computer Architecture | W | 6 credits | 4G | A. Gunzinger | |

Abstract | This lecture gives an overview of the requirements and the architecture of parallel computer systems, performance, reliability and costs. | |||||

Objective | Understand the function, the design and the performance modeling of parallel computer systems. | |||||

Content | The lecture "Applied Computer Architecture" gives technical and corporate insights in innovative Computer Systems/Architectures (CPU, GPU, FPGA, dedicated processors) and their real implementations and applications. Often the designs have to deal with technical limits. Which computer architecture allows the control of the over 1000 magnets at the Swiss Light Source (SLS)? Which architecture is behind the alarm center of the Swiss Railway (SBB)? Which computer architectures are applied for driver assistance systems? Which computer architecture is hidden behind a professional digital audio mixing desk? How can data streams of about 30 TB/s, produced by a protone accelerator, be processed in real time? Can the weather forecast also be processed with GPUs? How can a good computer architecture be found? Which are the driving factors in succesful computer architecture design? | |||||

Lecture notes | Script and exercices sheets. | |||||

Prerequisites / Notice | Prerequisites: Basics of computer architecture. | |||||

151-0593-00L | Embedded Control SystemsDoes not take place this semester. | W | 4 credits | 6G | ||

Abstract | This course provides a comprehensive overview of embedded control systems. The concepts introduced are implemented and verified on a microprocessor-controlled haptic device. | |||||

Objective | Familiarize students with main architectural principles and concepts of embedded control systems. | |||||

Content | An embedded system is a microprocessor used as a component in another piece of technology, such as cell phones or automobiles. In this intensive two-week block course the students are presented the principles of embedded digital control systems using a haptic device as an example for a mechatronic system. A haptic interface allows for a human to interact with a computer through the sense of touch. Subjects covered in lectures and practical lab exercises include: - The application of C-programming on a microprocessor - Digital I/O and serial communication - Quadrature decoding for wheel position sensing - Queued analog-to-digital conversion to interface with the analog world - Pulse width modulation - Timer interrupts to create sampling time intervals - System dynamics and virtual worlds with haptic feedback - Introduction to rapid prototyping | |||||

Lecture notes | Lecture notes, lab instructions, supplemental material | |||||

Prerequisites / Notice | Prerequisite courses are Control Systems I and Informatics I. This course is restricted to 33 students due to limited lab infrastructure. Interested students please contact Marianne Schmid (E-Mail: marischm@ethz.ch) After your reservation has been confirmed please register online at www.mystudies.ethz.ch. Detailed information can be found on the course website http://www.idsc.ethz.ch/education/lectures/embedded-control-systems.html | |||||

252-1411-00L | Security of Wireless Networks | W | 6 credits | 2V + 1U + 2A | S. Capkun, K. Kostiainen | |

Abstract | Core Elements: Wireless communication channel, Wireless network architectures and protocols, Attacks on wireless networks, Protection techniques. | |||||

Objective | After this course, the students should be able to: describe and classify security goals and attacks in wireless networks; describe security architectures of the following wireless systems and networks: 802.11, GSM/UMTS, RFID, ad hoc/sensor networks; reason about security protocols for wireless network; implement mechanisms to secure 802.11 networks. | |||||

Content | Wireless channel basics. Wireless electronic warfare: jamming and target tracking. Basic security protocols in cellular, WLAN and multi-hop networks. Recent advances in security of multi-hop networks; RFID privacy challenges and solutions. | |||||

263-3900-01L | Communication Networks Seminar Number of participants limited to 20. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | A. Singla, L. Vanbever | |

Abstract | We explore recent advances in networking by reading high quality research papers, and discussing open research opportunities, most of which are suitable for students to later take up as thesis or semester projects. | |||||

Objective | The objectives are (a) to understand the state-of-the-art in the field; (b) to learn to read, present and critique papers; (c) to engage in discussion and debate about research questions; and (d) to identify opportunities for new research. Students are expected to attend the entire seminar, choose a topic for presentation from a given list, make a presentation on that topic, and lead the discussion. Further, for each reading, every student needs to submit a review before the in-class discussion. Students are evaluated on their submitted reviews, their presentation and discussion leadership, and participation in seminar discussions. | |||||

Literature | A program will be posted here: https://ndal.ethz.ch/courses/networks-seminar.html, comprising of a list of papers the seminar group will cover. | |||||

Prerequisites / Notice | An undergraduate-level understanding of networking, such that the student is familiar with concepts like reliable transport protocols (like TCP) and basics of Internet routing. ETH courses that fulfill this requirement: Computer Networks (252-0064-00L) and Communication Networks (227-0120-00L). Similar courses at other universities are also sufficient. |

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