# Search result: Catalogue data in Autumn Semester 2020

Electrical Engineering and Information Technology Bachelor | ||||||

1st semester | ||||||

First Year Examinations | ||||||

First Year Examination Block A | ||||||

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

227-0003-00L | Digital Circuits | O | 4 credits | 2V + 2U | M. Luisier | |

Abstract | Digital and analogue signals and their representation. Combinational and sequential circuits and systems, boolean algebra, K-maps. Finite state machines. Memory and computing building blocks in CMOS technology. | |||||

Objective | Provide basic knowledge and methods to understand and to design digital circuits and systems. | |||||

Content | Digital and analogue signals and their representation. Boolean Algebra, circuit analysis and synthesis, the MOS transistor, CMOS logic, static and dynamic behaviour, tristate logic, Karnough-Maps, hazards, binary nuber systems, coding. Combinational and sequential circuits and systems (boolean algebra, K-maps, etc.). Memory building blocks and memory structures, programmable logic circuits. Finite state machines, architetcure of microprocessors. | |||||

Lecture notes | Lecture notes for all lessons, assignments and solutions. https://iis-students.ee.ethz.ch/lectures/digital-circuits/vorlesung/ | |||||

Literature | Literature will be announced during the lessons. Access to the book «J. Reichardt, "Digitaltechnik: eine Einfuehrung mit VHDL", 4th edition, De Gruyter Studium, 2017.» is provided online by the ETH Library. | |||||

Prerequisites / Notice | No special prerequisites. | |||||

401-0151-00L | Linear Algebra | O | 5 credits | 3V + 2U | V. C. Gradinaru | |

Abstract | Contents: Linear systems - the Gaussian algorithm, matrices - LU decomposition, determinants, vector spaces, least squares - QR decomposition, linear maps, eigenvalue problem, normal forms - singular value decomposition; numerical aspects; introduction to MATLAB. | |||||

Objective | Einführung in die Lineare Algebra für Ingenieure unter Berücksichtigung numerischer Aspekte | |||||

Literature | K. Nipp / D. Stoffer, Lineare Algebra, vdf Hochschulverlag, 5. Auflage 2002 Peter J. Olver / Chehrzad Shakiban, Applied linear algebra, 2nd ed. 2018, 10.1007/978-3-319-91041-3 , online in ETH-BIB | |||||

227-0001-00L | Networks and Circuits I | O | 4 credits | 2V + 2U | C. Franck | |

Abstract | This course introduces the students into the basics of electric circuits, the underlying physical phenomena and required mathematical methods. | |||||

Objective | Voltage, current and properties of basic elements of electric circuits, i.e. capacitors, resistors and inductors should be understood in relation to electric and magnetic fields. Furthermore, the students should be able to mathematically describe, analyze and finally design technical realizations of circuit elements. Students should also be familiar with the calculation of voltage and current distributions of DC circuits. The effect and the mathematical formulation of magnetic induction should be known for technical applications. | |||||

Content | Electrostatic field; Stationary electric current flow; Basic electric circuits; current conduction mechanisms; time variant electromagnetic field. | |||||

Lecture notes | Manfred Albach, Elekrotechnik ISBN 978-3-86894-398-6 (2020) and lecture notes | |||||

Literature | Manfred Albach, Elekrotechnik 978-3-86894-398-6 (2020) | |||||

151-0223-10L | Engineering Mechanics | O | 4 credits | 2V + 2U + 1K | J. Dual, C. Glocker | |

Abstract | Introduction to engineering mechanics: kinematics, statics and dynamics of rigid bodies and systems of rigid bodies. | |||||

Objective | Students can solve problems of elementary engineering mechanics. | |||||

Content | Basic notions: position and velocitiy of particles, rigid bodies, planar motion, kinematics of rigid body, force, couple, power. Statics: static equivalence, force-couple system, center of forces, centroid, principle of virtual power, equilibrium, constraints, statics, friction. Dynamics: acceleration, inertial forces, d'Alembert's Principle, Newton's Second Law, principles of linear and angular momentum, equations of planar motion of rigid bodies. | |||||

Lecture notes | yes, in German | |||||

Literature | M. B. Sayir, J. Dual, S. Kaufmann, E. Mazza: Ingenieurmechanik 1, Grundlagen und Statik. Springer Vieweg, Wiesbaden, 2015. M. B. Sayir, S. Kaufmann: Ingenieurmechanik 3, Dynamik. Springer Vieweg, Wiesbaden, 2014. | |||||

First Year Examination Block B | ||||||

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

401-0231-10L | Analysis 1 | O | 8 credits | 4V + 3U | E. Kowalski | |

Abstract | Reelle und komplexe Zahlen, Grenzwerte, Folgen, Reihen, Potenzreihen, stetige Abbildungen, Differential- und Integralrechnung einer Variablen, Einführung in gewöhnliche Differentialgleichungen | |||||

Objective | Einführung in die Grundlagen der Analysis | |||||

Lecture notes | Christian Blatter: Ingenieur-Analysis (Kapitel 1-4) | |||||

Literature | Konrad Koenigsberger, Analysis I. Christian Blatter, Analysis I. | |||||

First Year Compulsory Laboratory Courses | ||||||

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

227-0005-10L | Digital Circuits Laboratory | O | 1 credit | 1P | A. Emboras, M. Luisier | |

Abstract | Digital and analogue signals and their representation. Combinational and sequential circuits and systems, boolean algebra, K-maps. Finite state machines. Memory and computing building blocks in CMOS technology, programmable logic circuits. | |||||

Objective | Deepen and extend the knowledge from lecture and exercises, usage of design software Quartus II as well as an oscilloscope | |||||

Content | The contents of the digital circuits laboratory will deepen and extend the knowledge of the correspondent lecture and exercises. With the help of the logic device design software Quartus II different circuits will be designed and then tested on an evaluation board. You will build up the control for a 7-digit display as well as an adder and you will create different types of latches and flip-flops. At the end of the laboratory a small synthesizer will be programmed that is able to play self-created melodies. At the same time the usage of a modern oscilloscope will be taught in order to analyse the programmed circuits through the digital and analogue inputs. | |||||

Lecture notes | Lecture notes for all experiments. https://iis-students.ee.ethz.ch/lectures/digital-circuits/praktikum/ | |||||

Prerequisites / Notice | No special prerequisites | |||||

252-0865-00L | Preparatory Course in Computer Science | O | 1 credit | 1P | M. Schwerhoff | |

Abstract | The course provides an elementary introduction to programming with C++. Prior programming experience is not required. | |||||

Objective | Establish an understanding of basic concepts of imperative programming and how to systematically approach programming problems. Students are able to read and write simple C++ programs. | |||||

Content | This course introduces you to the basics of programming with C++. Programming means instructing a computer to execute a series of commands that ultimately solve a particular problem. The course comprises the following: - General introduction to computer science: development, goals, fundamental concepts - Interactive self-study tutorial that provides an introduction to C++ and covers the following topics: variables, data types, conditional statements and loops - Introduction to stepwise refinement as an approach to systematically solving programming problems - Two small programming projects, to practically apply the studied fundamentals | |||||

Lecture notes | All teaching material is available online; an online development environment is used for the the programmig projects. | |||||

Repetition Fist Year Electrical Engineering and Information Techn. BSc | ||||||

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

900-9017-00L | Repetition Fist Year Electrical Engineering and Information Technology BSc | 0 credits | not available | |||

Abstract | ||||||

Objective | ||||||

3rd Semester: Examination Blocks | ||||||

Examination Block 1 | ||||||

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

401-0353-00L | Analysis 3 | O | 4 credits | 2V + 2U | M. Iacobelli | |

Abstract | In this lecture we treat problems in applied analysis. The focus lies on the solution of quasilinear first order PDEs with the method of characteristics, and on the study of three fundamental types of partial differential equations of second order: the Laplace equation, the heat equation, and the wave equation. | |||||

Objective | The aim of this class is to provide students with a general overview of first and second order PDEs, and teach them how to solve some of these equations using characteristics and/or separation of variables. | |||||

Content | 1.) General introduction to PDEs and their classification (linear, quasilinear, semilinear, nonlinear / elliptic, parabolic, hyperbolic) 2.) Quasilinear first order PDEs - Solution with the method of characteristics - COnservation laws 3.) Hyperbolic PDEs - wave equation - d'Alembert formula in (1+1)-dimensions - method of separation of variables 4.) Parabolic PDEs - heat equation - maximum principle - method of separation of variables 5.) Elliptic PDEs - Laplace equation - maximum principle - method of separation of variables - variational method | |||||

Literature | Y. Pinchover, J. Rubinstein, "An Introduction to Partial Differential Equations", Cambridge University Press (12. Mai 2005) | |||||

Prerequisites / Notice | Prerequisites: Analysis I and II, Fourier series (Complex Analysis) | |||||

402-0053-00L | Physics II | O | 8 credits | 4V + 2U | A. Imamoglu | |

Abstract | The goal of the Physics II class is an introduction to quantum mechanics | |||||

Objective | To work effectively in many areas of modern engineering, such as renewable energy and nanotechnology, students must possess a basic understanding of quantum mechanics. The aim of this course is to provide this knowledge while making connections to applications of relevancy to engineers. After completing this course, students will understand the basic postulates of quantum mechanics and be able to apply mathematical methods for solving various problems including atoms, molecules, and solids. Additional examples from engineering disciplines will also be integrated. | |||||

Content | Content: - Wave mechanics: the old quantum theory - Postulates and formalism of Quantum Mechanics - First application: the quantum well and the harmonic Oscillator - QM in three dimension: the Hydrogen atom - Identical particles: Pauli's principle - Crystalline Systems and band structures - Quantum statistics - Approximation Methods - Applications in Engineering - Entanglement and superposition | |||||

Lecture notes | Lecture notes (hand-written) will be distributed via the Moodle interface | |||||

Literature | David J. Griffiths, "Introduction to quantum mechanics" Second edition, Cambridge University Press. Link | |||||

Prerequisites / Notice | Prerequisites: Physics I. | |||||

227-0045-00L | Signals and Systems I | O | 4 credits | 2V + 2U | H. Bölcskei | |

Abstract | Signal theory and systems theory (continuous-time and discrete-time): Signal analysis in the time and frequency domains, signal spaces, Hilbert spaces, generalized functions, linear time-invariant systems, sampling theorems, discrete-time signals and systems, digital filter structures, Discrete Fourier Transform (DFT), finite-dimensional signals and systems, Fast Fourier Transform (FFT). | |||||

Objective | Introduction to mathematical signal processing and system theory. | |||||

Content | Signal theory and systems theory (continuous-time and discrete-time): Signal analysis in the time and frequency domains, signal spaces, Hilbert spaces, generalized functions, linear time-invariant systems, sampling theorems, discrete-time signals and systems, digital filter structures, Discrete Fourier Transform (DFT), finite-dimensional signals and systems, Fast Fourier Transform (FFT). | |||||

Lecture notes | Lecture notes, problem set with solutions. | |||||

252-0836-00L | Computer Science II | O | 4 credits | 2V + 1U | F. Mattern | |

Abstract | Introduction to basic problem solving methods, algorithms, and data structures. Topics: divide and conquer, recursion, sorting algorithms, backtracking, game tree search, data structures (lists, stacks, binary trees, etc.), discrete simulation, concurrency, complexity, verification. In the assignments and exercises, the programming language Java is used. | |||||

Objective | Introduction to the general methods of computer science for electrical engineers. Also provides basic skills for advanced exercises and projects later in the electrical engineering program. | |||||

Content | Part II of the lecture concentrates on the most common problem solving skills, algorithms, and data structures. It also teaches fundamental concepts and mechanisms of structured programming. Furthermore, working with formal systems, the necessity of abstraction, and the importance of modeling in computer science will be motivated. The emphasis of the lecture is on practical concepts of computer science. Specific topics are: complexity and correctness of algorithms, divide and conquer, recursion, algorithms for sorting, backtracking, game tree search, data structures (lists, stacks, inary trees, etc.), discrete simulation, concurrency, and verification. For the assignments and exercises, the programming language Java is used. Here, also modularization, abstraction, encapsulation, and object orientation will be considered. Occasionally, short remarks on the historical context of relevant concepts are given. In the practice groups, students program an automatic player for the game "Reversi"; at the end of the semester a tournament will take place. | |||||

Lecture notes | Copies of slides, extended with bonus slides that give hints to advanced concepts and present the historical context of selected concepts. | |||||

Literature | Textbook: Mark Allan Weiss: Data Structures and Problem Solving Using Java, Addison Wesley. | |||||

Prerequisites / Notice | Prerequisite: Part 1 of the course. | |||||

Examination Block 2 | ||||||

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

227-0077-10L | Electronic Circuits | O | 4 credits | 2V + 2U | Q. Huang | |

Abstract | Introductory lecture on electronic circuits. Transistor fundamentals, analysis and design of transistor based electronic circuits such as amplifiers and filters; operational amplifiers and circuits based thereon. | |||||

Objective | Modern, transistor-based electronics has transformed our lives and plays a crucial role in our economy since the 2nd half of last century. The main objective of this course in electronic circuits is to introduce the concept of the active device, including operational amplifiers, and their use in amplification, signal conditioning, switching and filtering to students. In addition to gaining experience with typical electronic circuits that are found in common applications, including their own Gruppenarbeit and Fachpraktikum projects, students sharpen their understanding of linear circuits based on nonlinear devices, imperfections of electronic circuits and the concept of design (as opposed to analysis). The course is a prerequisite for higher semester subjects such as analog integrated circuits, RF circuits for wireless communications, A/D and D/A converters and optoelectronics. | |||||

Content | Review of transistor devices (bipolar and MOSFET), large signal and small signal characteristics, biasing and operating points. Single transistor amplifiers, simple feedback for bias stabilization. Frequency response of simple amplifiers. Broadbanding techniques. Differential amplifiers, operational amplifiers, variable gain amplifiers. Instrumentation amplifiers: common mode rejection, noise, distortion, chopper stabilization. Transimpedance amplifiers. Active filters: simple and biquadratic active RC-filters, higher order filters, biquad and ladder realizations. Switched-capacitor filters. | |||||

Literature | Göbel, H.: Einführung in die Halbleiter-Schaltungstechnik. Springer-Verlag Berlin Heidelberg, 6th edition, 2019. Pederson, D.O. and Mayaram, K.: Analog Integrated Circuits for Communication. Springer US, 2nd edition, 2008. Sansen, W.M.C.: Analog Design Essentials. Springer US, 1st edition, 2006. Su, K.L.: Analog Filters. Springer US, 2nd edition, 2002. | |||||

401-0053-00L | Discrete Mathematics | O | 4 credits | 2V + 1U | D. Adjiashvili | |

Abstract | Introduction to foundations of discrete mathematics: combinatorics (elementary counting), graph theory, algebra, and applications thereof. | |||||

Objective | The main goal is to get a good understanding of some of the most prominent areas within discrete mathematics. | |||||

3rd Semester: Second Year Compulsory Laboratory Course | ||||||

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

227-0079-10L | Electronic Circuits Laboratory | O | 1 credit | 1P | Q. Huang | |

Abstract | Lab with principal electronic circuit experiments on the transistor and operational amplifier basis. | |||||

Objective | Modern, transistor-based electronics has transformed our lives and plays a crucial role in our economy since the 2nd half of last century. The main objective of this course in electronic circuits is to introduce the concept of active device, including operational amplifiers, and their use in amplification, signal conditioning, switching and filtering to students. In addition to gaining experience with typical electronic circuits that are found in common applications, including their own Gruppenarbeit and Fachpraktikum projects, students sharpen their understanding of linear circuits based on nonlinear devices, imperfections of electronic circuits and the concept of design (as opposed to analysis). The course is a prerequisite for higher semester subjects such as analog integrated circuits, RF circuits for wireless communications, A/D and D/A converters and optoelectronics. | |||||

Content | Get to know and understand basic transistor and op amp based electronic circuits. Build and operate simple electronic circuits including supply decoupling. Carry out and understand different, principal measurement methods such as DC- and AC-analysis, time and frequency domain measurements, impedance and transfer function measurements. In the lab we will have a closer look at the following topics and circuits: characterization of a real capacitor including non-idealties; common-emitter transistor amplifier with emitter degeneration; characterization of a real operational amplifier with non-idealties; band pass filter with op amp, resistors and capacitors; data converters; oscillator and function generator based on an op amp. | |||||

5th Semester: Third Year Additional Foundation Courses Students complete at least two of the Additional Foundation Courses available for selection. Recommendations are available under Link | ||||||

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

227-0014-20L | Computational Thinking | W | 4 credits | 2V + 1U | R. Wattenhofer | |

Abstract | We learn: algorithmic principles, dynamic and linear programming, complexity, electronic circuits, P vs. NP, Turing machines, reductions, cryptography, zero-knowledge proofs, data organization, dictionaries, hashing, databases, SQL, machine learning, regression, clustering, deep neural networks. We will use Python as a programming language. There will be paper and programming exercises every week. | |||||

Objective | Computation is everywhere, but what is computation actually? In this lecture we will discuss the power and limitations of computation. Computational thinking is about understanding machine intelligence: What is computable, and how efficiently? Understanding computation lies at the heart of many exciting scientific, social and even philosophical developments. Computational thinking is more than programming a computer, it means thinking in abstractions. Consequently, computational thinking has become a fundamental skill for everyone, not just computer scientists. For example, functions which can easily be computed but not inverted are at the heart of understanding data security and privacy. Machine learning on the other hand has given us fascinating new tools to teach machines how to estimate functions. Thanks to clever heuristics, machines now appear to be capable of solving complex cognitive tasks. To give just one more example: How can we design the best electronic circuit for a given problem? In this class, we study various problems together with the fundamental theory of computation. The weekly lectures will be based on blackboard discussions and coding demos, supported by a script and coding examples. The course uses Python as a programming language. Python is popular and intuitive, a programming language that looks and feels a bit like human instructions. The lecture will feature weekly exercises, on paper and in Python. | |||||

227-0053-00L | High-Frequency Design Techniques | W | 4 credits | 2V + 2U | C. Bolognesi | |

Abstract | Introduction to the basics of high-frequency circuit design techniques used in the realization of high-bandwidth communication systems and devices. Modern society depends on increasingly large data masses that need to be transmitted/processed as rapidly as possible: higher carrier frequencies allow wider bandwidth channels which enable higher data transmission rates. | |||||

Objective | Familiarize students with the essential tools and principles exploited in high-frequency design. Introduction to circuit simulation. | |||||

Content | Introduction to wireless, radio spectrum, review of vectors and complex numbers, AC circuit analysis, matching networks, distributed circuit design, transmission lines and transmission line equations, reflection coefficients, the Smith Chart and its software, voltage standing wave ratio (VSWR), skin effect, matrix analysis, scattering parameters, electromagnetic fields and waves, antenna basics. | |||||

Lecture notes | Lecture notes | |||||

Literature | Textbook: High Frequency Techniques, by Joseph F. White, 2004, Wiley-Interscience & IEEE Press ISBN 0-471-45591-1 (free online access via ETH-Bibliothek) | |||||

227-0122-00L | Introduction to Electric Power Transmission: System & TechnologyStudents that complete the course from HS 2020 onwards obtain 4 credits. | W | 4 credits | 2V + 2U | C. Franck, G. Hug | |

Abstract | Introduction to theory and technology of electric power transmission systems. | |||||

Objective | At the end of this course, the student will be able to: describe the structure of electric power systems, name the most important components and describe what they are needed for, apply models for transformers and overhead power lines, explain the technology of transformers and lines, calculate stationary power flows and other basic parameters in simple power systems. | |||||

Content | Structure of electric power systems, transformer and power line models, analysis of and power flow calculation in basic systems, technology and principle of electric power systems. | |||||

Lecture notes | Lecture script in English, exercises and sample solutions. | |||||

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 | ||||||

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 | |||||

227-0102-00L | 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. | |||||

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 |

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