# Search result: Catalogue data in Spring Semester 2020

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

Bachelor Studies (Programme Regulations 2018) | ||||||

2. Semester | ||||||

First Year Examinations | ||||||

First Year Examination Block A Offered in the autumn semester. | ||||||

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

Number | Title | Type | ECTS | Hours | Lecturers | |
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401-0232-10L | Analysis 2 Students in BSc EEIT who registered for the course unit 401-1261-07L Analysis I in the Autumn Semester may instead register for 401-1262-07L Analysis II (for BSc Mathematics, BSc Physics and BSc Interdisciplinary Science (Phys Chem)) and take the performance assessment of the corresponding two-semester course. | O | 8 credits | 4V + 2U | P. Feller | |

Abstract | Introduction to differential calculus and integration in several variables. | |||||

Learning objective | Einführung in die Grundlagen der Analysis | |||||

Content | Differentiation in several variables, maxima and minima, the implicit function theorem, integration in several variables, integration over submanifolds, the theorems of Gauss and Stokes. | |||||

Lecture notes | Christian Blatter: Ingenieur-Analysis (Kapitel 4-6). Konrad Koenigsberger, Analysis II. | |||||

252-0848-00L | Computer Science I | O | 4 credits | 2V + 2U | M. Schwerhoff, H. Lehner | |

Abstract | The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required. | |||||

Learning objective | Primary educational objective is to learn programming with C++. When successfully attended the course, students have a good command of the mechanisms to construct a program. They know the fundamental control and data structures and understand how an algorithmic problem is mapped to a computer program. They have an idea of what happens "behind the scenes" when a program is translated and executed. Secondary goals are an algorithmic computational thinking, understanding the possibilities and limits of programming and to impart the way of thinking of a computer scientist. | |||||

Content | The course covers fundamental data types, expressions and statements, (Limits of) computer arithmetic, control statements, functions, arrays, structural types and pointers. The part on object orientation deals with classes, inheritance and polymorphy, simple dynamic data types are introduced as examples. In general, the concepts provided in the course are motivated and illustrated with algorithms and applications. | |||||

Lecture notes | A script written in English will be provided during the semester. The script and slides will be made available for download on the course web page. | |||||

Literature | Bjarne Stroustrup: Einführung in die Programmierung mit C++, Pearson Studium, 2010 Stephen Prata, C++ Primer Plus, Sixth Edition, Addison Wesley, 2012 Andrew Koenig and Barbara E. Moo: Accelerated C++, Addison-Wesley, 2000. | |||||

401-0302-10L | Complex Analysis as of 4 March 2020: The lecturer and many students are in the lecture hall, but some students are absent. The lecture is recorded. | O | 4 credits | 3V + 1U | A. Iozzi | |

Abstract | Basics of complex analysis in theory and applications, in particular the global properties of analytic functions. Introduction to the integral transforms and description of some applications | |||||

Learning objective | Erwerb von einigen grundlegenden Werkzeuge der komplexen Analysis. | |||||

Content | Examples of analytic functions, Cauchy‘s theorem, Taylor and Laurent series, singularities of analytic functions, residues. Fourier series and Fourier integral, Laplace transform. | |||||

Literature | J. Brown, R. Churchill: "Complex Analysis and Applications", McGraw-Hill 1995 T. Needham. Visual complex analysis. Clarendon Press, Oxford. 2004. M. Ablowitz, A. Fokas: "Complex variables: introduction and applications", Cambridge Text in Applied Mathematics, Cambridge University Press 1997 E. Kreyszig: "Advanced Engineering Analysis", Wiley 1999 J. Marsden, M. Hoffman: "Basic complex analysis", W. H. Freeman 1999 P. P. G. Dyke: "An Introduction to Laplace Transforms and Fourier Series", Springer 2004 A. Oppenheim, A. Willsky: "Signals & Systems", Prentice Hall 1997 M. Spiegel: "Laplace Transforms", Schaum's Outlines, Mc Graw Hill | |||||

Prerequisites / Notice | Prerequisites: Analysis I and II | |||||

227-0002-00L | Networks and Circuits II | O | 8 credits | 4V + 2U | J. Biela | |

Abstract | Introduction to AC circuits analysis, Fourier analysis, frequency and time domain, step response of electric circuits, Fourier and Laplace transform, frequency response of electric networks, two-port systems, differential amplifier, operational amplifier, basic and advanced operational amplifier circuits | |||||

Learning objective | The lecture is aiming to make students familiar with basis methods of AC circuits analysis, the Fourier analysis of non-sinusoidal periodic signals, i.e. the relations of frequency and time domain, the calculation of the step response and transfer function of linear networks using Fourier- and Laplace transform and the analysis and design operational amplifier circuits. | |||||

Content | Introduction to AC circuits analysis, Fourier analysis, frequency and time domain, step response of electric circuits, Fourier and Laplace transform, frequency response of electric networks, two-port systems, differential amplifier, operational amplifier, basic and advanced operational amplifier circuits | |||||

Lecture notes | Lecture notes are available in Moodle. In addition, the listed literature could be used. | |||||

Literature | Elektrotechnik; Manfred Albach; 1. Auflage; 629 Seiten; Pearson Studium 2011; ISBN: 9783868940817 Grundlagen der Elektrotechnik – Netzwerke; 2. Auflage; 372 Sei- ten; Schmidt / Schaller / Martius; Pearson Studium 2014; ISBN: 9783868942392 Microelectronic Circuits; 7. Auflage; 1472 Seiten; Sedra / Smith; Oxford University Press 2015; ISBN: 9780199339143 | |||||

402-0052-00L | Physics I: Waves and Thermodynamics | O | 4 credits | 2V + 2U | A. Wallraff | |

Abstract | Physics I is an introduction to continuum mechanics, wave phenomena, and fundamental concepts of thermodynamics. | |||||

Learning objective | After completing this course, students should be able to construct and apply simple models of dynamics in non-rigid materials. Students should also be able to identify and relate basic thermodynamic quantities in equilibrium systems given realistic constraints. | |||||

Content | The lecture will discuss the following concepts: Waves - One dimensional wave equation - Plane waves, spherical waves in 2 and 3 dimensions - Elastic waves, sound velocity - Stationary waves, resonances - Propagation: interference and diffraction - Doppler effect Thermodynamics - Kinetic theory of gases, perfect gases - Conservation of energy, first principle - Second principle, thermal cycles - Entropy, thermodynamical and statistical interpretation - Thermal radiation and heat transfer. | |||||

Lecture notes | The lecture notes will be distributed via the Moodle platform. | |||||

Literature | P. A. Tipler and G. Mosca, "Physics for Scientists and Engineers" (6th edition) Chapters 14-20. | |||||

Prerequisites / Notice | Technical Mechanics, Analysis | |||||

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

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

227-0004-10L | Networks and Circuits Laboratory Only for Electrical Engineering and Information Technology BSc. | O | 1 credit | 1P | J. W. Kolar | |

Abstract | Concepts from the lectures "Networks and Circuits I and II" explored through experiments, with inductive energy transmission systems (equivalent circuit parameters, transmission characteristics, resonance compensation, high-voltage generation) and photovoltaics (solar module characteristics, power flow adjustment with DC-DC converters, electro-mechanical energy conversion) used as examples. | |||||

Learning objective | The core topics of the course "Networks and Circuits I and II" are reviewed in practice, through experiments, in a modern laboratory environment. Furthermore, through the illustrative experiments in the fields of inductive power transfer and photovoltaics, a methodical experimental approach, the use of modern measurement equipment, and proper documentation skills are all learned. | |||||

Content | The "Networks and Circuits Laboratory" covers core topics presented in the lectures and exercises of the courses "Networks and Circuits I and II" through experiments. These topics are demonstrated in practice within the context of selected real-world industrial applications: - Inductive power transfer (topics: parameters of equivalent circuits, transmission characteristics, resonance compensation, and high-voltage generation); and - Photovoltaics (topics: characteristics and power performance of a solar module, power flow and/or operating point adjustment with power electronic converters, electro-mechanical energy conversion). In each experiment, after measuring and observing components and subsystems of the above, the structuring and overall function of the system is discussed, in order to promote higher-level abstract reasoning and synthesis skills in addition to analysis skills. Further important goals of this Laboratory Course are familiarisation with modern measuring equipment, and highlighting the importance of planning, executing, and documenting experiments and measurements in a thorough and methodical fashion. | |||||

Lecture notes | Instruction manual | |||||

Literature | Lecture documents Networks and Circuits I and II | |||||

Examination Blocks | ||||||

Examination Block 2 | ||||||

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

227-0013-00L | Computer Engineering | O | 4 credits | 2V + 1U + 1P | L. Thiele | |

Abstract | The course provides knowledge about structures and models of digital systems, assembler and compiler, control path and data path, pipelining, speculation techniques, superscalar computer architectures, memory hierarchy and virtual memory, operating system, processes and threads. | |||||

Learning objective | Logical and physical structure of computer systems. Introduction to principles in hardware design, datapath and control path, assembler programming, modern architectures (pipelining, speculation techniques, superscalar architectures, multithreading), memory hierarchy and virtual memory, software concepts. | |||||

Content | Structures and models of digital systems, abstraction and hierarchy in computer systems, assembler and compiler, control path and data path, pipelining, speculation techniques, superscalar computer architectures, memory hierarchy and virtual memory, operating system, processes and threads. Theoretical and practical exercises using a simulation-based infrastructure. | |||||

Lecture notes | Material for practical training, copies of transparencies. | |||||

Literature | D.A. Patterson, J.L. Hennessy: Computer Organization and Design: The Hardware/ Software Interface. Morgan Kaufmann Publishers, Inc., San Francisco, ISBN-13: 978-0124077263, 2014. | |||||

Prerequisites / Notice | Prerequisites: Programming skills in high level language, knowledge of digital design. | |||||

227-0046-10L | Signals and Systems II | O | 4 credits | 2V + 2U | J. Lygeros | |

Abstract | Continuous and discrete time linear system theory, state space methods, frequency domain methods, controllability, observability, stability. | |||||

Learning objective | Introduction to basic concepts of system theory. | |||||

Content | Modeling and classification of dynamical systems. Modeling of linear, time invariant systems by state equations. Solution of state equations by time domain and Laplace methods. Stability, controllability and observability analysis. Frequency domain description, Bode and Nyquist plots. Sampled data and discrete time systems. Advanced topics: Nonlinear systems, chaos, discrete event systems, hybrid systems. | |||||

Lecture notes | Copy of transparencies | |||||

Literature | Recommended: K.J. Astrom and R. Murray, "Feedback Systems: An Introduction for Scientists and Engineers", Princeton University Press 2009 http://www.cds.caltech.edu/~murray/amwiki/ | |||||

Examination Block 3 | ||||||

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

401-0654-00L | Numerical Methods | O | 4 credits | 2V + 1U | R. Käppeli | |

Abstract | The course introduces numerical methods according to the type of problem they tackle. The tutorials will include both theoretical exercises and practical tasks. | |||||

Learning objective | This course intends to introduce students to fundamental numerical methods that form the foundation of numerical simulation in engineering. Students are to understand the principles of numerical methods, and will be taught how to assess, implement, and apply them. The focus of this class is on the numerical solution of ordinary differential equations. During the course they will become familiar with basic techniques and concepts of numerical analysis. They should be enabled to select and adapt suitable numerical methods for a particular problem. | |||||

Content | Quadrature, Newton method, initial value problems for ordinary differential equations: explicit one step methods, step length control, stability analysis and implicit methods, structure preserving methods | |||||

Literature | M. Hanke Bourgeois: Grundlagen der Numerischen Mathematik und des Wissenschaftlichen Rechnens, BG Teubner, Stuttgart, 2002. W. Dahmen, A. Reusken: Numerik für Ingenieure und Naturwissenschaftler, Springer, 2008. Extensive study of the literature is not necessary for the understanding of the lectures. | |||||

Prerequisites / Notice | Prerequisite is familiarity with basic calculus and linear algebra. | |||||

227-0052-10L | Electromagnetic Fields and Waves | O | 4 credits | 2V + 2U | L. Novotny | |

Abstract | This course is focused on the generation and propagation of electromagnetic fields. Based on Maxwell's equations we will derive the wave equation and its solutions. Specifically, we will discuss fields and waves in free space, refraction and reflection at plane interfaces, dipole radiation and Green functions, vector and scalar potentials, as well as gauge transformations. | |||||

Learning objective | Understanding of electromagnetic fields | |||||

227-0056-00L | Semiconductor Devices | O | 4 credits | 2V + 2U | C. Bolognesi | |

Abstract | The course covers the basic principles of semiconductor devices in micro-, opto-, and power electronics. It imparts knowledge both of the basic physics and on the operation principles of pn-junctions, diodes, contacts, bipolar transistors, MOS devices, solar cells, photodetectors, LEDs and laser diodes. | |||||

Learning objective | Understanding of the basic principles of semiconductor devices in micro-, opto-, and power electronics. | |||||

Content | Brief survey of the history of microelectronics. Basic physics: Crystal structure of solids, properties of silicon and other semiconductors, principles of quantum mechanics, band model, conductivity, dispersion relation, equilibrium statistics, transport equations, generation-recombination (G-R), Quasi-Fermi levels. Physical and electrical properties of the pn-junction. pn-diode: Characteristics, small-signal behaviour, G-R currents, ideality factor, junction breakdown. Contacts: Schottky contact, rectifying barrier, Ohmic contact, Heterojunctions. Bipolar transistor: Operation principles, modes of operation, characteristics, models, simulation. MOS devices: Band diagram, MOSFET operation, CV- and IV characteristics, frequency limitations and non-ideal behaviour. Optoelectronic devices: Optical absorption, solar cells, photodetector, LED, laser diode. | |||||

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

Literature | The lecture course follows the book Neamen, Semiconductor Physics and Devices, ISBN 978-007-108902-9, Fr. 89.00 | |||||

Prerequisites / Notice | Qualifications: Physics I+II | |||||

401-0604-00L | Probability Theory and Statistics | O | 4 credits | 2V + 1U | V. Tassion | |

Abstract | Probability models and applications, introduction to statistical estimation and statistical tests. | |||||

Learning objective | Ability to understand the covered methods and models from probability theory and to apply them in other contexts. Ability to perform basic statistical tests and to interpret the results. | |||||

Content | The concept of probability space and some classical models: the axioms of Kolmogorov, easy consequences, discrete models, densities, product spaces, relations between various models, distribution functions, transformations of probability distributions. Conditional probabilities, definition and examples, calculation of absolute probabilities from conditional probabilities, Bayes' formula, conditional distribution. Expectation of a random variable,application to coding, variance, covariance and correlation, linear estimator, law of large numbers, central limit theorem. Introduction to statistics: estimation of parameters and tests | |||||

Lecture notes | yes | |||||

Literature | Textbuch: P. Brémaud: 'An Introduction to Probabilistic Modeling', Springer, 1988. |

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