Search result: Catalogue data in Spring Semester 2020

Electrical Engineering and Information Technology Bachelor Information
Bachelor Studies (Programme Regulations 2018)
Examination Blocks
Examination Block 2
NumberTitleTypeECTSHoursLecturers
227-0013-00LComputer Engineering Information Restricted registration - show details O4 credits2V + 1U + 1PL. Thiele
AbstractThe 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 objectiveLogical 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.
ContentStructures 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 notesMaterial for practical training, copies of transparencies.
LiteratureD.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 / NoticePrerequisites: Programming skills in high level language, knowledge of digital design.
227-0046-10LSignals and Systems IIO4 credits2V + 2UJ. Lygeros
AbstractContinuous and discrete time linear system theory, state space methods, frequency domain methods, controllability, observability, stability.
Learning objectiveIntroduction to basic concepts of system theory.
ContentModeling 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 notesCopy of transparencies
LiteratureRecommended:
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
NumberTitleTypeECTSHoursLecturers
401-0654-00LNumerical Methods Information Restricted registration - show details O4 credits2V + 1UR. Käppeli
AbstractThe course introduces numerical methods according to the type of problem they tackle. The tutorials will include both theoretical exercises and practical tasks.
Learning objectiveThis 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.
ContentQuadrature, Newton method, initial value problems for ordinary differential equations: explicit one step methods, step length control, stability analysis and implicit methods, structure preserving methods
LiteratureM. 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 / NoticePrerequisite is familiarity with basic calculus and linear algebra.
227-0052-10LElectromagnetic Fields and Waves Information O4 credits2V + 2UL. Novotny
AbstractThis 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 objectiveUnderstanding of electromagnetic fields
227-0056-00LSemiconductor Devices Information O4 credits2V + 2UC. Bolognesi
AbstractThe 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 objectiveUnderstanding of the basic principles of semiconductor devices in micro-, opto-, and power electronics.
ContentBrief 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 notesLecture slides.
LiteratureThe lecture course follows the book Neamen, Semiconductor Physics and Devices, ISBN 978-007-108902-9, Fr. 89.00
Prerequisites / NoticeQualifications: Physics I+II
401-0604-00LProbability Theory and Statistics Information O4 credits2V + 1UV. Tassion
AbstractProbability models and applications, introduction to statistical estimation and statistical tests.
Learning objectiveAbility 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.
ContentThe 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 notesyes
LiteratureTextbuch: P. Brémaud: 'An Introduction to Probabilistic Modeling', Springer, 1988.
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