Search result: Catalogue data in Autumn Semester 2017

Electrical Engineering and Information Technology Bachelor Information
3. Semester
Examination Blocks
Examination Block 1
NumberTitleTypeECTSHoursLecturers
401-0353-00LAnalysis III Information O4 credits2V + 1UA. Figalli
AbstractIn this lecture we treat problems in applied analysis. The focus lies on the simplest cases of three fundamental types of partial differential equations of second order: the Laplace equation, the heat equation and the wave equation.
Objective
Content1.) Klassifizierung von PDE's
- linear, quasilinear, nicht-linear
- elliptisch, parabolisch, hyperbolisch

2.) Quasilineare PDE
- Methode der Charakteristiken (Beispiele)

3.) Elliptische PDE
- Bsp: Laplace-Gleichung
- Harmonische Funktionen, Maximumsprinzip, Mittelwerts-Formel.
- Methode der Variablenseparation.

4.) Parabolische PDE
- Bsp: Wärmeleitungsgleichung
- Bsp: Inverse Wärmeleitungsgleichung
- Methode der Variablenseparation

5.) Hyperbolische PDE
- Bsp: Wellengleichung
- Formel von d'Alembert in (1+1)-Dimensionen
- Methode der Variablenseparation

6.) Green'sche Funktionen
- Rechnen mit der Dirac-Deltafunktion
- Idee der Green'schen Funktionen (Beispiele)

7.) Ausblick auf numerische Methoden
- 5-Punkt-Diskretisierung des Laplace-Operators (Beispiele)
LiteratureY. Pinchover, J. Rubinstein, "An Introduction to Partial Differential Equations", Cambridge University Press (12. Mai 2005)

Zusätzliche Literatur:
Erwin Kreyszig, "Advanced Engineering Mathematics", John Wiley & Sons, Kap. 8, 11, 16 (sehr gutes Buch, als Referenz zu benutzen)
Norbert Hungerbühler, "Einführung in die partiellen Differentialgleichungen", vdf Hochschulverlag AG an der ETH Zürich.
G. Felder:Partielle Differenzialgleichungen.
Link
Prerequisites / NoticePrerequisites: Analysis I and II, Fourier series (Komplexe Analysis)
402-0053-00LPhysics IIO8 credits4V + 2UJ. Faist
AbstractThe goal of the Physics II class is an introduction to quantum mechanics
ObjectiveTo 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.
ContentContent:
- The Photon of Planck and Einstein
- 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 notesLecture notes (Some in as a Latex script and some hand-written) will be distributed via the Moodle interface
LiteratureDavid J. Griffiths, "Introduction to quantum mechanics" Second edition, Cambridge University Press.

Link
Prerequisites / NoticePrerequisites: Physics I.
227-0045-00LSignals and Systems IO4 credits2V + 2UH. Bölcskei
AbstractSignal 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).
ObjectiveIntroduction to mathematical signal processing and system theory.
ContentSignal 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 notesLecture notes, problem set with solutions.
227-0013-00LComputer Engineering I Information Restricted registration - show details O4 credits2V + 1U + 1PL. Thiele
AbstractThe course provides knowledge about structures and models of digital systems (abstract data types finite state automata, dependence and process graphs), assembler and compiler, control path and data path, pipelining, speculation techniques, superscalar computer architectures, memory hierarchy and virtual memory, operating system, processes and threads.
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), memory hierarchy and virtual memnory, software concepts.
ContentStructures and models of digital systems (abstract data types finite state automata, dependence and process graphs), 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.
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