Search result: Catalogue data in Autumn Semester 2016

Computational Science and Engineering Bachelor Information
Bachelor Studies (Programme Regulations 2016)
First Year Compulsory Courses
First Year Examination Block 1
NumberTitleTypeECTSHoursLecturers
401-0151-00LLinear Algebra Information O4 credits3G + 2UV. C. Gradinaru, R. Käppeli
AbstractContents: 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.
ObjectiveEinführung in die Lineare Algebra für Ingenieure unter Berücksichtigung numerischer Aspekte
Lecture notesK. Nipp / D. Stoffer, Lineare Algebra, vdf Hochschulverlag, 5. Auflage 2002
LiteratureK. Nipp / D. Stoffer, Lineare Algebra, vdf Hochschulverlag, 5. Auflage 2002
252-0025-00LDiscrete MathematicsO7 credits4V + 2UU. Maurer
AbstractContent: Mathematical reasoning and proofs, abstraction. Sets, relations (e.g. equivalence and order relations), functions, (un-)countability, number theory, algebra (groups, rings, fields, polynomials, subalgebras, morphisms), logic (propositional and predicate logic, proof calculi).
ObjectiveThe primary goals of this course are (1) to introduce the most important concepts of discrete mathematics, (2) to understand and appreciate the role of abstraction and mathematical proofs, and (3) to discuss a number of applications, e.g. in cryptography, coding theory, and algorithm theory.
ContentSee course description.
Lecture notesavailable (in english)
227-0003-00LDigital CircuitsO4 credits2V + 2UG. Tröster
AbstractDigital 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.
ObjectiveProvide basic knowledge and methods to understand and to design digital circuits and systems.
ContentDigital 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 notesLecture notes for all lessons, assignments and solutions.
Textbook: Link
LiteratureLiterature will be announced during the lessons.
Prerequisites / NoticeNo special prerequisites
252-0835-00LComputer Science I Information O4 credits2V + 2UF. Friedrich Wicker
AbstractThe course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Teached language is C++. No programming experience is required.
ObjectivePrimary 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 secenes" when a program is translated and executed.
Secondary goals are an algorithmic computational thinking, undestanding the possibilities and limits of programming and to impart the way of thinking of a computer scientist.
ContentThe course covers fundamental data types, expressions and statements, (Limits of) computer arithmetic, control statements, functions, arrays, structural types and pointers. The part on object orientiation 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 notesA script written in English will be provided during the semeter. The script and slides will be made available for download on the course web page.
LiteratureBjarne 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.
Prerequisites / NoticeFrom AS 2013, an admission to the exam does not any more formally require an attending of the recitation sessions. Handing in solutions to the weekly exercise sheets is thus not mandatory, but we strongly recommend it.

Examination is a one hour-long written test.
First Year Examination Block 2
NumberTitleTypeECTSHoursLecturers
401-0231-10LAnalysis IO8 credits4V + 3UD. A. Salamon
AbstractCalculus of one variable: Real and complex numbers, vectors, limits, sequences, series, power series, continuous maps, differentiation and integration in one variable, introduction to ordinary differential equations
ObjectiveEinfuehrung in die Grundlagen der Analysis
Lecture notesKonrad Koenigsberger, Analysis I.
Christian Blatter: Ingenieur-Analysis (Kapitel 1-3)
Bachelor Studies (Programme Regulations 2012)
First Year
Course Units of the first year can be found in section Bachelor Studies (Programme Regulations 2016) - First Year Compulsory Courses.
Basic Courses
Block G1
NumberTitleTypeECTSHoursLecturers
401-0353-00LAnalysis IIIO4 credits2V + 1UE. Kowalski
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)
402-0811-00LProgramming Techniques for Scientific Simulations IO5 credits4GM. Troyer
AbstractThis lecture provides an overview of programming techniques for scientific simulations. The focus is on advances C++ programming techniques and scientific software libraries. Based on an overview over the hardware components of PCs and supercomputer, optimization methods for scientific simulation codes are explained.
Objective
401-0663-00LNumerical Methods for CSE Information O7 credits4V + 2UR. Hiptmair
AbstractThe course gives an introduction into fundamental techniques and algorithms of numerical mathematics which play a central role in numerical simulations in science and technology. The course focuses on fundamental ideas and algorithmic aspects of numerical methods. The exercises involve actual implementation of numerical methods in C++.
Objective* Knowledge of the fundamental algorithms in numerical mathematics
* Knowledge of the essential terms in numerical mathematics and the
techniques used for the analysis of numerical algorithms
* Ability to choose the appropriate numerical method for concrete problems
* Ability to interpret numerical results
* Ability to implement numerical algorithms afficiently
Content1. Direct Methods for linear systems of equations
2. Least Squares Techniques
3. Data Interpolation and Fitting
4. Filtering Algorithms
8. Approximation of Functions
9. Numerical Quadrature
10. Iterative Methods for non-linear systems of equations
11. Single Step Methods for ODEs
12. Stiff Integrators
Lecture notesLecture materials (PDF documents and codes) will be made available to participants:

Lecture document: Link

Lecture Git repository: Link

Tablet classroom notes: Link

Lecture recording: Link

Homework problems: Link
LiteratureU. ASCHER AND C. GREIF, A First Course in Numerical Methods, SIAM, Philadelphia, 2011.

A. QUARTERONI, R. SACCO, AND F. SALERI, Numerical mathematics, vol. 37 of Texts in Applied Mathematics, Springer, New York, 2000.

W. Dahmen, A. Reusken "Numerik für Ingenieure und Naturwissenschaftler", Springer 2006.

M. Hanke-Bourgeois "Grundlagen der Numerischen Mathematik und des wissenschaftlichen Rechnens", BG Teubner, 2002

P. Deuflhard and A. Hohmann, "Numerische Mathematik I", DeGruyter, 2002
Prerequisites / NoticeThe course will be accompanied by programming exercises in C++ relying on the template library EIGEN. Familiarity with C++, object oriented and generic programming is an advantage. Participants of the course are expected to learn C++ by themselves.
Block G2
NumberTitleTypeECTSHoursLecturers
401-0603-00LStochastics (Probability and Statistics)O4 credits2V + 1UM. H. Maathuis
AbstractThis class covers the following concepts: random variables, probability, discrete and continuous distributions, joint and conditional probabilities and distributions, the law of large numbers, the central limit theorem, descriptive statistics, statistical inference, inference for normally distributed data, point estimation, and two-sample tests.
ObjectiveKnowledge of the basic principles of probability and statistics.
ContentIntroduction to probability theory, some basic principles from mathematical statistics and basic methods for applied statistics.
Lecture notesLecture notes
LiteratureLecture notes
252-0834-00LInformation Systems for Engineers Information O4 credits2V + 1UR. Marti
AbstractFoundations of information systems from a user's viewpoint. The focus is on structured data: relational databases, the data language SQL, designing relational databases. Additional topics: Information Retrieval (searching documents), and estimating their relevance and authority with respect to free-text queries; XML as a format for data exchange; Characteristics and processing of "Big Data"
ObjectiveFollowing the course should enable students to

1. answer non-trivial queries on existing relational databases by formulating (entry-level) SQL statements, as well as to add new database content and to update or delete existing content,

2. formalize facts as perceived in the real world in terms of the entity-relationship model, and derive a set of normalized relations (tables) which define the structure of a relational database

3. explain how a database management system (DBMS) essentially works and what kind of services it provides

4. understand how a web search engine such as Google basically works

5. know and apply the core concepts to structure and query XML-documents

6. list the characteristics of "Big Data" and know the basics of processing "Big Data"
ContentDie Lehrveranstaltung vermittelt Grundlagen und Konzepte von Informationssystemen aus der Sicht eines Anwenders.

Im Zentrum stehen relationale Datenbanksysteme, die Abfrage- und Datenmanipulationssprache SQL, sowie der Entwurf bzw. die Strukturierung relationaler Datenbanken. Dieser Stoff wird auch in praktischen Übungen vertieft.

Weitere Themen sind der Umgang mit unstrukturierten und semistrukturierten Daten, die Integration von Daten aus verschiedenen autonomen Informationssystemen, sowie eine Übersicht der Architektur von Datenbanksystemen.

Inhalt:
1. Einleitung.
2. Das Relationenmodell.
3. Die Abfrage- und Datenmanipulationssprache SQL.
4. Entwurf relationaler Datenbanken mit Hilfe von Entity-Relationship Diagrammen. Grundideen der Normalisierung von Relationen.
5. Architektur relationaler Datenbanksysteme.
6. Information Retrieval: Suche von (Text-) Dokumenten. Indexing, Stopwort-Elimination und Stemming. Boole'sches Retrieval und das Verktorraum-Modell.
7. Web Information Retrieval: Web-Crawling. Ausnutzen der Web-Links zwischen Web-Seiten (Page Ranking). Das Zusammenspiel von Crawling, klassischem Information Retrieval und Page Ranking.
8. Modellierung semi-strukturierter Daten mit XML und einfache Anfragen mit XPath und XQuery.
9. Zugriff auf SQL-Datenbanken aus Programmen, Transaktionen.
10. Neuere Entwicklungen: "Big Data", CAP Theorem, Hadoop (HDFS als verteiltes File System, Map-Reduce als Verarbeitungskonzept)
LiteratureVorlesungsunterlagen (PowerPoint Folien, teilweise auch zusätzlicher Text) werden auf der Web-Site publiziert. Der Kauf eines Buches wird nicht vorausgesetzt.

Das Buch "Datenbanksysteme: Eine Einführung, 9. Auflage" von Alfons Kemper und André Eickler, erschienen im Oldenbourg Verlag, 2013, enthält den behandelten Stoff, und vieles mehr (Umfang: 848 Seiten!). Die Vorlesung ist jedoch nur teilweise auf das Buch abgestimmt.

Als englischsprachiges Werk kann z.B.

A. Silberschatz, H.F. Korth, S. Sudarshan:
Database System Concepts, 6th Edition, McGraw-Hill, 2010.

empfohlen werden (Umfang: 1349 Seiten).
Prerequisites / NoticeVoraussetzung:
Elementare Kenntnisse von Mengenlehre und logischen Ausdrücken.
Kenntnisse und minimale Programmiererfahrung in einer Programmiersprache wie z.B. Pascal, C, C++, Java, Python.
401-0647-00LIntroduction to Mathematical Optimization Information O5 credits2V + 1UD. Adjiashvili
AbstractIntroduction to basic techniques and problems in mathematical optimization, and their applications to problems in engineering.
ObjectiveThe goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering.
ContentTopics covered in this course include:
- Linear programming (simplex method, duality theory, shadow prices, ...).
- Basic combinatorial optimization problems (spanning trees, network flows, knapsack problem, ...).
- Modelling with mathematical optimization: applications of mathematical programming in engineering.
LiteratureInformation about relevant literature will be given in the lecture.
Prerequisites / NoticeThis course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics and more.
Block G3
All course units within Block G3 are offered in the spring semester.
Block G4
Students that enrol for the second year in the CSE Bachelor Programme and whose first year examination did not involve the subject "Physics I" will instead take the "Physics I and II" (402-0043-00L and 402-0044-00L) courses with performance assessment as a yearly course.
NumberTitleTypeECTSHoursLecturers
402-0043-00LPhysics IW4 credits3V + 1UT. Esslinger
AbstractIntroduction to the concepts and tools in physics with the help of demonstration experiments: mechanics of point-like and ridged bodies, periodic motion and mechanical waves.
ObjectiveThe concepts and tools in physics, as well as the methods of an experimental science are taught. The student should learn to identify, communicate and solve physical problems in his/her own field of science.
ContentMechanics (motion, Newton's laws, work and energy, conservation of momentum, rotation, gravitation, fluids)
Periodic Motion and Waves (periodic motion, mechanical waves, acoustics).
Lecture notesThe lecture follows the book "Physics" by Paul A. Tipler.
LiteraturePaul A. Tipler and Gene P. Mosca, Physics (for Scientists and Engineers), W. H. Freeman and Company
Prerequisites / NoticePrerequisites: Mathematics I & II
Core Courses
NumberTitleTypeECTSHoursLecturers
151-0107-20LHigh Performance Computing for Science and Engineering (HPCSE) IO4 credits4GM. Troyer, P. Chatzidoukas
AbstractThis course gives an introduction into algorithms and numerical methods for parallel computing for multi and many-core architectures and for applications from problems in science and engineering.
ObjectiveIntroduction to HPC for scientists and engineers
Fundamental of:
1. Parallel Computing Architectures
2. MultiCores
3. ManyCores
ContentProgramming models and languages:
1. C++ threading (2 weeks)
2. OpenMP (4 weeks)
3. MPI (5 weeks)

Computers and methods:
1. Hardware and architectures
2. Libraries
3. Particles: N-body solvers
4. Fields: PDEs
5. Stochastics: Monte Carlo
Lecture notesLink
Class notes, handouts
Fields of Specialization
Astrophysics
NumberTitleTypeECTSHoursLecturers
401-7851-00LTheoretical Astrophysics (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: AST512

Mind the enrolment deadlines at UZH:
Link
W10 credits4V + 2UR. Teyssier
AbstractRadiative processes in the interstellar medium; stellar structure and evolution; supernovae; white dwarfs; neutron stars; black holes; planet formation
Objective
Literature(1) "Formation of stars" (S. Stahler and F. Palla - Wiley editions, this is the book on which about half of the classes will be based and photocopies will be organized during first lecture)
(2) "Radiative processes in astrophysics" (R. Ribycki and A. Lightman)
(3) "The Physics of Stars" (A.C. Philllips)
(4) "Black Holes, White Dwarfs and Neutron Stars: The physics of compact objects" (S. Shapiro and S.A. Teukolski).
Additionally PowerPoint slides will be prepared by the lecturer on these and extra topics (e.g. planet formation).
Prerequisites / NoticePrerequisites: Elementary atomic physics, thermodynamics, mechanics, fluid dynamics.
Introduction to astrophysics (preferred but not obligatory).
401-7855-00LComputational Astrophysics (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: AST245

Mind the enrolment deadlines at UZH:
Link
W6 credits2VL. M. Mayer
AbstractAcquire knowledge of main methodologies for computer-based models of astrophysical systems,the physical equations behind them, and train such knowledge with simple examples of computer programmes
ObjectiveAcquire knowledge of main methodologies for computer-based models of astrophysical systems,the physical equations behind them, and train such knowledge with simple examples of computer programmes
Content1. Integration of ODE, Hamiltonians and Symplectic integration techniques, time adaptivity, time reversibility
2. Large-N gravity calculation, collisionless N-body systems and their simulation
3. Fast Fourier Transform and spectral methods in general
4. Eulerian Hydrodynamics: Upwinding, Riemann solvers, Limiters
5. Lagrangian Hydrodynamics: The SPH method
6. Resolution and instabilities in Hydrodynamics
7. Initial Conditions: Cosmological Simulations and Astrophysical Disks
8. Physical Approximations and Methods for Radiative Transfer in Astrophysics
LiteratureGalactic Dynamics (Binney & Tremaine, Princeton University Press),
Computer Simulation using Particles (Hockney & Eastwood CRC press),
Targeted journal reviews on computational methods for astrophysical fluids (SPH, AMR, moving mesh)
Prerequisites / NoticeSome knowledge of UNIX, scripting languages (see Link as an example), some prior experience programming, knowledge of C, C++ beneficial
Physics of the Atmosphere
NumberTitleTypeECTSHoursLecturers
701-0023-00LAtmosphere Information W3 credits2VH. Wernli, E. Fischer, T. Peter
AbstractBasic principles of the atmosphere, physical structure and chemical composition, trace gases, atmospheric cycles, circulation, stability, radiation, condensation, clouds, oxidation capacity and ozone layer.
ObjectiveUnderstanding of basic physical and chemical processes in the atmosphere. Understanding of mechanisms of and interactions between: weather - climate, atmosphere - ocean - continents, troposhere - stratosphere. Understanding of environmentally relevant structures and processes on vastly differing scales. Basis for the modelling of complex interrelations in the atmospehre.
ContentBasic principles of the atmosphere, physical structure and chemical composition, trace gases, atmospheric cycles, circulation, stability, radiation, condensation, clouds, oxidation capacity and ozone layer.
Lecture notesWritten information will be supplied.
Literature- John H. Seinfeld and Spyros N. Pandis, Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley, New York, 1998.
- Gösta H. Liljequist, Allgemeine Meteorologie, Vieweg, Braunschweig, 1974.
Chemistry
NumberTitleTypeECTSHoursLecturers
529-0004-00LComputer Simulation in Chemistry, Biology and Physics Restricted registration - show details W7 credits4GP. H. Hünenberger
AbstractMolecular models, Force fields, Boundary conditions, Electrostatic interactions, Molecular dynamics, Analysis of trajectories, Quantum-mechanical simulation, Structure refinement, Application to real systems. Exercises: Analysis of papers on computer simulation, Molecular simulation in practice, Validation of molecular dynamics simulation.

For more information: Link
ObjectiveIntroduction to computer simulation of (bio)molecular systems, development of skills to carry out and interpret computer simulations of biomolecular systems.
ContentMolecular models, Force fields, Spatial boundary conditions, Calculation of Coulomb forces, Molecular dynamics, Analysis of trajectories, Quantum-mechanical simulation, Structure refinement, Application to real systems. Exercises: Analysis of papers on computer simulation, Molecular simulation in practice, Validation of molecular dynamics simulation.
Lecture notesAvailable (copies of powerpoint slides distributed before each lecture)
LiteratureSee: Link
Prerequisites / NoticeSince the exercises on the computer do convey and test essentially different skills as those being conveyed during the lectures and tested at the oral exam, the results of the exercises are taken into account when evaluating the results of the exam.

For more information about the lecture: Link
Fluid Dynamics
NumberTitleTypeECTSHoursLecturers
151-0103-00LFluid Dynamics IIW3 credits2V + 1UP. Jenny
AbstractTwo-dimensional irrotational (potential) flows: stream function and potential, singularity method, unsteady flow, aerodynamic concepts.
Vorticity dynamics: vorticity and circulation, vorticity equation, vortex theorems of Helmholtz and Kelvin.
Compressible flows: isentropic flow along stream tube, normal and oblique shocks, Laval nozzle, Prandtl-Meyer expansion, viscous effects.
ObjectiveExpand basic knowledge of fluid dynamics.
Concepts, phenomena and quantitative description of irrotational (potential), rotational, and one-dimensional compressible flows.
ContentTwo-dimensional irrotational (potential) flows: stream function and potential, complex notation, singularity method, unsteady flow, aerodynamic concepts.
Vorticity dynamics: vorticity and circulation, vorticity equation, vortex theorems of Helmholtz and Kelvin.
Compressible flows: isentropic flow along stream tube, normal and oblique shocks, Laval nozzle, Prandtl-Meyer expansion, viscous effects.
Lecture notesLecture notes are available (in German).
(See also info on literature below.)
LiteratureRelevant chapters (corresponding to lecture notes) from the textbook

P.K. Kundu, I.M. Cohen, D.R. Dowling: Fluid Mechanics, Academic Press, 5th ed., 2011 (includes a free copy of the DVD "Multimedia Fluid Mechanics")

P.K. Kundu, I.M. Cohen, D.R. Dowling: Fluid Mechanics, Academic Press, 6th ed., 2015 (does NOT include a free copy of the DVD "Multimedia Fluid Mechanics")
Prerequisites / NoticeAnalysis I/II, Knowledge of Fluid Dynamics I, thermodynamics of ideal gas
Systems and Control
NumberTitleTypeECTSHoursLecturers
227-0103-00LControl Systems Information W6 credits2V + 2UF. Dörfler
AbstractStudy 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.
ObjectiveStudy 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.
ContentProcess 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.
LiteratureK. 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 / NoticePrerequisites: Signal and Systems Theory II.

MATLAB is used for system analysis and simulation.
227-0045-00LSignals and Systems IW4 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.
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