Fakultät für Ingenieurwissenschaften und Informatik Modulhandbuch Masterstudiengang Informationssystemtechnik Wintersemester 2013/14 Basierend auf Rev. 1106. Letzte Änderung am 13.09.2013 um 12:48 durch vpollex. Generiert am 13.09.2013 um 14:52 Uhr. Inhaltsverzeichnis 1 Advanced Channel Coding 5 2 Analog CMOS Circuit Design 8 3 Angewandte Diskrete Mathematik 10 4 Angewandte Numerik I 12 5 Angewandte Numerik II 14 6 Angewandte Stochastik II 16 7 Applied Information Theory 18 8 Architekturen für verteilte Internetdienste 21 9 Ausgewählte Methoden und Anwendungen in Computer Vision 23 10 Bildgebende Systeme in der Medizin 25 11 Channel Coding 27 12 Communication Systems 30 13 Communications Engineering 32 14 Compiler für Eingebettete Systeme 34 15 Compressed Sensing - Effiziente Informationserfassung 36 16 Computation in Cognitive and Neural Systems I - Introduction to Cognitive and Neural Modeling 40 17 Computation in Cognitive and Neural Systems II - Advanced Topics in Neural Modeling 42 18 Computer Vision II - Mehrbildanalyse 44 19 Cross-organizational distributed systems and Clouds 46 20 Datenkompression 48 21 Dialogue Systems 50 22 Digitale Regelungen 53 23 Echtzeitsysteme in Robotik und Regelungstechnik 55 24 Electronic System Design using C and SystemC 57 25 Embedded Security - Informationssicherheit in eingebetteten Systemen 59 26 Entwurf integrierter Systeme 63 27 Entwurf und Synthese von Digitalfiltern 66 28 Entwurfsmethodik Eingebetteter Systeme 68 29 Fahrerassistenzsysteme 70 30 Filter- und Trackingverfahren 72 31 Fortgeschrittene Konzepte der Rechnernetze 74 32 Grundlagen des Übersetzerbaus 76 2 33 Identifikation dynamischer Systeme 78 34 Individualprojekt Software Engineering und Compilerbau 80 35 Industriepraxis 82 36 Information Theory and Biology 84 37 Iterative Methods for Wireless Communications 87 38 Kommunikationsnetze 89 39 Kryptologie: Algorithmen und Methoden 91 40 Lab - Vector Network Analysis 93 41 Labor Eingebettete Systeme 95 42 Labor Softwareentwurf mit Multiparadigmen-Programmiersprachen 97 43 Masterarbeit 99 44 Methoden der Optimierung und optimalen Steuerung 100 45 Mikrowellensysteme 102 46 Mobile und Ubiquitous Computing 104 47 Mobilkommunikation 106 48 Modellbildung dynamischer Systeme 108 49 Multiagentensysteme 110 50 Multimediakommunikation 112 51 Multiuser Communications and MIMO Systems 114 52 Natural Computation - Computation in Natural Systems 116 53 Neural Networks and Pattern Classification 118 54 Nichtlineare Regelungen 120 55 Optoelectronic Devices 122 56 Praktikum Informationstechnik 124 57 Praktikum Mess- und Automatisierungstechnik 126 58 Praktikum Regelungstechnik 128 59 Praktische IT-Sicherheit 130 60 Project - Analog CMOS Circuit Design 132 61 Project - Design of Integrated Systems 134 62 Project - Dialogue Systems 136 63 Projekt - Hochautomatisiertes Fahren 138 64 Projekt Algorithmen der Echtzeitanalyse 140 65 Projekt Apollo Steuercomputer 142 66 Projekt Autonomes Fahrzeug 144 3 67 Projekt Echtzeitkommunikationssysteme 146 68 Projekt Entwicklungsmanagement eingebetteter Systeme 148 69 Projekt Middlewaresystem-Entwicklung 149 70 Projekt Middlewaresystem-Praxis 151 71 Projekt Smart Systems: Autonomous Under Water Vehicle 153 72 Radio Frequency Power Amplifier Design 155 73 Rechnerarchitektur 157 74 Rechnernetze und IT-Sicherheit für Informationssystemtechniker 159 75 Requirements Engineering 161 76 Satellite Communications and Navigation 163 77 Sicherheit in IT-Systemen 165 78 Sicherheit und Privacy in Mobilen Systemen 167 79 Systemtheorie 169 80 Theory of Digital Networks 171 81 Usability Engineering 173 82 Using the Advanced Design System (ADS) in Electronic Design 175 83 Videotechnologie 177 84 Vision in Man and Machine 180 85 Web Engineering 182 4 1 Advanced Channel Coding Kürzel / Nummer: 8834870442 Deutscher Titel: - Leistungspunkte: 4 ECTS Semesterwochenstunden: 3 Sprache: Englisch Turnus / Dauer: jedes Sommersemester / 1 Semester Modulverantwortlicher: Prof. Dr.-Ing. Martin Bossert Dozenten: Prof. Dr.-Ing. Georg Schmidt Einordnung des Moduls Elektrotechnik, M.Sc., Wahlpflichtmodul Ingenieurwissenschaften in Studiengänge: Elektrotechnik, M.Sc., Wahlmodul Komunikations- und Systemtechnik Elektrotechnik, M.Sc., Wahlmodul Automatisierungs- und Energietechnik Elektrotechnik, M.Sc., Wahlmodul Allgemeine Elektrotechnik Informationssystemtechnik, M.Sc., Wahlmodul Communications Technology, M.Sc., Technisches Wahlmodul Communications Engineering Voraussetzungen Bachelor. Linear Algebra, Probability Theory, Combinatorics, elementary Galois (inhaltlich): Theory Lernziele: The students can analyze, evaluate and compare coding schemes for error de- tection and error correction which are currently and in future systems used for data transmission, data storage, and data processing. Especially different deco- ding algorithms, those based on iterative methods as well as those based on algebraic methods can be categorized and combined. Inhalt: The contents of the lecture can be grouped into two blocks: iterative decoding methods and algebraic decoding methods, which are suited for different kinds of applications Iterative decoding methods are interesting for operating points close to capacity in applications where codes with large block lengths can be applied. In the lecture, two classes of iterative decoding schemes will be consi- dered. The class of Turbo Codes was introduced 1993 by C. Berrou, A. Glavieux and P. Thitimasjshima. A Turbo Code consists of simple parallel concatenated component codes, which can efficiently be decoded by a symbol-by-symbol A Posteriori Probability (s/s APP) decoder. Such an s/s APP decoder is capable of utilizing reliability information from the channel and can compute reliabilities for the code symbols. After formally introducing the concept of reliabilities on the basis of probabilities, the principle of s/s APP decoding will be explained. 5 Inhalt (Fortsetzung): After this, several tools for analyzing Turbo decoders are considered. Another class of iteratively decodable codes is the class of Low Density Single Parity Check (LDPC) codes. Such codes are either described by sparsely occupied ma- trices or by bipartite graphs. Both descriptions will be considered, and it will be explained how LDPC codes can be constructed on the basis of these descrip- tions. After explaining how LDPC codes can be decoded iteratively, tools for analyzing them will be considered. Algebraic decoding of Reed-Solomon (RS) codes is used in many technical data transmission and data storage systems like hard disks, CDs, DVDs, digital video broadcasting, and many other appli- cations. Two types of decoding strategies will be considered: syndrome-based decoding and interpolation-based decoding. Syndrome-based techniques for de- coding Reed-Solomon codes are known for more than 30 years, and allow for decoding errors up to half the minimum code distance. Since such methods can be implemented very efficiently, they are applied in many algebraic error correc- ting schemes. After introducing these classical syndrome-based methods, it will be explained how these techniques may be applied in interleaved Reed-Solomon (IRS) schemes for decoding errors beyond half the minimum code distance. In 1997, M. Sudan proposed a novel algorithm for decoding RS codes, which is based on bivariate polynomial interpolation. This algorithm can also decode errors beyond half the minimum code distance by creating lists of codewords to resolve ambiguous decoding situations. Moreover, derivatives of the Sudan algorithm are capable of using lists of symbols at their inputs. The principles behind such interpolation-based techniques will be considered in the last part of the lecture. It will be explained how the list decoding concept can be used for decoding errors beyond half the minimum code distance, and how the problem of list decoding is solved by the Sudan algorithm and its derivatives. Inhalt (Fortsetzung): In the exercise, students have the opportunity to implement selected algorithms from the lecture using MATLAB under guidance of a research assistant. Topics: Iterative Decoding Methods Turbo-Codes - A Posteriori Probability (APP) Decoding - Intrinsic and Extrinsic Information - Statistical Analysis Methods like Monte-Carlo Simulation and Exit-Chart- Ana- lysis Low Density Single Parity Check (LDPC) Codes - Matrix and Graph Representation of LDPC Codes - Code Construction - Iterative Decoding by "Message Passing" - Statistical and Graph-Based Analysis Methods like Density Evolution and Stop- ping Sets Algebraic Decoding Methods Syndrome-Based Techniques - Reed-Solomon (RS) Codes - Classical Decoding Approaches like the Peterson-Gorenstein-Zierler and Forney Algorithms - Interleaved Reed-Solomon (IRS) Codes and Collaborative Decoding Interpolation-Based Techniques - Interpretation of the Decoding Problem as a Polynomial Interpolation Problem - The Sudan Algorithm and its Derivatives - List Decoding Concepts 6 Literatur: - Roth R., Introduction to Coding Theory, Cambridge University Press, 2006 - Justesen J. and Hoeholdt, T., A Course In Error Correcting Codes, EMS Pu- blishing House, 2004 - Bossert M., Channel Coding for Telecommunications, John Wiley & Sons, 1999 - Blahut R. E., Algebraic Codes for Data Transmission, Cambridge University Press, 2003 - MacWilliams F. J. and Sloane N. J. A., The Theory of Error-Correcting Codes, Elsevier, 1977 Grundlage für: keine Angaben Lehrveranstaltungen Vorlesung “Advanced Channel Coding”, 2 SWS (V) () und Lehrformen: Übung “Advanced Channel Coding”, 1 SWS (Ü) () Abschätzung