UnivIS
Information system of Friedrich-Alexander-University Erlangen-Nuremberg © Config eG 
FAU Logo
  Collection/class schedule    module collection Home  |  Legal Matters  |  Contact  |  Help    
search:      semester:   
ACHTUNG: seit 15.06.2022 werden Lecture list nur noch über Campo verwaltet. Diese Daten in UnivIS sind nicht mehr auf aktuellem Stand!
 
 Layout
 
printable version

 
 

  Information Theory and Coding (ITC(A))

Lecturer
Prof. Dr.-Ing. Ralf Müller

Details
Vorlesung
Präsenz
3 cred.h, ECTS studies, ECTS credits: 5
nur Fachstudium, Sprache Englisch
Time and place: Mon 10:15 - 11:45, KS I; Wed 16:15 - 17:45, H6

Fields of study
WF EEI-BA 5-6
PF EEI-MA-INT 1-4
PF CE-BA-TA-IT 5
WF CE-MA-TA-IT 1
PF EEI-BA-INT 5-6
WF IuK-BA 5
PF ICT-MA-NDC 1-4
WPF ICT-MA-ES 1-4
WPF ICT-MA-MPS 1-4
WPF WING-BA-IKS-ING-MG1 5-6
WPF WING-MA 1-3
WPF WING-MA-ET-IT 1-3
WPF WING-BA-ET-IT 5-6
PF CME-MA 1
PF ASC-MA 1
WPF INF-NF-EEI 1-4

Contents
Introduction to coding and information theory (binomial distribution, (7,4)-Hamming code, parity-check matrix, generator matrix); Probability, entropy, and inference (entropy, conditional probability, Bayes’ law, likelihood, Jensen’s inequality); Inference (inverse probability, statistical inference); Source coding theorem (information content, typical sequences, Chebychev inequality, law of large numbers); Symbol codes (unique decidability, expected codeword length, prefix-free codes, Kraft inequality, Huffman coding); Stream codes (arithmetic coding, Lempel-Ziv coding, Burrows-Wheeler transform); Dependent random variables (mutual information, data processing lemma); Communication over a noisy channel (discrete memory-less channel, channel coding theorem, channel capacity); Noisy-channel coding theorem (jointly-typical sequences, proof of the channel coding theorem, proof of converse, symmetric channels); Gaussian channel (AWGN channel, multivariate Gaussian pdf, capacity of AWGN channel); Binary codes (minimum distance, perfect codes, why perfect codes are bad, why distance isn’t everything); Message passing (distributed counting, path counting, low-cost path, min-sum (=Viterbi) algorithm); Marginalization in graphs (factor graphs, sum-product algorithm); Low-density parity-check codes (density evolution, check node degree, regular vs. irregular codes, girth); Lossy source coding (transform coding and JPEG compression) (automatisch geplant, erwartete Hörerzahl original: 85, fixe Veranstaltung: nein)

ECTS information:
Credits: 5

Additional information
Expected participants: 83

Assigned lectures
UE ([hybrid]):Tutorial for Information Theory and Coding
Time and place:

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2022/2023:
Information Theory and Coding (ITC)

Department: Institute for Digital Communications (IDC) (Prof. Dr. Schober)
UnivIS is a product of Config eG, Buckenhof