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Elektrotechnik, Elektronik und Informationstechnik (Bachelor of Science) >>
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Information Theory and Coding (ITC)- Dozentinnen/Dozenten
- Prof. Dr.-Ing. Ralf Müller, Dr.-Ing. Ali Bereyhi
- Angaben
- Vorlesung
3 SWS, ECTS-Studium, ECTS-Credits: 5
nur Fachstudium, Sprache Englisch
Zeit und Ort: Mo 14:15 - 15:45, H6; Di 10:15 - 11:45, H6
- Studienfächer / Studienrichtungen
- 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
- Inhalt
- 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)
- ECTS-Informationen:
- Credits: 5
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 90
www: https://www.studon.fau.de/crs3253106.html
Für diese Lehrveranstaltung ist eine Anmeldung erforderlich.
Die Anmeldung erfolgt über: StudOn
- Zugeordnete Lehrveranstaltungen
- UE: Tutorial for Information Theory and Coding
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Dozent/in: Dr.-Ing. Ali Bereyhi
Zeit und Ort: n.V.
www: https://www.studon.fau.de/crs3253106.html
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2020/2021:
- Information Theory and Coding (ITC)
- Institution: Lehrstuhl für Digitale Übertragung
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