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Information Theory

Course 0000001378 in WS 2015/6

General Data

Course Type Lecture w/ Exercise
Semester Weekly Hours 4 SWS
Organisational Unit Chair of Communications Engineering (Prof. Kramer)

and 1 singular or moved dates

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks Review of probability theory. Information theory for discrete and continuous variables: entropy, informational divergence, mutual information, inequalities. Coding of memoryless sources: rooted trees with probabilities, Kraft inequality, entropy bounds on source coding, Huffman codes, Tunstall codes. Coding of stationary sources: entropy bounds, Elias code for the positive integers, Elias-Willems universal source coding, hidden finite-memory sources. Channel coding: memoryless channels, block and bit error probability, random coding, converse, binary symmetric channel, binary erasure channel, symmetric channels, real and complex AWGN channels, parallel and vector AWGN channels, source and channel coding.
Links E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

WS 2014/5 Information Theory

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