6.441 Information Theory

Class Info

Mathematical definitions of information measures, convexity, continuity, and variational properties. Lossless source coding; variable-length and block compression; Slepian-Wolf theorem; ergodic sources and Shannon-McMillan theorem. Hypothesis testing, large deviations and I-projection. Fundamental limits of block coding for noisy channels: capacity, dispersion, finite blocklength bounds. Coding with feedback. Joint source-channel problem. Rate-distortion theory, vector quantizers. Advanced topics include Gelfand-Pinsker problem, multiple access channels, broadcast channels (depending on available time).

This class has 6.041B as a prerequisite.

6.441 will be offered this semester (Spring 2019). It is instructed by M. Medard, Y. Polyanskiy and L. Zheng.

Lecture occurs 11:00 AM to 12:30 PM on Tuesdays and Thursdays in 4-149.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+6.441&btnG=Google+Search&inurl=https site.

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