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 6.041 as a prerequisite.

6.441 will not be offered this semester. It will be available in the Spring semester, and will be instructed by L. Zheng, M. Medard and Y. Polyanskiy.

Lecture occurs 11:00 AM to 12:30 PM on Tuesdays and Thursdays in 34-301.

This class counts for a total of 12 credits.

In the Spring 2016 Subject Evaluations, 6.441 was rated 6.9 out of 7.0. You can find more information on MIT OpenCourseWare at the Information Theory site or on the 6.441 Stellar site.

MIT 6.441 Information Theory Related Textbooks
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Information Theory
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