Information theory

Lectures: 2 sessions / week, 1.5 hours / session

This is a graduate-level introduction to mathematics of information theory. We will cover both classical and modern topics (such as finite blocklength IT and applications to statistical decision theory). Those taking Information Theory for the first time may benefit from reading the standard textbook by T. Cover and J. Thomas (see below).

This course requires knowledge of theorem-proof exposition and probability theory, as taught in 6.042J Mathematics for Computer Science or 6.436J Fundamentals of Probability.

This course will cover the following topics:

In addition to the lecture notes, students may find the following text to be of use. Some homework problems will be assigned from the text.

T. Cover, and J. Thomas. Elements of Information Theory, Second Edition. Wiley-Interscience, 2006. ISBN: 9780471241959.

There will be weekly assigned problem sets, one take-home midterm, and one take-home final. Collaboration is allowed on the problem sets but not on the take-home exams. The final grade will be weighted as follows:

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