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MATH 474 Information Theory Units: 3.00
Topics include: information measures, entropy, mutual information, modeling of information sources, lossless data compression, block encoding, variable-length encoding, Kraft inequality, fundamentals of channel coding, channel capacity, rate-distortion theory, lossy data compression, rate-distortion theorem. Given jointly with MATH 874.
Learning Hours: 140 (36 Lecture, 104 Private Study)
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Computing Shannon's information measures (entropy, Kullback-Leibler distance and mutual information).
- Computing the capacity of communication channels.
- Reasoning about the properties of Shannon's information measures (entropy, Kullback-Leibler distance and mutual information).
- Using mathematical tools to infer properties of coding and communication systems.
- Working with probabilistic modeling of communication systems for source and channel coding purposes.
- Using tools from probability theory to analyze communication systems.
- Working with metric assessment of data compression code designs.