Course

COM-102: Advanced information, computation, communication II

Summary

Text, sound, and images are examples of information sources stored in our computers and/or communicated over the Internet. How do we measure, compress, and protect the informatin they contain?

Lectures

Instructor

Michael Christoph Gastpar

Michael Gastpar is a (full) Professor at EPFL. From 2003 to 2011, he was a professor at the University of California at Berkeley, earning his tenure in 2008. He received his Dipl. El.-Ing. degree from ETH Zürich, Switzerland, in 1997 and his MS degree from the University of Illinois at Urbana-Champaign, IL, USA, in 1999. He defended his doctoral thesis at EPFL on Santa Claus day, 2002. He was also a (full) Professor at Delft University of Technology, The Netherlands. His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience. He is a Fellow of the IEEE. He is the co-recipient of the 2013 Communications Society & Information Theory Society Joint Paper Award. He was an Information Theory Society Distinguished Lecturer (2009-2011). He won an ERC Starting Grant in 2010, an Okawa Foundation Research Grant in 2008, an NSF CAREER award in 2004, and the 2002 EPFL Best Thesis Award. He has served as an Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11), and as Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory, Austin, TX.

Official source

https://edu.epfl.ch/coursebook/en/advanced-information-computation-communication-ii-COM-102

Moodle Page

http://go.epfl.ch/COM-102

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Summary

Text, sound, and images are examples of information sources stored in our computers and/or communicated over the Internet. How do we measure, compress, and protect the informatin they contain?

Lectures

Instructor

Michael Christoph Gastpar

Official source

https://edu.epfl.ch/coursebook/en/advanced-information-computation-communication-ii-COM-102

Moodle Page

http://go.epfl.ch/COM-102

Lectures in this course (54)

Information Coding: Source, Cryptography, Channel

Covers source coding, cryptography, and channel coding for communication systems.

Law of Total Probability

Explores the Law of Total Probability and its applications in real-world scenarios, introducing key concepts in probability theory.

Information Theory Basics

Introduces information theory basics, including entropy, independence, and binary entropy function.

Source Coding: Compression

Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.

Kraft-McMillan Theorem

Explores the Kraft-McMillan theorem, proving the existence of uniquely decodable prefix-free codes.

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