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EE 654
Information Theory

Faculty Faculty of Engineering and Natural Sciences
Semester Spring 2025-2026
Course EE 654 - Information Theory
Time/Place
Time
Week Day
Place
Date
14:40-16:30
Wed
FENS-L047
Feb 16-May 22, 2026
14:40-15:30
Thu
FENS-L047
Feb 16-May 22, 2026
Level of course Masters
Course Credits SU Credit:3, ECTS:10
Prerequisites -
Corequisites -
Course Type Lecture

Instructor(s) Information

Özgür Erçetin
Hüseyin Özkan

Course Information

Catalog Course Description
Entropy and mutual information concepts, Markov chains and entropy rate. Shannon�s lossless source coding, channel capacity, white and colored Gaussian channels, rate distortion theory with applications to scalar and vector quantizer design. Multi-user information theory and applications.
Course Learning Outcomes:
1. Building a mathematical model of concrete concepts.
2. Understanding the limits of compression and transmission
3. Analyze and design compression and error correction control algorithms
Course Objective
To learn about information, how to measure it and how to use it to better design inference systems.
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Course Materials

Resources:
Thomas and Cover, "Elements of Information Theory", 2nd Edition
Technology Requirements:

Policies