Syllabus Application
EE 410
Information and Coding Theory
Faculty
Faculty of Engineering and Natural Sciences
Semester
Spring 2025-2026
Course
EE 410 -
Information and Coding 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
Undergraduate
Course Credits
SU Credit:3, ECTS:6, Basic:1, Engineering:5
Prerequisites
( MATH 201 or MATH 212) and MATH 203
Corequisites
Course Type
Lecture
Instructor(s) Information
Özgür Erçetin
- Email: oercetin@sabanciuniv.edu
Hüseyin Özkan
- Email: hozkan@sabanciuniv.edu
Course Information
Catalog Course Description
Mathematical models for communication channels and sources; entropy, information, lossless data compression, Huffman coding, channel capacity, Shannon's theorems rate-distortion theory.
Course Learning Outcomes:
| 1. | Define the information content of an information source mathematically and define information theoretical measures such as entropy, conditional entropy, joint entropy mutual information, differential entropy etc. |
|---|---|
| 2. | Describe the fundamental limit in source coding and learn Shannon?s Source Coding Theorem |
| 3. | Design and implement some of the practical source codes |
| 4. | Describe the fundamental limit in maximum information rate at which the information is sent reliably and learn Shannon?s Channel Capacity Theorem. |
| 5. | Design and implement some of the practical channel codes |
| 6. | Describe the capacity of Gaussian Channel and optimal power allocation over Gaussian Channel using Water-Filling algorithm. |
| 7. | Describe the application of information theory to some of engineering problems through the course project. |
Course Objective
To learn about information, how to measure it and how to use it to better design inference systems.
Sustainable Development Goals (SDGs) Related to This Course:
| Clean Water and Sanitation | |
| Industry, Innovation and Infrastructure |
Course Materials
Resources:
Thomas and Cover, "Elements of Information Theory", 2nd Edition