TEXTILE AND FASHION DESIGN | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
EEE5600 | Introduction to Information and Coding Theory | Spring | 3 | 0 | 3 | 12 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | |
Course Coordinator : | Assoc. Prof. SAEID KARAMZADEH |
Course Lecturer(s): |
Assoc. Prof. ALKAN SOYSAL |
Recommended Optional Program Components: | none.......... |
Course Objectives: | The aim of this course is to understand, in detail, basic information theory and coding theory arguments. Information theoretic analysis covers entropy/mutual information, source and channel coding. Coding theory analysis covers code construction, linear codes, cyclic and convolutional codes, near capacity codes. |
The students who have succeeded in this course; 1. Understand basic concepts and definitions of information theory 2. Know and apply source and channel coding theorems 3. Gain knowledge on code constructions 4. Understand basic concepts of coding theory 5. Apply modern error correcting codes |
This course covers basics of information theory and coding theory. The course starts with definitions of information theoretic quantities such as entropy, mutual information, etc. It covers Shannon's source coding theorem and explains Shannon codes and Huffman codes. Then Shannon's channel coding theorem is analyzed and capacity values of several channels are calculated. In the second half of the course, basic code construction methods are explained. Linear codes, cyclic codes, convolutional codes are introduced. |
Week | Subject | Related Preparation |
1) | Introduction to basic concepts of information transfer | |
2) | Define concepts of entropy, relative entropy, conditional entropy | |
3) | Definition of mutual information and its calculation for different scenarios. | |
4) | Source coding theorem | |
5) | Applications of source coding theorem: Shannon codes, Huffman codes | |
6) | Channel coding theorem | |
7) | Differential entropy | |
8) | Capacity calculations for different channel models. Midterm | |
9) | The Gaussian channel and its capacity | |
10) | Basics of code construction, Error detection and correction | |
11) | Linear block codes | |
12) | Cyclic codes | |
13) | Convolutional codes | |
14) | Near capacity codes |
Course Notes / Textbooks: | Thomas and Cover, "Elements of Information Theory", 2nd Edition, Wiley. |
References: | none.......... |
Semester Requirements | Number of Activities | Level of Contribution |
Project | 1 | % 30 |
Midterms | 1 | % 30 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 30 | |
PERCENTAGE OF FINAL WORK | % 70 | |
Total | % 100 |
Activities | Number of Activities | Workload |
Course Hours | 14 | 42 |
Project | 4 | 50 |
Midterms | 8 | 60 |
Final | 4 | 48 |
Total Workload | 200 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |