EEE5600 Introduction to Information and Coding TheoryBahçeşehir UniversityDegree Programs ARTIFICIAL INTELLIGENCE ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

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.

Basic information

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.

Learning Outcomes

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

Course Content

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.

Weekly Detailed Course Contents

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

Sources

Course Notes / Textbooks: Thomas and Cover, "Elements of Information Theory", 2nd Edition, Wiley.
References: none..........

Evaluation System

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

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Project 4 50
Midterms 8 60
Final 4 48
Total Workload 200

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Have sufficient background in mathematics, science and artificial intelligence engineering.
2) Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3) Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4) Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5) Select and use modern techniques and tools necessary for engineering applications.
6) Design and conduct experiments, collect data, and analyse and interpret results.
7) Work effectively both as an individual and as a multi-disciplinary team member.
8) Access information via conducting literature research, using databases and other resources
9) Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10) Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11) Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12) Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13) Have a sense of professional and ethical responsibility.
14) Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.