| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Information Theory | MEH544 | Elective | Master's degree | 1 | Fall | 10 |
Name of Lecturer(s)
Associate Prof. Dr. Sıtkı ÖZTÜRK
Learning Outcomes of the Course Unit
1) Defining the fundamental concepts of information theory
2) Explaining noiseless coding techniques
3) Calculating channel capacity
4) Applying coding techniques in the course of optimum
5) Explaining hamming coding and decoding
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | ||
| Learning Outcomes | ||||||||
| 1 | No relation | Low | Middle | Low | Low | High | Middle | |
| 2 | Low | Low | Middle | Low | Low | High | Middle | |
| 3 | Middle | Low | Middle | Low | Low | High | Middle | |
| 4 | Low | Low | Middle | Low | Low | High | Middle | |
| 5 | Low | Low | Middle | Low | Low | High | Middle | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Wireless Communications
Course Contents
This course equips candidates with in-depth knowledge on information measure, entropy, its properties, joint and conditional entropy, noiseless coding technique: uniquely decipherable and instantaneously decipherable codes, kraft inequality, noiseless coding theorem, huffman codes, lempel-ziv algorithm, discrete channel models: discrete memoryless channels, channel capacity and computing methods, decoding techniques: optimum and maximum likelihood decoding, noisy coding theorem, error correcting codes: linear block codes, generator and parity check matrices, syndrome, hamming codes, cyclic codes, BCH codes, convolutional codes, properties, encoder and decoder structures.
Weekly Schedule
1) Introduction, Source Model and Source Coding, Channel Models and Channel Coding2) Entrophy and Properties
3) Joint and Conditional Entrophy
4) Noiseless Coding Technique: Uniquely Decipherable and Instantaneously Decipherable Codes, Kraft Inequality
5) Noiseless Coding Theorem, Huffman Codes
6) Noiseless Coding Theorem, Lempel-Ziv Algorithm
7) Discrete Channel Models: Discrete Memoryless Channels
8) Midterm Examination/Assessment
9) Channel Capacity and Computing Methods
10) Channel Capacity Calculation Application
11) Decoding Techniques: Optimum and Maximum Probability Decoding
12) Noisy Coding Theorem
13) Error Correcting Codes: Linear Block Codes, Generator and Parity Check Matrices, Syndrome
14) Hamming Codes
15) Encoder and Decoder Structures
16) Final Examination
Recommended or Required Reading
1- Modern Digital and Analog Communication Systems, Bhagwandas Pannalal LATHI, Holt, Rinehart and Winston, 1989
2- Fundamentals Of Communication Systems, John G. Proakis, Masoud Salehi, Prentice Hall, 2004
3- Analog and Digital Comminication, Hwei P. Hsu, Schaum's Outline Series, McGraw-Hill, 1993
4- Bhagwandas Pannalal LATHI, “Modern Digital and Analog Communication Systems”, Holt, Rinehart and Winston, Inc. (1989)
5- Bhagwandas Pannalal LATHI, “Modern Digital and Analog Communication Systems”, Holt, Rinehart and Winston, Inc. (1989)
6- www.complextoreal.com
7- www.complextoreal.com
8- Bir sınav yapılacak
9- To do an exam
10- www.complextoreal.com
11- www.complextoreal.com
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
5) Group Study
6) Self Study
7) Problem Solving
Assessment Methods and Criteria
Contribution of Semester Studies to Course Grade |
40% |
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Contribution of Final Examination to Course Grade |
60% |
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Total | 100% | |||||||||||
Language of Instruction
Turkish
Work Placement(s)
Not Required