Syllabus ( ELEC 633 )
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Basic information
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| Course title: |
Information Theory |
| Course code: |
ELEC 633 |
| Lecturer: |
Assoc. Prof. Dr. Serdar Süer ERDEM
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| ECTS credits: |
7.5 |
| GTU credits: |
3 (3+0+0) |
| Year, Semester: |
1, Fall and Spring |
| Level of course: |
Second Cycle (Master's) |
| Type of course: |
Area Elective
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| Language of instruction: |
English
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| Mode of delivery: |
Face to face
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| Pre- and co-requisites: |
none |
| Professional practice: |
No |
| Purpose of the course: |
Understanding the basics of the information theory |
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Learning outcomes
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Upon successful completion of this course, students will be able to:
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understand the basics of information theory
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Electronics Engineering
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Formulate and solve advanced engineering problems
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Manipulate knowledge and cooperate with multi-disciplines
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Acquire scientific knowledge
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Work effectively in multi-disciplinary research teams
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Find out new methods to improve his/her knowledge
Method of assessment
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Written exam
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Homework assignment
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have a deeper insight of the data communication applications, based on information theory
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Electronics Engineering
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Formulate and solve advanced engineering problems
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Manipulate knowledge and cooperate with multi-disciplines
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Acquire scientific knowledge
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Develop an awareness of continuous learning in relation with modern technology
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Demonstrate professional and ethical responsibility
Method of assessment
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Written exam
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Homework assignment
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understand the use of the probability theory for data communication and compression
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Electronics Engineering
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Formulate and solve advanced engineering problems
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Manipulate knowledge and cooperate with multi-disciplines
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Acquire scientific knowledge
-
Develop an awareness of continuous learning in relation with modern technology
-
Demonstrate professional and ethical responsibility
Method of assessment
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Written exam
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Homework assignment
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Contents
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| Week 1: |
Introduction, entropy |
| Week 2: |
Mathematical properties of entropy |
| Week 3: |
Asymptotic equipartition property (AEP), typical set, joint typicality |
| Week 4: |
Data compression, Kraft inequality, optimal codes |
| Week 5: |
Huffman codes |
| Week 6: |
Midterm exam |
| Week 7: |
Probability, random variables |
| Week 8: |
Entropy. |
| Week 9: |
Differential entropy 1 |
| Week 10: |
Differential entropy 2 |
| Week 11: |
Additive Gaussian noise channel |
| Week 12: |
Channel capacity, binary symmetric and erasure channels |
| Week 13: |
The channel coding theorem 1 |
| Week 14: |
The channel coding theorem 2 |
| Week 15*: |
review |
| Week 16*: |
Fınal Exam |
| Textbooks and materials: |
Cover, Thomas, and Joy Thomas. Elements of Information Theory. 2nd ed. New York, NY: Wiley-Interscience, 2006. |
| Recommended readings: |
lecture notes |
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* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
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Assessment
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| Method of assessment |
Week number |
Weight (%) |
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| Mid-terms: |
6 |
30 |
| Other in-term studies: |
0 |
0 |
| Project: |
0 |
0 |
| Homework: |
2,3,4,8,9,10,11 |
40 |
| Quiz: |
0 |
0 |
| Final exam: |
16 |
30 |
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Total weight: |
(%) |
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Workload
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| Activity |
Duration (Hours per week) |
Total number of weeks |
Total hours in term |
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| Courses (Face-to-face teaching): |
3 |
16 |
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| Own studies outside class: |
0 |
0 |
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| Practice, Recitation: |
0 |
0 |
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| Homework: |
6 |
16 |
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| Term project: |
0 |
0 |
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| Term project presentation: |
0 |
0 |
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| Quiz: |
0 |
0 |
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| Own study for mid-term exam: |
15 |
1 |
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| Mid-term: |
3 |
1 |
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| Personal studies for final exam: |
18 |
1 |
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| Final exam: |
3 |
1 |
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Total workload: |
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Total ECTS credits: |
* |
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* ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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