INFORMATION THEORY AND CODING
| Title | ΘΕΩΡΙΑ ΠΛΗΡΟΦΟΡΙΩΝ ΚΑΙ ΚΩΔΙΚΟΠΟΙΗΣΗ / INFORMATION THEORY AND CODING |
| Code | NNA-08-03 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Nikolaos Pleros |
| Common | No |
| Status | Active |
| Course ID | 40002943 |
Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)
Registered students: 25
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| GENIKĪ KATEUTHYNSĪ | Elective Courses | 8 | 4 | 5 |
| Academic Year | 2020 – 2021 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600180209
|
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600180209
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=8128
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
- English (Examination)
Prerequisites
General Prerequisites
basic knowledge on signal theory, basic knowledge on probabilities
Learning Outcomes
Knowledge: Knowing and understanding the basic principles and techniques if information theory, understanding coding techniques, knowing how to calculate the channel capacity.
Skills: Identify the appropriate coding scheme and optimize channel capacity. Solve exercises, present in front of an audience, search the corresponding literature.
General Competences
- Apply knowledge in practice
- Work autonomously
- Advance free, creative and causative thinking
Course Content (Syllabus)
Information – entropy (entropy, joint entropy, conditional entropy, memory and memoryless information sources), channel capacity (information channels, mutual information and capacity, lossless channels, uniform information channel, binary symmetric channel, binary erasure channel), coding in noiseless communications (Kraft inequality, Shannon’s theorem, typical codes (Shannon, Shannon-Fano, Huffmann, binary coding trees). Coding in noisy communications (decoding criteria, Fano’s limit, Shannon’s second theorem, Hamming code). Arithmetic coding, algebraic coding.
Keywords
information, entropy, channel, capacity, code
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | ✓ | |||
| Reading Assigment | 71 | ✓ | |||
| Project | 40 | ✓ | |||
| Total | 150 |
Student Assessment
Description
Written Exams
Student Assessment methods
- Written Assignment (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
1. ΘΕΩΡΙΑ ΠΛΗΡΟΦΟΡΙΩΝ - ΚΩΔΙΚΕΣ, ΒΟΥΚΑΛΗΣ ΔΗΜΗΤΡΙΟΣ, ΙΩΝ, ΑΘΗΝΑ, 1994
2. ΣΤΟΙΧΕΙΑ ΤΗΣ ΘΕΩΡΙΑΣ ΠΛΗΡΟΦΟΡΙΑΣ, COVER THOMAS M. THOMAS JOY A., ΠΕΚ
Additional bibliography for study
ΣΗΜΕΙΩΣΕΙΣ ΔΙΔΑΣΚΟΝΤΑ
Last Update
03-12-2020
