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- Graduate School of Information Science and Engineering
- Graduate School of Decision Science and Technology
- Graduate School of Innovation Management
- Common Course of Graduate School
- Program for Leading Graduate Schools
- Academic unit or major
- Computer Science
- Instructor(s)
- Yamada Isao
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Mon7-8(W321) Thr7-8(W321)
- Group
- E
- Course number
- ZUS.M202
- Credits
- 2
- Academic year
- 2016
- Offered quarter
- 4Q
- Syllabus updated
- 2016/4/27
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course covers the information theory.
Student learning outcomes
Students will understand the information theory.
Keywords
Please refer to the corresponding Japanese description
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | ✔ Critical thinking skills | Practical and/or problem-solving skills |
Class flow
This course is lecture-centric and uses the passive learning.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Model of information and communication | None |
| Class 2 | Data compression 1 | None |
| Class 3 | Data compression 2 | None |
| Class 4 | Data compression 3 | None |
| Class 5 | Data compression 4 | None |
| Class 6 | Data compression 5 | None |
| Class 7 | Data compression 6 | None |
| Class 8 | Information and entropy 1 | None |
| Class 9 | Information and entropy 2 | None |
| Class 10 | Channel coding 1 | None |
| Class 11 | Channel coding 2 | None |
| Class 12 | Channel coding 3 | None |
| Class 13 | Channel coding 4 | None |
| Class 14 | Cryptography 1 | None |
| Class 15 | Cryptography 2 | None |
Textbook(s)
Please refer to the corresponding Japanese description
Reference books, course materials, etc.
Please refer to the corresponding Japanese description
Assessment criteria and methods
Grade evaluation is given by paper examination.
Related courses
- ZUS.M201 ： Probability Theory and Statistics
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Students should have a course credit of the probability and statistics.
