| Academic Year |
2024Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA128001 |
Subject Classification |
Specialized Education |
| Subject Name |
情報理論 |
Subject Name
（Katakana） |
ジョウホウリロン |
Subject Name in
English |
Information Theory |
| Instructor |
NAKANISHI TOORU |
Instructor
(Katakana) |
ナカニシ トオル |
| Campus |
Higashi-Hiroshima |
Semester/Term |
2nd-Year, First Semester, 2Term |
| Days, Periods, and Classrooms |
(2T) Weds7-8：ENG 219, (2T) Fri7-8：ENG 218 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Hybrid (Combination of face-to-face and online(simultaneous interactive)) |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
J
:
Japanese |
| Course Level |
3
:
Undergraduate High-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
|
| Keywords |
Entropy, Source coding, Channel coding, Cryptography |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | Explain fundamentals of information theory with models and expressions for information. This provides a part of foundations of information science. |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Computer Science Program
（Knowledge and Understanding）
・D1. Knowledge and ability to understand the theoretical framework underlying computer science and to collect and process high-dimensional data through full use of information processing technology based on scientific logic.
Data Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
・B. Ability to identify new problems independently and solve them through quantitative and logical thinking based on data, multifaceted perspectives, and advanced information processing and analysis.
Intelligence Science Program
（Knowledge and Understanding）
・D1. A deep systematic understanding of the advanced intelligence of human beings and its realization by computers. |
|---|
Class Objectives
/Class Outline |
As the fundamentals of information and communication, this class targets to learn entropy to measure information, source coding to efficiently represent information, and chennel coding to correct errors. In addition, this class targets to learn fundamental concepts of probability theory, and cryptography. |
| Class Schedule |
lesson1: Guidance
lesson2: Entropy (1)
lesson3: Entropy (2)
lesson4: Entropy (3)
lesson5: Source coding (1)
lesson6: Source coding (2)
lesson7: Source coding (3)
lesson8: Source coding (4)
lesson9: Markov information source, Excercise
lesson10: Channel coding (1)
lesson11: Channel coding (2)
lesson12: Channel coding (3)
lesson13: Channel coding (4)
lesson14: Excercise
lesson15: Cryptography
The final examination will be held. |
Text/Reference
Books,etc. |
Textbook: "情報・符号理論", Yuichi Kaji, Ohmsha |
PC or AV used in
Class,etc. |
|
| (More Details) |
Powerpoint, Textbook, Handouts |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Students should review the exercises in each lecture. |
| Requirements |
|
| Grading Method |
Evaluation based on exercises/small tests/reports (about 30%) and examinations (about 70%) |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |