Course title
M20930002
Introduction to Information Processing 

phan xuan tan
Course description
This course is about the measure, representation and communication of information. Since information theory is considered as subset of communication theory, there are two fundamental questions in communication theory that can be answered by information theory: What is ultimate data compression and what is the ultimate transmission rate of communication. Accordingly, lectures will focus on fundamental topics of information theory including information measures, lossless data compression, losssy data compression, channel coding, relations to and manifestations in other areas (e.g., blockchains, machine learning,etc.)
Purpose of class
The aim of this course is to provide fundamental knowledge of information theory to apply to a range of relevant real situations.
Goals and objectives

Goals and objectives Course Outcomes
1. Understand the fundamentals of information theory so that the beauty and utility of information science can be exposed
A-1
2. Understand the fundamental limits in communication system
A-1
3. Apply the equipped knowledge of information theory to various disciplines in information science
A-1
Language
English
Class schedule

Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Introduction to Information theory and its applications
Introduction to probability
Self-investigation on information theory 190分
2. Entropy - Relative Entropy - Mutual Entropy (I) Self-investigation on probability 190分
3. Entropy - Relative Entropy - Mutual Entropy (II) Read chapter 2 in the textbook 190分
4. Entropy - Relative Entropy - Mutual Entropy (III) Read chapter 2 in the textbook 190分
5. Asymptotic Equipartition Property and Entropy Rate of a stochastic process (I) Read chapter 3 and 4 in the textbook 190分
6. Asymptotic Equipartition Property and Entropy Rate of a stochastic process (II) Read chapter 3 and 4 in the textbook 190分
7. Data compression (I) Read chapter 5 in the textbook 190分
8. Mid-term exam and discussions on the solutions Preparation for mid-term exam 190分
9. Data compression (II) Read chapter 5 in the textbook 190分
10. Channel Capacity (I) Read chapter 7 in the textbook 190分
11. Channel Capacity (II) Read chapter 7 in the textbook 190分
12. Gaussian channel and Differential Entropy Read chapter 8 and 9 in the textbook 190分
13. - Rate distortion theory
- practical applications of information theory
Read chapter 10 in the textbook 190分
Investigate concepts in machine learning, image compression and blockchain technology
14. Final exam and discussions on the solutions Preparation for final exam 190分
Total. - - 2660分
Relationship between 'Goals and Objectives' and 'Course Outcomes'

Mid-term Final Total.
1. 10% 25% 35%
2. 10% 25% 35%
3. 10% 20% 30%
Total. 30% 70% -
Evaluation method and criteria
Midterm exam (30%) and Final Exam (70%) are the criteria of the grade. More than 60% of the total score is needed for getting the course credit.
<Note>
Students are marked absent from the class if they are late regardless of the delay time.
If students are absent from more than one third of the total number of classes, the credit of this course cannot be given to them.
Even though students are absent from the class whatever the reason, e.g. sickness, delay of public transportation systems, forgetting to bring the student ID card, it is counted as absence.
Textbooks and reference materials
Elements of information theory - 2nd edition, Thomas M. Cover, Joy A. Thomas, 2006
Prerequisites
Probability and statistics
Linear Algebra
Calculus I, II
Office hours and How to contact professors for questions
  • Weekdays: From 10:00 - 16:30 by email or face-to-face discussion at 4F-Research building office. Making an appointment beforehand is highly recommended.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
Most classes are interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
N/A N/A
Education related SDGs:the Sustainable Development Goals
    Last modified : Thu Nov 04 04:03:07 JST 2021