消息理論
Information Theory
學期
113-1
學分
3
學分
當期課號
535360
永久課號
EECM30063
開課單位
電信工程研究所
授課教師
黃昱智
校區
光復
類別
選修
上課時間表
| 節 | 週三 |
|---|---|
2 09:00–09:50 | 消息理論 ED103 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
概述
This course covers fundamentals of information theory, with applications drawn from data compression, communication over noisy channels, hypothesis testing, and coding for noiseless networks. The goal of this course is to develop the abilities of students: • To understand the basic language and tools of information theory; • To apply the basic tools of information theory to solve various communication engineering problems.
先修科目
Probability, Introduction to digital communication
評分方式
Homework and Quiz 30% Midterm 35% Final 35%
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction |
| 第 2 週 | Information measure (1/2) |
| 第 3 週 | Information measure (2/2) |
| 第 4 週 | Data compression (1/3) |
| 第 5 週 | Data compression (2/3) |
| 第 6 週 | Data compression (3/3) |
| 第 7 週 | Asymptotic equipartition property |
| 第 8 週 | Midterm exam |
| 第 9 週 | Channel coding theorem (1/2) |
| 第 10 週 | Channel coding theorem (2/2) |
| 第 11 週 | Polar codes |
| 第 12 週 | Differential entropy and continuous channel (1/2) |
| 第 13 週 | Differential entropy and continuous channel (2/2) |
| 第 14 週 | Gaussian multiple access channel and broadcast channel |
| 第 15 週 | Binary hypothesis testing |
| 第 16 週 | Final exam |
| 第 17 週 | Supplementary 1: Information-theoretic analysis of machine learning (1/2) |
| 第 18 週 | Supplementary 2: Information-theoretic analysis of machine learning (2/2) |
教科書
[1] F. Alajaji and P.-N. Chen, An Introduction to Single-User Information Theory, Springer, 2018 [2] T. Cover and J. Thomas, Elements of Information Theory 2nd edition, Wiley, 2006
Office Hours
- 地點
- ED 834
- 時間
- TBA