|
課程名稱 |
消息理論
Information Theory |
|
開課學期 |
111-1 |
|
授課對象 |
電機資訊學院 電信工程學研究所 |
|
授課教師 |
王奕翔 |
|
課號 |
EE5028 |
|
課程識別碼 |
921EU1190 |
|
班次 |
|
|
學分 |
3.0 |
|
全/半年 |
半年 |
|
必/選修 |
選修 |
|
上課時間 |
星期二3,4(10:20~12:10)星期四6,7(13:20~15:10) |
|
上課地點 |
電二106電二106 |
|
備註 |
本課程以英語授課。上課時間:二34(10:30~11:50)、四67(13:50~15:10)。
總人數上限：30人 |
|
課程網頁 |
|
|
課程簡介影片 |
|
|
核心能力關聯 |
本課程尚未建立核心能力關連 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
Information Theory is a graduate level course (motivated undergraduate students are also welcome) designed for students who are interested in the quantitative fundamental limits of information. What is information and how to quantify information? What is the fundamental limits in representing information, delivering information, and learning information? In this course, we try to answer the above high-level questions with mathematical rigor.
We first introduce the fascinating theory originated from Claude E. Shannon, which addresses the above fundamental questions in the context of communication systems. We then provide algorithms that achieve these fundamental limits. Finally, advanced topics will be selectively overviewed in class and explored in final projects. |
|
課程目標 |
1. Introduce the fundamental limits in representing information (source coding), delivering information (channel coding), and learning information (statistical inference), along with the fundamental measures of information.
2. Develop algorithms to achieve these fundamental limits.
3. Explore advanced topics of information theory. |
|
課程要求 |
Prerequisite: Probability, Linear Algebra.
Grading: Homework (40%), Exam (30%), Project (30%). |
|
預期每週課後學習時數 |
6 hours (the average amount of time from the student feedback in Spring 2021). |
|
Office Hours |
|
|
指定閱讀 |
Lectures will be based on lecture notes and slides. Further information about assigned readings will be provided in the first lecture. |
|
參考書目 |
1. T. Cover and J. Thomas, Elements of Information Theory, Second Edition, Wiley-Interscience, 2006.
2. R. Gallager, Information Theory and Reliable Communications, Wiley, 1968.
3. I. Csiszar and J. Korner, Information Theory: Coding Theorems for Discrete Memoryless Systems, Second Edition, Cambridge University Press, 2011.
4. S. M. Moser, Information Theory (Lecture Notes), 6th Edition, ISI Lab, ETH Zürich, Switzerland, 2018.
5. Y. Polyanskiy and Y. Wu, Lecture notes on Information Theory, MIT (6.441), UIUC (ECE 563), Yale (STAT 664), 2012-2017. |
|
評量方式
(僅供參考) |
|
No. |
項目 |
百分比 |
說明 |
|
1. |
Homework |
40% |
|
2. |
Exam |
30% |
|
3. |
Project |
30% |
|
|
|
針對學生困難提供學生調整方式 |
|
上課形式 |
以錄影輔助 |
|
作業繳交方式 |
延長作業繳交期限 |
|
考試形式 |
|
|
其他 |
|
|
|