National Chengchi University
Uedu Main Site
Explore Uedu
Student Console
Register as Member/Login
Research Informed Consent Center
Survey Center
UeduGPTs
Aida Learning Companion
Agentic AI
Local AI
Uedu Code
Find an Advisor
Paper Reading
Uedu Note
Uedu Open
Uedu Jupyter
Language Learning
Lingua Writing
My Writing History
Cognomics Test Toolkit
Uedu Finance
Educational Big Data Challenge
Uedu Interdisciplinary General Education
Uedu Physics
Uedu Calculus
Uedu Biology
Uedu Chemistry
Uedu Electronics
Uedu Semiconductor
Uedu AI
Uedu Statistics
Uedu UAV
Teaching Materials
Literature Hall
Taiwan: Four Hundred Years
Uedu Science
Teacher Console
Course Setup
Support & Messages
Uptime Data

UeduGPTs

--

Jupyters

6

Local AI

--

Uedu Code

--

CISOSE26 Local AI Uedu Code UG26
政治大學 AQI 43 26°C PM2.5 9
AI Reply Desktop Notifications

Show a desktop notification when the AI TA finishes replying

Chat Message Notifications

Notify me when classmates post messages in the forum

Sound notification

Play an alert sound whenever there is a new notification

More settings
Account settings Data privacy settings Research Informed Consent Form
Uedu Open / Information Theory
6.441

Information Theory

Prof. Yury Polyanskiy | Spring 2016
Data Science, Analytics & Computer Technology Computer Science Science & Math Mathematics Engineering Applied Mathematics Computation Probability and Statistics
Go to original course
CC BY-NC-SA 4.0
Course introduction
This is a graduate-level introduction to mathematics of information theory. We will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.
Course Information
SourceMIT 開放式課程
DepartmentElectrical Engineering and Computer Science
LanguageEnglish
Number of videos0
Course videos (0)
No video materials are available for this Course yet
Go to the original course page to view