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YouTube

Information Theory and Network Coding

Center for Science of Information NSF STC via YouTube

Overview

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Explore the fundamental principles of information theory through this comprehensive video lecture series taught by Prof. Raymond Yeung from the Chinese University of Hong Kong. Master the mathematical foundations that govern communication systems, data compression, and information transmission across 15+ hours of structured content based on the widely-adopted textbook "Information Theory and Network Coding." Begin with the science of information and information measures, then progress through advanced topics including the I-Measure, zero-error data compression, weak and strong typicality, discrete memoryless channels, rate-distortion theory, and the Blahut-Arimoto algorithms. Delve into differential entropy and continuous-valued channels to complete your understanding of both discrete and continuous information systems. Develop the ability to analyze fundamental limits in communication systems, apply information-theoretic concepts across various disciplines in information science, and gain deeper insights into how communication systems operate at their theoretical boundaries. Each week builds systematically on previous concepts, covering 11 comprehensive chapters with detailed subsections that break down complex mathematical concepts into digestible segments. Gain proficiency in calculating entropy, mutual information, and channel capacity while understanding the theoretical underpinnings that drive modern digital communication, data storage, and network coding applications.

Syllabus

IT Week1 - Introduction
IT Week1 - Chapter 1
IT Week1 Chapter 2.1a
IT Week1 Chapter 2.1b
IT Week1 Chapter 2.1c
IT Week1 Chapter 2.2
IT Week1 Chapter 2.3
IT Week2
IT Week1 Chapter 2.4
IT Week1 Chapter 2.5
IT Week1 Chapter 2.6
IT Week1 Chapter 2.7
IT Week1 Chapter 2.8
IT Week1 Chapter 2.10
IT Week3 Introduction
IT Week3 Chapter 3.1
IT Week3 Chapter 3.3a
IT Week3 Chapter 3.3b
IT Week3 Chapter 3.4
IT Week3 Chapter 3.5a
IT Week4 Introduction
IT Week4 Chapter 3.5b
IT Week4 Chapter 3.6a
IT Week4 Chapter 3.6b
IT Week4 Chapter 4.1
IT Week4 Chapter 4.2a
IT Week5 Introduction
IT Week5 Chapter 4.2b
IT Week5 Chapter 4.2c
IT Week5 Chapter 4.3
IT Week5 Chapter 5.1
IT Week5 Chapter 5.2
IT Week6 Introduction
IT Week6 Chapter 6.1a
IT Week6 Chapter 6.1b
IT Week6 Chapter 6.2
IT Week6 Chapter 6.3a
IT Week6 Chapter 6.3b
IT Week6 Chapter 6.4
IT Week7 Introduction
IT Week7 Chapter 7.1a
IT Week7 Chapter 7.1b
IT Week7 Chapter 7.2
IT Week7 Chapter 7.3a
IT Week7 Chapter 7.3b
IT Week8 Introduction
IT Week8 Chapter 7.4a
IT Week8 Chapter 7.4b
IT Week8 Chapter 7.5
IT Week8 Chapter 7.6
IT Week8 Chapter 7.7
IT Week9 Introduction
IT Week9 Chapter 8.1
IT Week9 Chapter 8.2
IT Week9 Chapter 8.3a
IT Week9 Chapter 8.3b
IT Week9 Chapter 8.4
IT Week10 Introduction
IT Week10 Chapter 8.5a
IT Week 10 Chapter 8.5b
IT Week10 Chapter 9.1
IT Week10 Chapter 9.2a
IT Week10 Chapter 9.2b
IT Week11 Introduction
IT Week 11 Chapter 9.2c
IT Week 11 Chapter 9.3
IT Week 11 Chapter 10.1a
IT Week 11 Chapter 10.1b
IT Week12 Introduction
IT Week12 Chapter 10.2
IT Week12 Chapter 10.3a
IT Week12 Chapter 10.3b
IT Week12 Chapter 10.4
IT Week12 Chapter 10.5
IT Week12 Chapter 10.6
IT Week13 Introduction
IT Week13 Chapter 11.1
IT Week13 Chapter 11.2
IT Week13 Chapter 11.3a
IT Week13 Chapter 11.3b
IT Week14 Introduction
IT Week14 Chapter 11.4
IT Week14 Chapter 11.5
IT Week14 Chapter 11.6
IT Week15 Introduction
IT Week15 Chapter 11.7a
IT Week15 Chapter 11.7b
IT Week15 Chapter 11.8
IT Week15 Chapter 11.9

Taught by

Center for Science of Information NSF STC

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