Introductory Information Theory
Overview
This short course provides insight into Shannon's methods behind measuring communication channel capacity and reliability including coding, entropy, and multiple channels.
Recommended for those that have had some probability theory/statistics.
Estimated time required: 2 hours per week.
Keywords
Channel capacity
Channel capacity
Syllabus/Suggested Schedule
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Week 1: Coding, Entropy and Inequalities
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Introductory Information Theory - Overview -
Introductory Information Theory Part 1 - Coding -
Introductory Information Theory Part 1 - Entropy with Variance -
Introductory Information Theory Part 1 - Huffman Coding -
Lempel Ziv 77 Part 1 -
Lempel Ziv 77 Part 2 - C++ Program -
Introductory Information Theory Part 1 - Shannon's 1st Theorem -
Introductory Information Theory Part 1 - Kraft Inequality
Week 2: Channels & Information
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Introductory Information Theory Part 2 - Channels -
Introductory Information Theory Part 2 - Conditional and Joint Entropy Part 1 -
Introductory Information Theory Part 2 - Conditional and Joint Entropy Part 2 -
Introductory Information Theory Part 2 - Mutual Information -
Introductory Information Theory Part 2 - Information Theory Textbooks