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Lecture 5: Entropy and Data Compression (IV): Shannon's Source Coding Theorem, Symbol Codes and Arithmetic Coding thumbnail
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Lecture 5: Entropy and Data Compression (IV): Shannon's Source Coding Theorem, Symbol Codes and Arithmetic Coding

Published on Nov 05, 201217836 Views

David MacKay

Course on Information Theory, Pattern Recognition, and Neural Networks

Related categories

Bayesian LearningNeural NetworksPattern RecognitionInformation Theory

Chapter list

Outline00:00
Practical Data Compression00:26
Symbol Codes00:52
Last Time01:04
What Is The Optimal Symbol Code For (I)01:59
What Is The Optimal Symbol Code For (II)02:07
What Is The Optimal Symbol Code For (III)03:02
Prefix Codes Suffice (I)04:51
Prefix Codes Suffice (II)06:56
Symbol Code Summary07:10
Today07:31
Bent Coin07:46
The Guessing Game (I)09:14
The Guessing Game (II)10:37
The Guessing Game (III)12:40
The Guessing Game (IV)13:05
The Guessing Game (V)13:54
The Guessing Game (VI)14:59
The Guessing Game (VII)19:35
The Guessing Game (VIII)20:18
The Guessing Game (IX)20:21
Realistic Compression (I)21:11
Realistic Compression (II)22:54
Realistic Compression (III)23:25
Three Tasks (I)31:07
Three Tasks (II)31:52
Three Tasks (III)32:48
Arithmetic Coding (I)34:40
Arithmetic Coding (II)37:41
Arithmetic Coding (III)39:02
Arithmetic Coding (IV)40:05
Arithmetic Coding (V)45:15
Arithmetic Coding (VI)47:51
Arithmetic Coding (VII)50:55
Arithmetic Coding (VIII)52:16
Arithmetic Coding (IX)54:40
Arithmetic Coding (X)55:18
Arithmetic Coding (XI)57:44
Dasher59:44
Next Time01:02:00
Recommended Exercises01:02:29