Data Compression


Criteria

Survey Formats

Basics

Basic Terms

Symbol

Set of Symbols

Alphabet

Code

Coding

Redundancy

Information Theory

Message

Probability

Information

Entropy

Calculation

Characteristics

Extreme Values

Diagram

Redundancy Reduction

Irrelevance Reduction

Entropy Coding

Variable Length Codes

Code Trees

Compression Methods

Data Formats


Glossary

Index


Download


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Extreme Values



Minimum:


If only one particular message appears, so the probability for this message is 1, the entropy of this information source reaches its minimum. The absolute value results in

(1 log2 1) -> 0.

This information source does not provide information, there is no uncertainty about the next message appearing.


If a particular message never appears, the entropy results in

(0 log2 0) -> 0.

Such a message also does not increase the information at the receiving side. The entropy and therefore the average code length will not be affected by those messages.


Maximum:


If any message will appear with the same probability, the entropy will get their maximum. In this case a potential receiver has the largest possible uncertainty about the nature of the next message. The gain of information consequently is the largest.


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Entropy Characteristics of Entropy Diagram: Entropy of a binary Information Source