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Data compression Information theory
 

Summary: Data compression
&
Information theory
Gjerrit Meinsma
Mathematisch cafe 2-10-'03
Claude Elwood Shannon (1916-2001)
Mathematisch cafe 2-10-'03 1
Outline
1. Data compression
2. Universal compression algorithm
3. Mathematical model for `disorder' (information & entropy)
4. Connection entropy and data compression
5. `Written languages have high redundancy'
(70% can be thrown away)
Mathematisch cafe 2-10-'03 2
Data compression
For this LaTeX file:
# bytes after compression (gzip)
# bytes before compression
= 0.295

  

Source: Al Hanbali, Ahmad - Department of Applied Mathematics, Universiteit Twente

 

Collections: Engineering