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Protein Mechanics: from Single Molecule Force Spectroscopy toProtein-based Bi...
化工系膜中心学术论坛-MOF Chemistry: From design strategies to Applications
清华大学材料科学与工程研究院《材料科学论坛》学术报告:Multi-aspect characteri...
Brain-like spiking neural networks: A 4th generation of neural network models
报告题目:
Text-Compression using the Burrows-Wheeler Transform
 报告人:
Elad Verbin


报告时间:
2007-09-14 14:30
报告地点:
FIT-4-603
主办单位:
ITCS, Tsinghua University
  简介:

In 1994, Burrows and Wheeler introduced the Burrows-Wheeler Transform (BWT). Using the BWT they gave two new lossless text compression algorithms. A well known implementation of these algorithms is bzip2, which is installed in most unix environments. BWT-based text compressors are particularly easy to implement, and give quite good compression ratios. For example, bzip2 typically compresses text files to about 80% of what gzip does.

 

 

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