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Variable-length Codes for Data Compression

Bag om Variable-length Codes for Data Compression

Most data compression methods that are based on variable-length codes employ the Huffman or Golomb codes. However, there are a large number of less-known codes that have useful properties - such as those containing certain bit patterns, or which are robust - and these can be useful. This book brings this large set of codes to the attention of workers in the field and of students of computer science. David Salomon¿s crystal clear style of writing and presentation, which has been familiar to readers for many years now allows easy access to the topic. Readers are only required to have a general familiarity with computer methods and essentially an understanding of the representation of data in bits and files. Computer scientists, electrical engineers and students majoring in computer science or electrical engineering will find this volume an invaluable resource, as will those readers in various physical sciences and mathematics.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781846289583
  • Indbinding:
  • Paperback
  • Sideantal:
  • 208
  • Udgivet:
  • 25. oktober 2007
  • Størrelse:
  • 170x12x244 mm.
  • Vægt:
  • 369 g.
Leveringstid: 8-11 hverdage
Forventet levering: 16. januar 2025
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Variable-length Codes for Data Compression

Most data compression methods that are based on variable-length codes employ the Huffman or Golomb codes. However, there are a large number of less-known codes that have useful properties - such as those containing certain bit patterns, or which are robust - and these can be useful. This book brings this large set of codes to the attention of workers in the field and of students of computer science.
David Salomon¿s crystal clear style of writing and presentation, which has been familiar to readers for many years now allows easy access to the topic. Readers are only required to have a general familiarity with computer methods and essentially an understanding of the representation of data in bits and files.
Computer scientists, electrical engineers and students majoring in computer science or electrical engineering will find this volume an invaluable resource, as will those readers in various physical sciences and mathematics.

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