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Minimum-Redundancy Coding

  • Alistair Moffat
  • Andrew Turpin
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 669)

Abstract

We now turn to the more general case illustrated by the “Code 3” column in Table 1.1 on page 7. It is the best of the three listed codes because, somehow, its set of codeword lengths better matches the probability distribution than do the other two sets. Which forces the question: given a sorted list of symbol probabilities, how can a set of prefix-free codewords be assigned that is best for that data? And what is really meant by “best”?

Keywords

Code Algorithm Huffman Code Symbol Number Codeword Length Prefix Code 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Alistair Moffat
    • 1
  • Andrew Turpin
    • 2
  1. 1.The University of MelbourneAustralia
  2. 2.Curtin University of TechnologyAustralia

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