Optimal merging algorithms for lossless codes with generalized criteria

Themistoklis Charalambous, Charalambos D. Charalambous, Farzad Rezaei

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper presents lossless prefix codes optimized with respect to a payoff criterion consisting of a convex combination of maximum codeword length and average codeword length. The optimal codeword lengths obtained are based on a new coding algorithm, which transforms the initial source probability vector into a new probability vector according to a merging rule. The coding algorithm is equivalent to a partition of the source alphabet into disjoint sets on which a new transformed probability vector is defined as a function of the initial source probability vector and scalar parameter. The payoff criterion considered encompasses a tradeoff between maximum and average codeword length; it is related to a payoff criterion consisting of a convex combination of average codeword length and average of an exponential function of the codeword length, and to an average codeword length payoff criterion subject to a limited length constraint. A special case of the first related payoff is connected to coding problems involving source probability uncertainty and codeword overflow probability, whereas the second related payoff compliments limited length Huffman coding algorithms.

Original languageEnglish
Article number6851189
Pages (from-to)5486-5499
Number of pages14
JournalIEEE Transactions on Information Theory
Volume60
Issue number9
DOIs
Publication statusPublished - 2014
MoE publication typeA1 Journal article-refereed

Keywords

  • Lossless coding
  • merging algorithms
  • multiobjective criteria

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