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Article
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SIAM Journal on Computing
Article . 1982 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2017
Data sources: DBLP
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Minimum Variance Huffman Codes

Minimum variance Huffman codes
Authors: Lawrence T. Kou;

Minimum Variance Huffman Codes

Abstract

Huffman’s well-known coding method constructs a minimum redundancy code which minimizes the expected value of the word length. In this paper, we characterize the minimum redundancy code with the minimum variance of the word length. An algorithm is given to construct such a code. It is shown that the code is in a certain sense unique. Furthermore, the code is also shown to have a strong property in that it minimizes a general class of functions of the minimum redundancy codes as long as the functions are nondecreasing with respect to the path lengths from the root to the internal nodes of the corresponding decoding trees.

Keywords

Prefix, length-variable, comma-free codes, algorithm, decoding trees, minimum variance of the word length, weights at internal nodes, minimum redundancy code, weights at leaves, Searching and sorting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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