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Near-lossless compression of large alphabet sources

Authors: Benjamin G. Kelly; Aaron B. Wagner;

Near-lossless compression of large alphabet sources

Abstract

We study universal compression of independent and identically distributed sources over large alphabets using fixed-rate codes. To model large alphabets, we use sequences of discrete alphabets that increase in size with the blocklength. We show that universal compression is possible using deterministic codes provided that the alphabet growth is sub-linear in the blocklength. For linear alphabet growth, we show that universal compression is not possible, even if the use of randomized encoders and decoders is permitted. However, if only the decoder is provided with the source distribution, then randomized universal coding is always possible for any growth rate. For the non-universal case in which the goal is to compress a source generated by a known sequence of distributions, we show that compression at the entropy of the source sequence is possible if and only if the ratio of the square logarithm of the alphabet size to the blocklength goes to zero.

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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!
3
Average
Average
Average
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