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Algorithms
Article . 2010 . Peer-reviewed
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Algorithms
Article
License: CC BY
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Algorithms
Article . 2010
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Article . 2010
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Article . 2010
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Interactive Compression of Digital Data

Authors: CARPENTIERI, Bruno;

Interactive Compression of Digital Data

Abstract

If we can use previous knowledge of the source (or the knowledge of a source that is correlated to the one we want to compress) to exploit the compression process then we can have significant gains in compression. By doing this in the fundamental source coding theorem we can substitute entropy with conditional entropy and we have a new theoretical limit that allows for better compression. To do this, when data compression is used for data transmission, we can assume some degree of interaction between the compressor and the decompressor that can allow a more efficient usage of the previous knowledge they both have of the source. In this paper we review previous work that applies interactive approaches to data compression and discuss this possibility.

Country
Italy
Keywords

Numerical Analysis, Industrial engineering. Management engineering, QA75.5-76.95, T55.4-60.8, conditional compression, Theoretical Computer Science, Computational Mathematics, Computational Theory and Mathematics, Electronic computers. Computer science, entropy, data compression

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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!
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