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Error-Resilient LZW Data Compression

Authors: Yonghui Wu; Stefano Lonardi; Wojciech Szpankowski;

Error-Resilient LZW Data Compression

Abstract

Lossless data compression systems are typically regarded as very brittle to transmission errors. This limits their applicability to domains like noisy tetherless channels or file systems that can possibly get corrupted. Here we show how a popular lossless data compression scheme used in file formats GIF, PDF, and TIFF, among others, can be made error-resilient in such a way that the compression performance is minimally affected. The new scheme is designed to be backward-compatible, that is, a file compressed with our error-resilient algorithm can be still decompressed by the original decoder. In this preliminary report, we present our scheme, collect some experimental data supporting our claims, and provide some theoretical justifications.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
5
Average
Top 10%
Average
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