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IEEE Transactions on Information Theory
Article . 2001 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Article . 2001
Data sources: zbMATH Open
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Article . 2001
Data sources: DBLP
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Expander graph arguments for message-passing algorithms

Authors: David Burshtein; Gadi Miller;

Expander graph arguments for message-passing algorithms

Abstract

Summary: We show how expander-based arguments may be used to prove that message-passing algorithms can correct a linear number of erroneous messages. The implication of this result is that when the block length is sufficiently large, once a message-passing algorithm has corrected a sufficiently large fraction of the errors, it will eventually correct all errors. This result is then combined with known results on the ability of message-passing algorithms to reduce the number of errors to an arbitrarily small fraction for relatively high transmission rates. The results hold for various message-passing algorithms, including Gallager's hard-decision and soft-decision (with clipping) decoding algorithms. Our results assume low-density parity-check codes based on an irregular bipartite graph.

Related Organizations
Keywords

Other types of codes, Decoding, Applications of graph theory, message-passing algorithm, low-density parity-check codes, expander graph, belief propagation, iterative decoding

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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!
67
Top 10%
Top 1%
Top 10%
bronze