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IEEE Transactions on Information Theory
Article . 1997 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Binary codes derived from the Hoffman-Singleton and Higman-Sims graphs

Authors: Tonchev, Vladimir D.;

Binary codes derived from the Hoffman-Singleton and Higman-Sims graphs

Abstract

The author gives some binary linear codes of length 50 and 100 using the adjacency matrices of the Hoffman-Singleton graph and the Higman-Sims graph. Some of these codes are optimal or nearly optimal for the given length and dimension. The author also gives the weight distribution of the codes and observes that the dual codes admit majority logic decoding.

Related Organizations
Keywords

majority decoding, optimal linear code, Graphs and linear algebra (matrices, eigenvalues, etc.), automorphism group of a graph, strongly regular graph, weight distribution, Linear codes (general theory)

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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!
12
Top 10%
Top 10%
Average
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