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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 zbMATH Openarrow_drop_down
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Article . 1980
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SIAM Journal on Computing
Article . 1980 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2017
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Combinatorial Gray Codes

Combinatorial Gray codes
Authors: James T. Joichi; Dennis E. White; S. G. Williamson;

Combinatorial Gray Codes

Abstract

We consider families $\{ {\bf C}(n,k):O \leqq k \leqq n\} $ where each ${\bf C}(n,k)$ is a set of combinatorial objects, $C(n,k) = |{\bf C}(n,k)|$ satisfies a recursion $C(n,k)= a_{n,k}C(n - 1,k - 1) + b_{n,k} C(n - 1,k)$, and each object in ${\bf C}(n,k)$ is represented by an n-vector. We study “loop-free” or “uniformly bounded transition” algorithms, i.e., algorithms which yield linear orders on the sets ${\bf C}(n,k)$ so that the vectors representing consecutive objects are “close to each other” (combinatorial Gray codes).Key words. listing algorithms, uniformly bounded operations, uniformly bounded transition algorithms, loop-free algorithms, binary reflected Gray codes, combinatorial Gray codes, binomial grids

Keywords

loop free algorithms, recursion, combinatorial Gray codes, uniformly bounded transition algorithms, linear orders, Enumerative combinatorics, combinatorial objects, 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!
32
Top 10%
Top 10%
Average
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