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Michel Barth

dblp:18/6224 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1988
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes › decoding
decoding algorithms
0.011988
Nearest neighbor algorithm for spherical codes from the Leech lattice · IEEE Trans. Inf. Theory 1988
Coding theory › error-correcting codes › decoding
nearest neighbor decoding
0.011988
Nearest neighbor algorithm for spherical codes from the Leech lattice · IEEE Trans. Inf. Theory 1988
Coding theory › signal sets › signal set design
spherical codes
0.011988
Nearest neighbor algorithm for spherical codes from the Leech lattice · IEEE Trans. Inf. Theory 1988
Coding theory › source coding › quantization
vector quantization
0.011988
Nearest neighbor algorithm for spherical codes from the Leech lattice · IEEE Trans. Inf. Theory 1988

Methods — techniques the papers use, named apart from their topics

nearest neighbor search · 0.0
YearPublicationVenuePosition
1988 Nearest neighbor algorithm for spherical codes from the Leech lattice
abstract
The Leech lattice is a regular arrangement of points in 24-dimensional Euclidean space that yields an extremely dense packing when equal spheres are centered at these points. A subset of the Leech lattice can be used as a signal set for the Gaussian channel or as representative vectors for a vector quantizer. Of particular interest are the spherical codes (or code books) that consist of the points of the Leech lattice which lie on a sphere centered at the origin. The code points do not have to be stored because they can be obtained from a very small set of basic vectors using permutations of the components in a manner dictated by the words of the extended Golay code. A nearest-neighbor algorithm that works on this is developed to determine the point in the code closet to some arbitrary vector in R/sup 24/. The performance of this approach when quantizing independent identically distributed Gaussian samples is reported.>
Jean-Pierre Adoul, Michel Barth
IEEE Trans. Inf. Theory2