DocumentCode
934573
Title
Voronoi regions of lattices, second moments of polytopes, and quantization
Author
Conway, J.H. ; Sloane, N. J A
Volume
28
Issue
2
fYear
1982
fDate
3/1/1982 12:00:00 AM
Firstpage
211
Lastpage
226
Abstract
If a point is picked at random inside a regular simplex, octahedron,
-cell, or other polytope, what is its average squared distance from the centroid? In
-dimensional space, what is the average squared distance of a random point from the closest point of the lattice
(or
The answers are given here, together with a description of the Voronoi (or nearest neighbor) regions of these lattices. The results have applications to quantization and to the design of signals for the Gaussian channel. For example, a quantizer based on the eight-dimensional lattice E8 has a mean-squared error per symbol of
when applied to uniformly distributed data, compared with
for the best one-dimensional quantizer.
-cell, or other polytope, what is its average squared distance from the centroid? In
-dimensional space, what is the average squared distance of a random point from the closest point of the lattice
(or
The answers are given here, together with a description of the Voronoi (or nearest neighbor) regions of these lattices. The results have applications to quantization and to the design of signals for the Gaussian channel. For example, a quantizer based on the eight-dimensional lattice E8 has a mean-squared error per symbol of
when applied to uniformly distributed data, compared with
for the best one-dimensional quantizer.Keywords
Quantization (signal); Signal quantization; Gaussian channels; Helium; Lattices; Mathematics; Milling machines; Nearest neighbor searches; Probability density function; Quantization; Signal design; Statistics;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1982.1056483
Filename
1056483
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