Computing Euclidean bottleneck matchings in higher dimensions

Alon Efrat, Matthew J. Katz

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

We extend the planar results of Chang et al. (1992) to higher dimensions, and show that given a set A of 2n points in d-space it is possible to compute a Euclidean bottleneck matching of A in roughly O(n1.5) time, for d≤6, and in subquadratic time, for any constant d>6. If the underlying norm is L, then it is possible to compute a bottleneck matching of A in O(n1.5 log0.5 n) time, for any constant d≥2.

Original languageEnglish (US)
Pages (from-to)169-174
Number of pages6
JournalInformation Processing Letters
Volume75
Issue number4
DOIs
StatePublished - Sep 30 2000
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Signal Processing
  • Information Systems
  • Computer Science Applications

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