Algorithm for data clustering in pattern recognition problems based on quantum mechanics

David Horn, Assaf Gottlieb

Research output: Contribution to journalArticlepeer-review

Abstract

A clustering method based on quantum mechanics was proposed to analyze data clustering in pattern recognition problems. Quantum clustering (QC) was used to construct potential function for global spherical symmetry on the basis of data points controlling width of structures. The proposed algorithm consisted of single parameter to determine the scale over which the structures were searched. Analysis suggested that the method could be efficiently applied in higher dimensions by limiting the evaluation of Schrodinger potential to location of data points.

Original languageEnglish
Pages (from-to)187021-187024
Number of pages4
JournalPhysical Review Letters
Volume88
Issue number1
StatePublished - 7 Jan 2002

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