A novel measure for quantifying the topology preservation of self-organizing feature maps

Mu Chun Su, Hsiao Te Chang, Chien Hsing Chou

研究成果: 雜誌貢獻期刊論文同行評審

18 引文 斯高帕斯(Scopus)

摘要

Recently, feature maps have been applied to various problem domains. The success of some of these applications critically depends on whether feature maps are topologically ordered. In this paper, we propose a novel measure for quantifying the neighborhood preserving property of feature maps. Two data sets were tested to illustrate the performance of the proposed method.

原文???core.languages.en_GB???
頁(從 - 到)137-145
頁數9
期刊Neural Processing Letters
15
發行號2
DOIs
出版狀態已出版 - 4月 2002

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