Dangers of geometric filtering

A.I. Mees, Kevin Judd

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

We argue that there are unrecognised dangers in the popular and powerful geometric filtering method. Carelessly applied, geometric filtering can produce apparent structure in data which is pure noise, or can cause severe distortions in clean deterministic data. The explanations for these effects are straightforward and the dangers are easily avoided by taking simple precautions in the filtering process.
Original languageEnglish
Pages (from-to)427-436
JournalPhysica D
Volume68
DOIs
Publication statusPublished - 1993

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