Change in the embedding dimension as an indicator of an approaching transition

Yair Neuman, Norbert Marwan, Yohai Cohen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.

Original languageEnglish
Article numbere101014
JournalPLoS ONE
Volume9
Issue number6
DOIs
StatePublished - 30 Jun 2014

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