1998
DOI: 10.1016/s0375-9601(97)00843-8
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Recurrence quantification analysis and principal components in the detection of short complex signals

Abstract: Recurrence plots were introduced to help aid the detection of signals in complicated data series. This effort was furthered by the quantification of recurrence plot elements. We now demonstrate the utility of combining recurrence quantification analysis with principal components analysis to allow for a probabilistic evaluation for the presence of deterministic signals in relatively short data lengths. PACS: 05.40 05.45, 07.05Rm, 07.05Kf

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Cited by 141 publications
(93 citation statements)
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“…In order to obtain r for the different n values, a log-log plot is in order. The choice of τ is debatable [79]. In the following we have chosen τ = 500 like in other related studies [20], for n = 1 to 15.…”
Section: Grassberger-procacia Methodsmentioning
confidence: 99%
“…In order to obtain r for the different n values, a log-log plot is in order. The choice of τ is debatable [79]. In the following we have chosen τ = 500 like in other related studies [20], for n = 1 to 15.…”
Section: Grassberger-procacia Methodsmentioning
confidence: 99%
“…Hence, in a second step we will employ principal component analysis (PCA) to reduce the dimensionality of the CRQA measures, which has been suggested as a viable solution to reduce data complexity when using conceptually related and highly correlated CRQA measures [48,49]. Also, the questionnaire data collected consisted of multiple questions related to subjective aspects of social relations among team members and perceived team performance, and will be reduced to a more manageable set of variables via PCA as well.…”
Section: Data Analysis Strategymentioning
confidence: 99%
“…They used a graphical nonlinear method (Zbilut et al 1998;Marwan et al 2002): a recurrence plot to determine specific nonlinear indices. This method looks for recurrent values in a time series.…”
Section: Initial Rat Experiments: Graphical Methodsmentioning
confidence: 99%