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• W2007225319 abstract "We present an algorithmic scheme to compute the correlation dimension D 2 of a time series, without requiring the visual inspection of the scaling region in the correlation sum. It is based on the standard Grassberger–Proccacia [GP] algorithm for computing D 2 . The scheme is tested using synthetic data sets from several standard chaotic systems as well as by adding noise to low-dimensional chaotic data. We show that the scheme is efficient with a few thousand data points and is most suitable when a nonsubjective comparison of D 2 values of two time series is required, such as, in hypothesis testing." @default.
• W2007225319 created "2016-06-24" @default.
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• W2007225319 date "2007-01-30" @default.
• W2007225319 modified "2023-09-26" @default.
• W2007225319 title "AN ALGORITHMIC COMPUTATION OF CORRELATION DIMENSION FROM TIME SERIES" @default.
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• W2007225319 doi "https://doi.org/10.1142/s0217984907012517" @default.
• W2007225319 hasPublicationYear "2007" @default.
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