Presentation 1996/1/25
On dimension estimates with surrogate data sets
Tohru Ikeguchi, Kazuyuki Aihara,
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Abstract(in English) In this paper, we propose a new strategy of estimating correlation dimensions in combination with the method of surrogate data, which is a kind of statistical control usually introduced to avoid spurious estimates of nonlinear statistics. In case of analyzing time series with the method of surrogate data, it is desirable to decide a value of estimated nonlinear statistics of the original data and surrogate data sets exactly. However, when dimensional analysis is applied to possible attractors reconstructed from real time series, it is very dangerous to decide a single value as an estimated dimension, because dimension is an index of self-similarity and therefore analyzed with its scaling property. In order to solve this difficulty, a dimension estimator algorithm and the method of surrogate data are combined by introducing Monte Carlo significance testing. As a result, an analysis of scaling properties at various resolution levels based on the method of surrogate data is realized.
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Keyword(in English) chaos / correlation dimension / surrogate data / hypothesis testing / Fourier transform / time series analysis
Paper # CAS95-97,NLP95-88
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Committee CAS
Conference Date 1996/1/25(1days)
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Registration To Circuits and Systems (CAS)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) On dimension estimates with surrogate data sets
Sub Title (in English)
Keyword(1) chaos
Keyword(2) correlation dimension
Keyword(3) surrogate data
Keyword(4) hypothesis testing
Keyword(5) Fourier transform
Keyword(6) time series analysis
1st Author's Name Tohru Ikeguchi
1st Author's Affiliation Department of Applied Electronics, Science University of Tokyo()
2nd Author's Name Kazuyuki Aihara
2nd Author's Affiliation Department of Mathematical Engineering and Information Physics, University of Tokyo
Date 1996/1/25
Paper # CAS95-97,NLP95-88
Volume (vol) vol.95
Number (no) 482
Page pp.pp.-
#Pages 8
Date of Issue