Quantitative assessment of the log-log-step method for pattern detection in noise-prone environments.
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Gomez F
Institute of Neuroinformatics, ETH Zurich and University of Zurich, Zurich, Switzerland.
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Stoop R
English
Staircase-like structures in the log-log correlation plot of a time series indicate patterns against a noisy background, even under condition of strong jitter. We analyze the method for different jitter-noise-combinations, using quantitative criteria to measure the achievement by the method. A phase diagram shows the remarkable potential of this method even under very unfavorable conditions of noise and jitter. Moreover, we provide a novel and compact analytical derivation of the upper and lower bounds on the number of steps observable in the ideal noiseless case, as a function of pattern length and embedding dimension. The quantitative measure developed combined with the ideal bounds can serve as guiding lines for determining potential periodicity in noisy data.
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Language
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Open access status
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gold
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Persistent URL
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https://sonar.ch/global/documents/143334
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