Reconstruction of driving forces through recurrence plots

Tanio, Masaaki; Hirata, Yoshito; Suzuki, Hideyuki

doi:10.1016/j.physleta.2009.03.069

Cited by 26 publications

(16 citation statements)

References 16 publications

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“…3, 4, 6, and 8 to recurrence plots [49,50], making them continuous by the method of Ref. [51], and convert back to evenly sampled time series by the method of Refs. [52,53], the reconstructed time series look similar to the original time series (Figs.…”

Section: Discussionmentioning

confidence: 99%

“…The comparison between the subsampled dataset (the solid line) of the Lorenz model and its reconstruction (the dash dotted line) from the local maxima series of the upper lobe of . Here, the reconstruction shown is the fourth principal component obtained after obtaining a recurrence plot, making the plot continuous by the method ofRef [51],. and reproducing the time series by the method of Refs [52,53]…”

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confidence: 99%

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Possibility of short-term probabilistic forecasts for large earthquakes making good use of the limitations of existing catalogs

2016

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Earthquakes are quite hard to predict. One of the possible reasons can be the fact that the existing catalogs of past earthquakes are limited at most to the order of 100 years, while their characteristic time scale is sometimes greater than that time span. Here we rather use these limitations positively and characterize some large earthquake events as abnormal events that are not included there. When we constructed probabilistic forecasts for large earthquakes in Japan based on similarity and difference to their past patterns-which we call known and unknown abnormalities, respectively-our forecast achieved probabilistic gains of 5.7 and 2.4 against a time-independent model for main shocks with the magnitudes of 7 or above. Moreover, the two abnormal conditions covered 70% of days whose maximum magnitude was 7 or above.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Possibility of short-term probabilistic forecasts for large earthquakes making good use of the limitations of existing catalogs

2016

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“…Third, we took the union for the recurrence plots to infer the recurrence plot of the common driving force 77 . Fourth, we applied the assumption of continuity and supplied the points at (i,i+1) and (i+1,i) for each i 78 . Fifth, we applied the method described in 77 to convert the recurrence plot of the common driving force into time series.…”

Section: Reconstruction Of Driving Forces By Recurrence Plotsmentioning

confidence: 99%

A mobile ELF4 delivers circadian temperature information from shoots to roots

Chen

Takahashi

Hirata

et al. 2019

Preprint

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AbstractThe circadian clock is synchronized by environmental cues, mostly by light and temperature. Elucidating how the plant circadian clock responds to temperature oscillations is crucial to understand plant responsiveness to the environment. Here we found a prevalent temperature-dependent function of the Arabidopsis clock component ELF4 (EARLY FLOWERING 4) in the root clock. Micrografting assays and mathematical analyses show that ELF4 moves from shoots to regulate rhythms in roots. ELF4 movement does not convey photoperiodic information but trafficking is essential to control the period of the root clock in a temperature-dependent manner. At low temperatures, ELF4 mobility is favored and results in a slow-paced root clock while high temperatures decrease movement, leading to a fast clock. Hence, the mobile ELF4 delivers temperature information and establishes a shoot-to-root dialogue that sets the pace of the clock in roots.

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“…Groth [128] showed that a combination of cross-recurrence plots and order recurrence plots can lead to a robust estimator of coupling between two systems. Tanio, Hirata and Suzuki [129] used recurrence plots and combinatorial optimization to reconstruct a slowly varying driving force by observing only the driven system. Hirata and Aihara [130] presented an approach to detect common driving forces from bivariate time series measurements by using counts of joint recurrence of the two systems that were in excess of what was expected from their individual recurrence rates.…”

Section: Inferring Dependencies Using Recurrencesmentioning

confidence: 99%

A Brief Introduction to Nonlinear Time Series Analysis and Recurrence Plots

Goswami

2019

Vibration

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Nonlinear time series analysis gained prominence from the late 1980s on, primarily because of its ability to characterize, analyze, and predict nontrivial features in data sets that stem from a wide range of fields such as finance, music, human physiology, cognitive science, astrophysics, climate, and engineering. More recently, recurrence plots, initially proposed as a visual tool for the analysis of complex systems, have proven to be a powerful framework to quantify and reveal nontrivial dynamical features in time series data. This tutorial review provides a brief introduction to the fundamentals of nonlinear time series analysis, before discussing in greater detail a few (out of the many existing) approaches of recurrence plot-based analysis of time series. In particular, it focusses on recurrence plot-based measures which characterize dynamical features such as determinism, synchronization, and regime changes. The concept of surrogate-based hypothesis testing, which is crucial to drawing any inference from data analyses, is also discussed. Finally, the presented recurrence plot approaches are applied to two climatic indices related to the equatorial and North Pacific regions, and their dynamical behavior and their interrelations are investigated.

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Reconstruction of driving forces through recurrence plots

Cited by 26 publications

References 16 publications

Possibility of short-term probabilistic forecasts for large earthquakes making good use of the limitations of existing catalogs

Possibility of short-term probabilistic forecasts for large earthquakes making good use of the limitations of existing catalogs

A mobile ELF4 delivers circadian temperature information from shoots to roots

A Brief Introduction to Nonlinear Time Series Analysis and Recurrence Plots

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