Influence of observational noise on the recurrence quantification analysis

Thiel, Marco; Romano, M. Carmen; Kurths, Jürgen; Meucci, R.; Allaria, E.; Arecchi, F. T.

doi:10.1016/s0167-2789(02)00586-9

Cited by 227 publications

(130 citation statements)

References 12 publications

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“…The selection of an appropriate value for the threshold can be made by taking into account the influence of the observational noise that could affect the experimental measures and the minimum distance between the trajectories of the two 4 Complexity systems. In general, choosing equal to few percent of the maximum phase space diameter could ensure a sufficient number of structures in the cross recurrence plot [27], while the appearance of artifacts could be avoided by considering the signal-to-noise ratio for the underlying physical systems [28].…”

Section: Synchronization Indexmentioning

confidence: 99%

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A Novel Synchronization-Based Approach for Functional Connectivity Analysis

et al. 2017

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Complex network analysis has become a gold standard to investigate functional connectivity in the human brain. Popular approaches for quantifying functional coupling between fMRI time series are linear zero-lag correlation methods; however, they might reveal only partial aspects of the functional links between brain areas. In this work, we propose a novel approach for assessing functional coupling between fMRI time series and constructing functional brain networks. A phase space framework is used to map couples of signals exploiting their cross recurrence plots (CRPs) to compare the trajectories of the interacting systems. A synchronization metric is extracted from the CRP to assess the coupling behavior of the time series. Since the functional communities of a healthy population are expected to be highly consistent for the same task, we defined functional networks of taskrelated fMRI data of a cohort of healthy subjects and applied a modularity algorithm in order to determine the community structures of the networks. The within-group similarity of communities is evaluated to verify whether such new metric is robust enough against noise. The synchronization metric is also compared with Pearson's correlation coefficient and the detected communities seem to better reflect the functional brain organization during the specific task.

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Section: Synchronization Indexmentioning

confidence: 99%

“…We obtained m = 5.2 ± 0.75 and = 1.4 ± 0.66, so the embedded parameters were set to = 6 and = 1. Following the criteria reported in [27,28], we identified the range [1.2-1.8] for the threshold . The analysis was carried out with the average value of the range, setting = 1.5.…”

Section: Crp Parametersmentioning

confidence: 99%

A Novel Synchronization-Based Approach for Functional Connectivity Analysis

et al. 2017

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“…The threshold value has been selected in such a way that the point density was approximately 1%. 36 The changes in the character of the time series are clearly reflecting different regimes of dynamics of the plasma oscillations. (Fig.…”

Section: Rqa Of Plasma Oscillationsmentioning

confidence: 99%

Investigation of complexity dynamics in a DC glow discharge magnetized plasma using recurrence quantification analysis

Mitra

Sarma

et al. 2016

Physics of Plasmas

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Recurrence is an ubiquitous feature which provides deep insights into the dynamics of real dynamical systems. A suitable tool for investigating recurrences is recurrence quantification analysis (RQA). It allows, e.g., the detection of regime transitions with respect to varying control parameters. We investigate the complexity of different coexisting nonlinear dynamical regimes of the plasma floating potential fluctuations at different magnetic fields and discharge voltages by using recurrence quantification variables, in particular, DET, Lmax, and Entropy. The recurrence analysis reveals that the predictability of the system strongly depends on discharge voltage. Furthermore, the persistent behaviour of the plasma time series is characterized by the Detrended fluctuation analysis technique to explore the complexity in terms of long range correlation. The enhancement of the discharge voltage at constant magnetic field increases the nonlinear correlations; hence, the complexity of the system decreases, which corroborates the RQA analysis.

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“…Several "rules of thumb" for the choice of the threshold ε are present in the literature between them (Marwan et al, 2007): a/ it should not exceed 10% of the mean or the maximum phase space diameter (Koebbe and Mayer-Kress, 1992;Zbilut and Webber, 1992) b/ it should be such that the recurrence point density in RP is approximately 1% c/ in order to avoid problem related to noise, ε has to be chosen such that it is five time larger than the standard deviation of the observational noise, i.e. ε>5σ (Thiel et al, 2002) Nevertheless, the choice of e depends strongly on the considered system under study.…”

Section: Selection Of the Threshold Or Cutoff Value εmentioning

confidence: 99%