Studying long-range correlations in a liquid–vapor-phase transition

Zebende, Gilney Figueira; Silva, M.V.S. da; Rosa, A. C. P.; Alves, Álvaro Santos; Jesus, José Carlos Oliveira de; Moret, Marcelo A.

doi:10.1016/j.physa.2004.01.071

Cited by 36 publications

(9 citation statements)

References 15 publications

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“…There is growing evidence that output signals of many physical [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15], biological [16,17,18,19], physiological [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35] and economic systems [36,37,38,39,40,41,42,43], where multiple component feedback interactions play a central role, exhibit complex self-similar fluctuations over a broad range of space and/or time scales. These fluctuating signals can be characterized by long-range power-law correlations.…”

Section: Introductionmentioning

confidence: 99%

Quantifying signals with power-law correlations: A comparative study of detrended fluctuation analysis and detrended moving average techniques

et al. 2005

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Detrended fluctuation analysis (DFA) and detrended moving average (DMA) are two scaling analysis methods designed to quantify correlations in noisy non-stationary signals. We systematically study the performance of different variants of the DMA method when applied to artificially generated long-range power-law correlated signals with an a-priori known scaling exponent α0 and compare them with the DFA method. We find that the scaling results obtained from different variants of the DMA method strongly depend on the type of the moving average filter. Further, we investigate the optimal scaling regime where the DFA and DMA methods accurately quantify the scaling exponent α0, and how this regime depends on the correlations in the signal. Finally, we develop a three-dimensional representation to determine how the stability of the scaling curves obtained from the DFA and DMA methods depends on the scale of analysis, the order of detrending, and the order of the moving average we use, as well as on the type of correlations in the signal.PACS numbers: 95.75.Wx, 95.75.Pq,

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Section: Introductionmentioning

confidence: 99%

Quantifying signals with power-law correlations: A comparative study of detrended fluctuation analysis and detrended moving average techniques

et al. 2005

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“…In this way, α is the scaling exponent, a self-affinity parameter representing the long-range power-law correlation properties of the signal (fractal properties), such that if α = 0.50 the signal is uncorrelated, if α < 0.50 the correlation in the signal is antipersistent, and if α > 0.50 the correlation in the signal is persistent. Several applications have been made via DFA [15][16][17][18][19][20][21][22][23]. Now we present the detended cross-correlation method (DCCA) [12].…”

Section: Discussionmentioning

confidence: 99%

Cross-correlation between time series of vehicles and passengers

Zebende

Filho

2009

Physica A: Statistical Mechanics and its Applications

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a b s t r a c tWe study in this paper a cross-correlation between time series of vehicles and passengers collected in the ferry-boat system (sea route that connects the city of Salvador and Itaparica island, Bahia, Brazil), this study is based on the detrended cross-correlation analysis (DCCA) method. The DCCA method is designed to investigate power-law cross correlations between different simultaneously recorded time series in the presence of nonstationarity.Here in this paper we show that is possible to discriminate cross-correlation between vehicles and passengers and also identify seasonal components.

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“…The formation and disappearance of the gaseous phase in liquid should be accompanied by the sound generation [25]. The nature of the noise is a fluctuation of pressure connected with oscillations, during which the bubbles appear and move in pores, leaving the catalyst surface if y displace > y cr .…”

Section: Sound Generation In Reactions With Oscillationsmentioning

confidence: 99%

Oscillation theory

Datsevich¹

2005

Applied Catalysis A: General

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Studying long-range correlations in a liquid–vapor-phase transition

Cited by 36 publications

References 15 publications

Quantifying signals with power-law correlations: A comparative study of detrended fluctuation analysis and detrended moving average techniques

Quantifying signals with power-law correlations: A comparative study of detrended fluctuation analysis and detrended moving average techniques

Cross-correlation between time series of vehicles and passengers

Oscillation theory

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