## What is/are Fluctuations Analysis?

Fluctuations Analysis - To sum up, UDGV is an efficient tool to perform noise fluctuations analysis in environmental time series where low concentrations play an important role as well.^{[1]}The geometric classification is based on Continuous Wavelet Transform (CWT), whereas the statistical classification is based on Multifractal Detrended Fluctuations Analysis (MFDFA) and an energy metric.

^{[2]}The paper analyses data derived from three nearby stations via monofractal and multifractal detrended fluctuations analysis and explores whether pre-earthquake fractal and long-memory trends exist in the time series.

^{[3]}The complexity of R-R intervals was assessed by evenly spaced Detrended Fluctuations Analysis and evaluated by the fractal exponent α and deviation from maximal complexity |1-α|.

^{[4]}For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided.

^{[5]}pH fluctuations analysis reveals that 3-CDI can prolong the time required for the electrode to reach the desalination equilibrium and overtly delay the time for the conversion of desalination behavior to faradaic reactions.

^{[6]}Long-range correlations are investigated by means of the scaling of power spectra and of Detrended Fluctuations Analysis.

^{[7]}A saddle point plus fluctuations analysis of the periodically driven half-filled two-dimensional Hubbard model is performed.

^{[8]}According to this intracellular RI dependency, QPI has proven to be successful in performing cell counting, recognition and classification, the monitoring of cellular dry mass, cell membrane fluctuations analysis as well as the reconstruction, through tomographic approaches, of the intracellular 3D refractive index distribution.

^{[9]}We demonstrate an approach for super-resolution imaging by combining fluorophore fluctuations analysis with a confocal detector array setup.

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## Detrended Fluctuations Analysis

The geometric classification is based on Continuous Wavelet Transform (CWT), whereas the statistical classification is based on Multifractal Detrended Fluctuations Analysis (MFDFA) and an energy metric.^{[1]}The paper analyses data derived from three nearby stations via monofractal and multifractal detrended fluctuations analysis and explores whether pre-earthquake fractal and long-memory trends exist in the time series.

^{[2]}The complexity of R-R intervals was assessed by evenly spaced Detrended Fluctuations Analysis and evaluated by the fractal exponent α and deviation from maximal complexity |1-α|.

^{[3]}Long-range correlations are investigated by means of the scaling of power spectra and of Detrended Fluctuations Analysis.

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