scholarly journals Long-Range Correlations and Natural Time Series Analyses from Acoustic Emission Signals

2021 ◽  
Author(s):  
Leandro Ferreira Friedrich ◽  
Édiblu Silva Cezar ◽  
Angélica Bordin Colpo ◽  
Boris Nahuel Rojo Tanzi ◽  
Mario Sobczyk ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Long Range ◽  
Fluctuation Analysis ◽  
Long Range Correlations ◽  
Glass Fiber Reinforced ◽  
Bridge Model ◽  
Natural Time ◽  
Ae Signal ◽  
Time Series Analyses ◽  
Polymeric Plate

This work focuses on analyzing acoustic emission (AE) signals as a means to predict failure in structures. Two main approaches are considered: (i) long-range correlation analysis using both the Hurst (H) and the Detrended Fluctuation Analysis (DFA) exponents, and (ii) natural time domain (NT) analysis. These methodologies are applied to the data collected from two application examples: a glass fiber reinforced polymeric plate and a spaghetti bridge model, where both structures were subjected to increasing loads until collapse. A traditional (AE) signal analysis is also performed to reference the study of the other methods. Results indicate that the proposed methods yield a reliable indication of failure in the studied structures.

scholarly journals Long-Range Correlations and Characterization of Financial and Volcanic Time Series

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 441 ◽  
Author(s):  
Maria C. Mariani ◽  
Peter K. Asante ◽  
Md Al Masum Bhuiyan ◽  
Maria P. Beccar-Varela ◽  
Sebastian Jaroszewicz ◽  
...  
Keyword(s):  
Time Series ◽  
Long Range ◽  
Time Series Data ◽  
Financial Time Series ◽  
Seismic Station ◽  
Volcanic Eruptions ◽  
Series Data ◽  
Fluctuation Analysis ◽  
Scaling Properties ◽  
Long Range Correlations

In this study, we use the Diffusion Entropy Analysis (DEA) to analyze and detect the scaling properties of time series from both emerging and well established markets as well as volcanic eruptions recorded by a seismic station, both financial and volcanic time series data have high frequencies. The objective is to determine whether they follow a Gaussian or Lévy distribution, as well as establish the existence of long-range correlations in these time series. The results obtained from the DEA technique are compared with the Hurst R/S analysis and Detrended Fluctuation Analysis (DFA) methodologies. We conclude that these methodologies are effective in classifying the high frequency financial indices and volcanic eruption data—the financial time series can be characterized by a Lévy walk while the volcanic time series is characterized by a Lévy flight.

scholarly journals Scaling behaviour of the global tropopause

2009 ◽  
Vol 9 (2) ◽  
pp. 677-683 ◽  
Author(s):  
C. Varotsos ◽  
M. Efstathiou ◽  
C. Tzanis
Keyword(s):  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Sea Surface ◽  
Fluctuation Analysis ◽  
Tropopause Height ◽  
Time Intervals ◽  
Long Range Correlations ◽  
Scaling Behaviour ◽  
Detrended Fluctuation ◽  
Global Mean

Abstract. Detrended fluctuation analysis is applied to the time series of the global tropopause height derived from the 1980–2004 daily radiosonde data, in order to detect long-range correlations in its time evolution. Global tropopause height fluctuations in small time-intervals are found to be positively correlated to those in larger time intervals in a power-law fashion. The exponent of this dependence is larger in the tropics than in the middle and high latitudes in both hemispheres. Greater persistence is observed in the tropopause of the Northern than in the Southern Hemisphere. A plausible physical explanation of the fact that long-range correlations in tropopause variability decreases with increasing latitude is that the column ozone fluctuations (that are closely related with the tropopause ones) exhibit long range correlations, which are larger in tropics than in the middle and high latitudes at long time scales. This finding for the tropopause height variability should reduce the existing uncertainties in assessing the climatic characteristics. More specifically the reliably modelled values of a climatic variable (i.e. past and future simulations) must exhibit the same scaling behaviour with that possibly existing in the real observations of the variable under consideration. An effort has been made to this end by applying the detrended fluctuation analysis to the global mean monthly land and sea surface temperature anomalies during the period January 1850–August 2008. The result obtained supports the findings presented above, notably: the correlations between the fluctuations in the global mean monthly land and sea surface temperature display scaling behaviour which must characterizes any projection.

Complexity, Coordination, and Health: Avoiding Pitfalls and Erroneous Interpretations in Fractal Analyses

Medicina ◽  
2011 ◽  
Vol 47 (7) ◽  
pp. 393 ◽  
Author(s):  
Vivien Marmelat ◽  
Didier Delignières
Keyword(s):  
Long Range ◽  
Fluctuation Analysis ◽  
Short Term ◽  
Long Range Correlations ◽  
Optimal Functioning ◽  
Fractal Analyses ◽  
Serial Correlations ◽  
Walking Velocity ◽  
Fractal Fluctuation ◽  
Detrended Fluctuation

Background and Objective. The analysis of fractal fluctuation has become very popular because of the close relationships between health, adaptability, and long-range correlations. 1/f noise is considered a “magical” threshold, characterizing optimal functioning, and a decrease or conversely and increase of serial correlations, with respect to 1/f noise, is supposed to sign a kind of disadaptation of the system. Empirical results, however, should be interpreted with caution. In experimental series, serial correlations often present a complex pattern, resulting from the combination of long-range and short-term correlated processes. We show, in the present paper, that an increase in serial correlations cannot be directly interpreted as an increase in long-range correlations. Material and Methods. Eleven participants performed four walking bouts following 4 individually determined velocities (slow, comfortable, high, and critical). Series of 512 stride intervals were collected under each condition. The strength of serial correlation was measured by the detrended fluctuation analysis. The effective presence of 1/f fluctuation was tested through ARFIMA modeling. Results. The strength of serial correlations tended to increase with walking velocity. However, the ARFIMA modeling showed that long-range correlations were significantly present only at slow and comfortable velocities. Conclusions. The strength of correlations, as measured by classical methods, cannot be considered as predictive of the genuine presence of long-range correlations. Sometimes systems can present the moderate levels of effective long-range correlations, whereas in others cases, series can present high correlation levels without being long-range correlated.

scholarly journals DETRENDED FLUCTUATION ANALYSIS OF AUTOREGRESSIVE PROCESSES

2007 ◽  
Vol 07 (03) ◽  
pp. L249-L255 ◽  
Author(s):  
VASILE V. MORARIU ◽  
LUIZA BUIMAGA-IARINCA ◽  
CĂLIN VAMOŞ ◽  
ŞTEFAN M. ŞOLTUZ
Keyword(s):  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Short Range ◽  
Interaction Constant ◽  
Fluctuation Analysis ◽  
Autoregressive Processes ◽  
Long Range Correlations ◽  
Correlation Exponent ◽  
The Relationship ◽  
Detrended Fluctuation

Autoregressive processes (AR) have typical short-range memory. Detrended Fluctuation Analysis (DFA) was basically designed to reveal long-range correlations in non stationary processes. However DFA can also be regarded as a suitable method to investigate both long-range and short-range correlations in non stationary and stationary systems. Applying DFA to AR processes can help understanding the non-uniform correlation structure of such processes. We systematically investigated a first order autoregressive model AR(1) by DFA and established the relationship between the interaction constant of AR(1) and the DFA correlation exponent. The higher the interaction constant the higher is the short-range correlation exponent. They are exponentially related. The investigation was extended to AR(2) processes. The presence of an interaction between distant terms with characteristic time constant in the series, in addition to a near by interaction will increase the correlation exponent and the range of correlation while the effect of a distant negative interaction will significantly decrease the range of interaction, only. This analysis demonstrate the possibility to identify an AR(1) model in an unknown DFA plot or to distinguish between AR(1) and AR(2) models.

scholarly journals Tempting long-memory - on the interpretation of DFA results

2004 ◽  
Vol 11 (4) ◽  
pp. 495-503 ◽  
Author(s):  
D. Maraun ◽  
H. W. Rust ◽  
J. Timmer
Keyword(s):  
Long Range ◽  
Long Memory ◽  
A Priori ◽  
Confidence Regions ◽  
Fluctuation Analysis ◽  
Data Set ◽  
Fluctuation Function ◽  
Long Range Correlations ◽  
Straight Line ◽  
Scaling Region

Abstract. We study the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) and argue that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires the investigation of the local slopes. We account for the variability characteristic for stochastic processes by calculating empirical confidence regions. Comparing a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. We remark that scaling cannot be concluded from a straight line fit to the fluctuation function in a log-log representation. Furthermore, we show that a local slope larger than α=0.5 for large scales does not necessarily imply long-memory. We also demonstrate, that it is not valid to conclude from a finite scaling region of the fluctuation function to an equivalent scaling region of the autocorrelation function. Finally, we review DFA results for the Prague temperature data set and show that long-range correlations cannot not be concluded unambiguously.

scholarly journals IMPACT OF TANDEM REPEATS ON THE SCALING OF NUCLEOTIDE SEQUENCES

2006 ◽  
Vol 16 (10) ◽  
pp. 3103-3108
Author(s):  
RADHAKRISHNAN NAGARAJAN ◽  
MEENAKSHI UPRETI
Keyword(s):  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Tandem Repeats ◽  
Nucleotide Sequences ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Long Range Correlations ◽  
Reliable Estimation ◽  
Detrended Fluctuation

Techniques such as detrended fluctuation analysis (DFA) and its extensions have been widely used to determine the nature of scaling in nucleotide sequences. In this brief communication we show that tandem repeats which are ubiquitous in nucleotide sequences can prevent reliable estimation of possible long-range correlations. Therefore, it is important to investigate the presence of tandem repeats prior to scaling exponent estimation.

scholarly journals Differences in Gating Dynamics of BK Channels in Cellular and Mitochondrial Membranes from Human Glioblastoma Cells Unraveled by Short- and Long-Range Correlations Analysis

Cells ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 2305 ◽  
Author(s):  
Agata Wawrzkiewicz-Jałowiecka ◽  
Paulina Trybek ◽  
Przemysław Borys ◽  
Beata Dworakowska ◽  
Łukasz Machura ◽  
...  
Keyword(s):  
Long Range ◽  
Single Channel ◽  
Cellular Membrane ◽  
Bk Channels ◽  
Bk Channel ◽  
Fluctuation Analysis ◽  
Channel Activity ◽  
Human Glioblastoma ◽  
Long Range Correlations ◽  
Single Channel Activity

The large-conductance voltage- and Ca2+-activated K+ channels (BK) are encoded in humans by the Kcnma1 gene. Nevertheless, BK channel isoforms in different locations can exhibit functional heterogeneity mainly due to the alternative splicing during the Kcnma1 gene transcription. Here, we would like to examine the existence of dynamic diversity of BK channels from the inner mitochondrial and cellular membrane from human glioblastoma (U-87 MG). Not only the standard characteristics of the spontaneous switching between the functional states of the channel is discussed, but we put a special emphasis on the presence and strength of correlations within the signal describing the single-channel activity. The considered short- and long-range memory effects are here analyzed as they can be interpreted in terms of the complexity of the switching mechanism between stable conformational states of the channel. We calculate the dependencies of mean dwell-times of (conducting/non-conducting) states on the duration of the previous state, Hurst exponents by the rescaled range R/S method and detrended fluctuation analysis (DFA), and use the multifractal extension of the DFA (MFDFA) for the series describing single-channel activity. The obtained results unraveled statistically significant diversity in gating machinery between the mitochondrial and cellular BK channels.

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