scholarly journals Investigating the spatial variability of the time-scaling properties in Italian seismicity

2004 ◽  
Vol 11 (5/6) ◽  
pp. 545-552 ◽  
Author(s):  
L. Telesca ◽  
V. Lapenna
Keyword(s):  
Seismic Data ◽  
Detrended Fluctuation Analysis ◽  
Time Correlation ◽  
Fluctuation Analysis ◽  
Feedback Mechanisms ◽  
Scaling Properties ◽  
Time Scaling ◽  
Allan Factor ◽  
Detrended Fluctuation ◽  
Apennine Chain

Abstract. Significant power-law long-range correlated structures have been identified in the Italian seismicity from 1983 to 2003. We performed the Allan Factor Analysis and the Detrended Fluctuation Analysis on both the full and the aftershock-depleted seismic data, extracted by the INGV (National Institute of Geophysics and Volcanology) instrumental catalog.Our findings suggest that (i) the time-scaling behaviour characterizes mainly the Apennine chain; (ii) the time-correlated behaviour of the seismicity is persistent, and this implies that the dynamics underlying the seismic phenomenology is characterized by the presence of "positive feedback mechanisms"; (iii) significant time correlation is not simply related with the mainshock/aftershock mechanisms.

scholarly journals Time-Scaling Properties of Sunshine Duration Based on Detrended Fluctuation Analysis over China

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 83 ◽  
Author(s):  
Lei Jiang ◽  
Jiping Zhang ◽  
Yan Fang
Keyword(s):  
Time Series ◽  
Detrended Fluctuation Analysis ◽  
Sunshine Duration ◽  
Underlying Surface ◽  
Fluctuation Analysis ◽  
Scaling Properties ◽  
Long Range Correlations ◽  
Time Scaling ◽  
Daily Sunshine ◽  
Detrended Fluctuation

The spatial and temporal variabilities of the daily Sunshine Duration (SSD) time series from the Chinese Meteorological Administration during the 1954–2009 period are examined by the Detrended Fluctuation Analysis (DFA) method. As a whole, weak long-range correlations (LRCs) are found in the daily SSD anomaly records over China. LRCs are also verified by shuffling the SSD records. The proportion of the stations with LRCs accounts for about 97% of the total. Many factors affect the scaling properties of the daily SSD records such as sea-land difference and Tibetan Plateau landform and so on. We find land use and land cover as one of the important factors closely links to LRCs of the SSD. Strong LRCs of the SSD mainly happen in underlying surface of deserts and crops, while weak LRCs occur in forest and grassland. Further studies of scaling behaviors are still necessary to be performed due to the complex underlying surface and climate system.

scholarly journals Investigating the time-scaling behavior of the 2004–2010 seismicity of Aswan area (Egypt) by means of the Allan factor statistics and the detrended fluctuation analysis

2012 ◽  
Vol 12 (5) ◽  
pp. 1267-1276 ◽  
Author(s):  
L. Telesca ◽  
M. Lovallo ◽  
A. E.-E. Amin Mohamed ◽  
M. ElGabry ◽  
S. El-hady ◽  
...  
Keyword(s):  
Time Series ◽  
Detrended Fluctuation Analysis ◽  
Point Processes ◽  
Nonstationary Time Series ◽  
Fluctuation Analysis ◽  
Scaling Exponents ◽  
Time Dynamics ◽  
Time Scaling ◽  
Allan Factor ◽  
Detrended Fluctuation

Abstract. The time dynamics of seismicity of Aswan area (Egypt) from 2004 to 2010 was investigated by means of the (i) Allan Factor, which is a powerful tool allowing the capture of time-clusterized properties of temporal point processes; and the (ii) detrended fluctuation analysis, which is capable of detecting scaling in nonstationary time series. The analysis was performed varying the depth and the magnitude thresholds. The 2004–2010 Aswan seismicity is characterized by significant three-fold time-clustering behaviors with scaling exponents ~0.77 for timescales between 104.16 s and 105.14 s, ~0.34 for timescales between 105.14 s and 106.53 s, and ~1 for higher timescales. The seismic interevent times and distances are characterized by persistent temporal fluctuations for most of the magnitude and depth thresholds.

Scaling behavior of earthquakes’ inter-events time series

Open Physics ◽  
2009 ◽  
Vol 7 (3) ◽  
Author(s):  
Shahriar Shadkhoo ◽  
Fakhteh Ghanbarnejad ◽  
Gholam Jafari ◽  
Mohammad Tabar
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Hurst Exponent ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Data Set ◽  
Scaling Properties ◽  
Independent Events ◽  
Detrended Fluctuation

AbstractIn this paper, we investigate the statistical and scaling properties of the California earthquakes’ inter-events over a period of the recent 40 years. To detect long-term correlations behavior, we apply detrended fluctuation analysis (DFA), which can systematically detect and overcome nonstationarities in the data set at all time scales. We calculate for various earthquakes with magnitudes larger than a given M. The results indicate that the Hurst exponent decreases with increasing M; characterized by a Hurst exponent, which is given by, H = 0:34 + 1:53/M, indicating that for events with very large magnitudes M, the Hurst exponent decreases to 0:50, which is for independent events.

scholarly journals Effect of Trends on Detrended Fluctuation Analysis of Precipitation Series

2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Jianhai Yue ◽  
Xiaojun Zhao ◽  
Pengjian Shang
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Precipitation Series ◽  
Scaling Exponents ◽  
Scaling Properties ◽  
Original Series ◽  
Range Correlation ◽  
Before And After ◽  
Periodic Trend ◽  
Detrended Fluctuation

We use detrended fluctuation analysis (DFA) method to detect the long-range correlation and scaling properties of daily precipitation series of Beijing from 1973 to 2004 before and after adding diverse trends to the original series. The correlation and scaling properties of the original series are difficult to analyze due to existing crossovers. The effects of the coefficient and the power of the added trends on the scaling exponents and crossovers of the series are tested. A crossover is found to be independent of the added trends, which arises from the intrinsic periodic trend of the precipitation series. However, another crossover caused by the multifractal vanishes with the increasing power of added trends.

Local multifractal detrended fluctuation analysis for tea breeds identification

2014 ◽  
Vol 07 (05) ◽  
pp. 1450048 ◽  
Author(s):  
Fang Wang ◽  
Rui-Biao Zou ◽  
Gui-Ping Liao ◽  
Jin-Wei Li ◽  
Zi-Qiang Liu
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Estimation Method ◽  
Fluctuation Analysis ◽  
Characteristic Parameters ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Scaling Properties ◽  
Local Scaling ◽  
Comparison Results ◽  
Capacity Measure ◽  
Detrended Fluctuation

In recent years, the popular multifractal detrended fluctuation analysis (MF-DFA) is extended to two-dimensional (2D) version, which has been applied in some field of image processing. In this paper, based on the 2D MF-DFA, a novel multifractal estimation method for images, which we called the local multifractal detrended fluctuation analysis (LMF-DFA), is proposed to recognize and distinguish 20 types of tea breeds. A set of new multifractal descriptors, namely the local multifractal fluctuation exponents is defined to portray the local scaling properties of a surface. After collecting 10 tea leaves for each breed and photographing them to standard images, the LMF-DFA method is used to extract characteristic parameters for the images. Our analysis finds that there are significant differences among the different tea breeds' characteristic parameters by analysis of variance. Both the proposed LMF-DFA exponents and another classic parameter, namely the exponent based on capacity measure method have been used as features to distinguish the 20 tea breeds. The comparison results illustrate that the LMF-DFA estimation can differentiate the tea breeds more effectively and provide more satisfactory accuracy.

Two-dimensional DFA scaling analysis applied to encrypted images

2015 ◽  
Vol 26 (08) ◽  
pp. 1550093 ◽  
Author(s):  
C. Vargas-Olmos ◽  
J. S. Murguía ◽  
M. T. Ramírez-Torres ◽  
M. Mejía Carlos ◽  
H. C. Rosu ◽  
...  
Keyword(s):  
Cellular Automaton ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Scaling Analysis ◽  
Scaling Exponent ◽  
Two Dimensional ◽  
Scaling Properties ◽  
Encrypted Images ◽  
Detrended Fluctuation

The technique of detrended fluctuation analysis (DFA) has been widely used to unveil scaling properties of many different signals. In this paper, we determine scaling properties in the encrypted images by means of a two-dimensional DFA approach. To carry out the image encryption, we use an enhanced cryptosystem based on a rule-90 cellular automaton and we compare the results obtained with its unmodified version and the encryption system AES. The numerical results show that the encrypted images present a persistent behavior which is close to that of the 1/f-noise. These results point to the possibility that the DFA scaling exponent can be used to measure the quality of the encrypted image content.

Multifractal detrended fluctuation analysis of pseudorapidity and azimuthal distribution of pions emitted in high energy nuclear collisions

2014 ◽  
Vol 29 (18) ◽  
pp. 1450084 ◽  
Author(s):  
Srimonti Dutta ◽  
Dipak Ghosh ◽  
Sucharita Chatterjee
Keyword(s):  
Detrended Fluctuation Analysis ◽  
High Energy ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Scaling Properties ◽  
Nuclear Collisions ◽  
200 Gev ◽  
Fluctuation Pattern ◽  
Multifractal Scaling ◽  
Detrended Fluctuation

In this paper multifractal analysis of fluctuation pattern of pions emitted in 32 S-AgBr and 16 O-AgBr interactions at 200 GeV and 60 GeV, respectively, is performed in the framework of multifractal detrended fluctuation analysis (MFDFA). The pseudorapidity and azimuthal distributions exhibit multifractal scaling properties at both energies. The variation of multifractal width with energy is also studied. The study reveals a dependence of multifractal width on energy in pseudorapidity space while no such dependence is observed in azimuthal space.

Sign in / Sign up

Export Citation Format

Share Document