Investigating the time-correlation properties in self-potential signals recorded in a seismic area of Irpinia, southern Italy

Luciano Telesca, Marianna Balasco and Vincenzo Lapenna

Chaos, Solitons & Fractals, 2007, vol. 32, issue 1, 199-211

Abstract: Recent studies have shown that many natural phenomena are characterized by temporal fluctuations with long-range power-law correlations, suggesting a fractal geometry of the underlying dynamical system. The presence of power-law correlations are detected in four time series of self-potential signals, measured in a seismic area of southern Italy, by means of the Detrended Fluctuation Analysis (DFA), a method that permits the detection of long-range correlations in nonstationary time series. Results show scaling behaviour for all the signals recorded, indicating the presence of fractal features expressing a long-term correlation quantified by the numerical value of the scaling exponents. Our findings suggest a possible correlation between the earthquakes occurred in the area investigated and the relative maxima/minima of the mean and the standard deviation of the scaling exponents. Furthermore, the normalized average and standard deviation curves for all the signals tend to converge in correspondence with an earthquake.

Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077905010519
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:32:y:2007:i:1:p:199-211

DOI: 10.1016/j.chaos.2005.10.084

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().