alexa Traces of Long-Memory in Pre-Seismic MHz Electromagnetic Time Series-Part 1: Investigation Through the R/S Analysis and Time-Evolving Spectral Fractals
ISSN: 2157-7617

Journal of Earth Science & Climatic Change
Open Access

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Research Article

Traces of Long-Memory in Pre-Seismic MHz Electromagnetic Time Series-Part 1: Investigation Through the R/S Analysis and Time-Evolving Spectral Fractals

Dimitrios Nikolopoulos1, Demetrios Cantzos2, Ermioni Petraki1, Panayiotis H. Yannakopoulos1 and Constantinos Nomicos3*

1Piraeus University of Applied Sciences (TEI of Piraeus), Electronic Computer Systems Engineering, Petrou Ralli and Thivon - 250, GR-12244 Aigaleo, Greece

2Piraeus University of Applied Sciences (TEI of Piraeus), Department of Automation Engineering, Petrou Ralli and Thivon - 250, GR-12244 Aigaleo, Greece

3TEI of Athens, Department of Electronic Engineering, Agiou Spyridonos, GR-12243, Aigaleo, Athens, Greece

*Corresponding Author:
Dimitrios Nikolopoulos
Piraeus University of Applied Sciences (TEI of Piraeus)
Department of Electronic Computer Systems Engineering
Petrou Ralli and Thivon - 250, GR-12244 Aigaleo, Greece
Tel no: 0030-210-5381560
Fax: 0030-210-5381436
E-mail: [email protected]

Received date: June 26, 2016; Accepted date: July 15, 2016; Published date: July 18, 2016

Citation: Nikolopoulos D, Cantzos D, Petraki E, Yannakopoulos PH, Nomicos C (2016) Traces of Long-Memory in Pre-Seismic MHz Electromagnetic Time Series-Part 1: Investigation Through the R/S Analysis and Time-Evolving Spectral Fractals. J Earth Sci Clim Change 7:359. doi: 10.4172/2157-7617.1000359

Copyright: © 2016 Nikolopoulos D, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



This paper reports characteristic pre seismic electromagnetic disturbances in the MHz range detected prior to seven significant earthquakes of M L ≥ 5.0 which occurred in Greece between 2009 and 2015. The whole data set was investigated through Rescaled Range (R/S) analysis and wavelet based spectral fractal analysis. The long-memory trends hidden in the analysed signals were investigated via the Hurst exponent (H). The R/S method indicated that in the majority of the segments of the investigated signals, the H - exponents were in the range 0.7-0.9. Several exponents were above 0.9. This is associated with persistency. In several segments, the Hurst exponent exhibited small variance. Noteworthy fluctuations were also found. In many cases the H - time fluctuations were independent of the time evolution of the associated electromagnetic signals. The spectral fractal method, being more suited for this purpose, highlighted the characteristic signals’ epochs, governed by long-lasting fractal organisation. The calculated Hurst exponents in the characteristic long-lasting fractal epochs were associated with medium anti-persistent behaviour or with continuous switching between anti-persistency and persistency. The H - exponents of the random fractal organised segments were mainly persistent. From the data presented in this paper, it is deduced that the R/S method provides additional information on the estimation of the Hurst exponent when combined with the spectral fractal method. Both techniques should be employed in sequential steps to enhance the precursory value of the results.


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