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M. S. Lazaridou

Publications and source records attributed to M. S. Lazaridou.

7 recordsLinked to original sources
arXiv2009

The fluctuations, under time reversal, of the natural time and the entropy distinguish similar looking electric signals of different dynamics

We show that the scale dependence of the fluctuations of the natural time itself under time reversal provides a useful tool for the discrimination of seismic electric signals (critical dynamics) from noises emitted from man made sources as well as for the determination of the scaling exponent. We present recent data of electric signals detected at the Earth's surface, which confirm that the value of the entropy in natural time as well as its value under time reversal are smaller than that of the entropy of a "uniform" distribution.

cond-mat.stat-mech↗
arXiv2008

Investigation of the seismicity after the initiation of a Seismic Electric Signal activity until the main shock

The behavior of seismicity in the area candidate to suffer a main shock is investigated after the observation of the Seismic Electric Signal activity until the impending mainshock. This makes use of the concept of natural time $χ$ and reveals that the probability density function of the variance $κ_1(=< χ^2 > -< χ> ^2)$ exhibits distinct features before the occurrence of the mainshock. Examples are presented, which refer to magnitude class 6.0 earthquakes that occurred in Greece during the first two months in 2008.

cond-mat.stat-mech↗
arXiv2006

Comments on the entropy of seismic electric signals under time reversal

We present recent data of electric signals detected at the Earth's surface, which confirm the earlier finding [Phys. Rev. E 73, 031114 (2006)] that the value of the entropy in natural time as well as its value under time reversal are smaller than that of the entropy of a ``uniform'' distribution. Furthermore, we show that the scale dependence of the fluctuations of the natural time itself under time reversal provides a useful tool for the discrimination of seismic electric signals (critical dynamics) from noises emitted from manmade sources as well as for the determination of the scaling exponent.

cond-mat.stat-mech↗
arXiv2006

Additional information for the paper `Entropy of seismic electric signals: Analysis in natural time under time-reversal'

After the submission of the paper, three strong earthquakes with magnitude around 6.0-units occurred on October 17 and October 20, 2005, with epicenters in the Aegean Sea, at a distance {\em only} 100km from MYT station at which the intense signals $M_1$ to $M_4$ -analyzed in the main text- have been recorded. This confirms experimentally the proposed criterion we used for the classification of these signals as Seismic Electric Signals (SES). Moreover, we show that, if we follow the procedure described in [P.A. Varotsos, N. V. Sarlis, H. K. Tanaka and E. S. Skordas {\it Phys. Rev. E} {\bf 72}, 041103 (2005)], the analysis in the natural time of the seismicity after the SES initiation allows the estimation of the time window of the impending earthquakes with very good accuracy.

physics.geo-ph↗
arXiv2005

Entropy in the natural time-domain

A surrogate data analysis is presented, which is based on the fluctuations of the ``entropy'' $S$ defined in the natural time-domain [Phys. Rev. E {\bf 68}, 031106, 2003]. This entropy is not a static one as, for example, the Shannon entropy. The analysis is applied to three types of time-series, i.e., seismic electric signals, ``artificial'' noises and electrocardiograms, and ``recognizes'' the non-Markovianity in all these signals. Furthermore, it differentiates the electrocardiograms of healthy humans from those of the sudden cardiac death ones. If $δS$ and $δS_{shuf}$ denote the standard deviation when calculating the entropy by means of a time-window sweeping through the original data and the ``shuffled'' (randomized) data, respectively, it seems that the ratio $δS_{shuf}/δS$ plays a key-role. The physical meaning of $δS_{shuf}$ is investigated.

physics.data-an↗
arXiv2005

Natural entropy fluctuations discriminate similar looking electric signals emitted from systems of different dynamics

Complexity measures are introduced, that quantify the change of the natural entropy fluctuations at different length scales in time-series emitted from systems operating far from equilibrium. They identify impending sudden cardiac death (SD) by analyzing fifteen minutes electrocardiograms, and comparing to those of truly healthy humans (H). These measures seem to be complementary to the ones suggested recently [Phys. Rev. E {\bf 70}, 011106 (2004)] and altogether enable the classification of individuals into three categories: H, heart disease patients and SD. All the SD individuals, who exhibit critical dynamics, result in a common behavior.

physics.data-an↗