108 research outputs found
An attempt to find precursors in the ULF geomagnetic data by means of flicker noise spectroscopy
International audienceThe flicker noise spectroscopy which is a new phenomenological method for the retrieval of information contained in chaotic time signals, is based on the analysis of recognizable irregularities (pulse, jumps, and discontinuities of derivatives of various order). This method is applied to the ULF (ultra-low-frequency) data observed at Guam in 1992?1994, in order to study the temporal nonlinear behavior of the lithospheric activity prior to the large 1993 Guam earthquake (8 August 1993). We have found that the lithosphere must have exhibited the step-like discontinuous behaviors in the lithosphere 101, 78, 54, 31 and 8 days before the main shock. This kind of nonlinear temporal behavior can be tracked by means of our flicker noise spectroscopy
Analytical method for parameterizing the random profile components of nanosurfaces imaged by atomic force microscopy
The functional properties of many technological surfaces in biotechnology,
electronics, and mechanical engineering depend to a large degree on the
individual features of their nanoscale surface texture, which in turn are a
function of the surface manufacturing process. Among these features, the
surface irregularities and self-similarity structures at different spatial
scales, especially in the range of 1 to 100 nm, are of high importance because
they greatly affect the surface interaction forces acting at a nanoscale
distance. An analytical method for parameterizing the surface irregularities
and their correlations in nanosurfaces imaged by atomic force microscopy (AFM)
is proposed. In this method, flicker noise spectroscopy - a statistical physics
approach - is used to develop six nanometrological parameters characterizing
the high-frequency contributions of jump- and spike-like irregularities into
the surface texture. These contributions reflect the stochastic processes of
anomalous diffusion and inertial effects, respectively, in the process of
surface manufacturing. The AFM images of the texture of corrosion-resistant
magnetite coatings formed on low-carbon steel in hot nitrate solutions with
coating growth promoters at different temperatures are analyzed. It is shown
that the parameters characterizing surface spikiness are able to quantify the
effect of process temperature on the corrosion resistance of the coatings. It
is suggested that these parameters can be used for predicting and
characterizing the corrosion-resistant properties of magnetite coatings.Comment: 7 pages, 3 figures, 2 tables; to be published in Analys
Anomalous diffusion in the dynamics of complex processes
Anomalous diffusion, process in which the mean-squared displacement of system
states is a non-linear function of time, is usually identified in real
stochastic processes by comparing experimental and theoretical displacements at
relatively small time intervals. This paper proposes an interpolation
expression for the identification of anomalous diffusion in complex signals for
the cases when the dynamics of the system under study reaches a steady state
(large time intervals). This interpolation expression uses the chaotic
difference moment (transient structural function) of the second order as an
average characteristic of displacements. A general procedure for identifying
anomalous diffusion and calculating its parameters in real stochastic signals,
which includes the removal of the regular (low-frequency) components from the
source signal and the fitting of the chaotic part of the experimental
difference moment of the second order to the interpolation expression, is
presented. The procedure was applied to the analysis of the dynamics of
magnetoencephalograms, blinking fluorescence of quantum dots, and X-ray
emission from accreting objects. For all three applications, the interpolation
was able to adequately describe the chaotic part of the experimental difference
moment, which implies that anomalous diffusion manifests itself in these
natural signals. The results of this study make it possible to broaden the
range of complex natural processes in which anomalous diffusion can be
identified. The relation between the interpolation expression and a diffusion
model, which is derived in the paper, allows one to simulate the chaotic
processes in the open complex systems with anomalous diffusion.Comment: 47 pages, 15 figures; Submitted to Physical Review
Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia
We apply flicker-noise spectroscopy (FNS), a time series analysis method
operating on structure functions and power spectrum estimates, to study the
clinical electroencephalogram (EEG) signals recorded in children/adolescents
(11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the
National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical
Sciences. The EEG signals for these subjects were compared with the signals for
a control sample of chronically depressed children/adolescents. The purpose of
the study is to look for diagnostic signs of subjects' susceptibility to
schizophrenia in the FNS parameters for specific electrodes and
cross-correlations between the signals simultaneously measured at different
points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes
at locations F3 and F4, which are symmetrically positioned in the left and
right frontal areas of cerebral cortex, respectively, demonstrates an essential
role of frequency-phase synchronization, a phenomenon representing specific
correlations between the characteristic frequencies and phases of excitations
in the brain. We introduce quantitative measures of frequency-phase
synchronization and systematize the values of FNS parameters for the EEG data.
The comparison of our results with the medical diagnoses for 84 subjects
performed at NCPH makes it possible to group the EEG signals into 4 categories
corresponding to different risk levels of subjects' susceptibility to
schizophrenia. We suggest that the introduced quantitative characteristics and
classification of cross-correlations may be used for the diagnosis of
schizophrenia at the early stages of its development.Comment: 36 pages, 6 figures, 2 tables; to be published in "Physica A
Frequency and Phase Synchronization in Neuromagnetic Cortical Responses to Flickering-Color Stimuli
In our earlier study dealing with the analysis of neuromagnetic responses
(magnetoencephalograms - MEG) to flickering-color stimuli for a group of
control human subjects (9 volunteers) and a patient with photosensitive
epilepsy (a 12-year old girl), it was shown that Flicker-Noise Spectroscopy
(FNS) was able to identify specific differences in the responses of each
organism. The high specificity of individual MEG responses manifested itself in
the values of FNS parameters for both chaotic and resonant components of the
original signal. The present study applies the FNS cross-correlation function
to the analysis of correlations between the MEG responses simultaneously
measured at spatially separated points of the human cortex processing the
red-blue flickering color stimulus. It is shown that the cross-correlations for
control (healthy) subjects are characterized by frequency and phase
synchronization at different points of the cortex, with the dynamics of
neuromagnetic responses being determined by the low-frequency processes that
correspond to normal physiological rhythms. But for the patient, the frequency
and phase synchronization breaks down, which is associated with the suppression
of cortical regulatory functions when the flickering-color stimulus is applied,
and higher frequencies start playing the dominating role. This suggests that
the disruption of correlations in the MEG responses is the indicator of
pathological changes leading to photosensitive epilepsy, which can be used for
developing a method of diagnosing the disease based on the analysis with the
FNS cross-correlation function.Comment: 21 pages, 14 figures; submitted to "Laser Physics", 2010, 2
Identification of earthquake precursors in the hydrogeochemical and geoacoustic data for the Kamchatka peninsula by flicker-noise spectroscopy
A phenomenological systems approach for identifying potential precursors in
multiple signals of different types for the same local seismically active
region is proposed based on the assumption that a large earthquake may be
preceded by a system reconfiguration (preparation) at different time and space
scales. A nonstationarity factor introduced within the framework of
flicker-noise spectroscopy, a statistical physics approach to the analysis of
time series, is used as the dimensionless criterion for detecting qualitative
(precursory) changes within relatively short time intervals in arbitrary
signals. Nonstationarity factors for chlorine-ion concentration variations in
the underground water of two boreholes on the Kamchatka peninsula and
geacoustic emissions in a deep borehole within the same seismic zone are
studied together in the time frame around a large earthquake on October 8,
2001. It is shown that nonstationarity factor spikes (potential precursors)
take place in the interval from 70 to 50 days before the earthquake for the
hydrogeochemical data and at 29 and 6 days in advance for the geoacoustic data.Comment: 8 pages, 4 figures; to be published in Nat. Hazards Earth Syst. Sc
Cross-Correlation Earthquake Precursors in the Hydrogeochemical and Geoacoustic Signals for the Kamchatka Peninsula
We propose a new type of earthquake precursor based on the analysis of
correlation dynamics between geophysical signals of different nature. The
precursor is found using a two-parameter cross-correlation function introduced
within the framework of flicker-noise spectroscopy, a general statistical
physics approach to the analysis of time series. We consider an example of
cross-correlation analysis for water salinity time series, an integral
characteristic of the chemical composition of groundwater, and geoacoustic
emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time
frame from 2001 to 2003, which is characterized by a sequence of three groups
of significant seismic events. We found that cross-correlation precursors took
place 27, 31, and 35 days ahead of the strongest earthquakes for each group of
seismic events, respectively. At the same time, precursory anomalies in the
signals themselves were observed only in the geoacoustic emissions for one
group of earthquakes.Comment: 21 pages, 5 figures, 1 table; to be published in "Acta Geophysica".
arXiv admin note: substantial text overlap with arXiv:1101.147
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