Spectral Correlation Properties of Time Series Due To An Acoustic Source Moving Through An Oceanic Waveguide.

1996 ◽  
Author(s):  
M. Reuter
Keyword(s):  
Time Series ◽  
Acoustic Source ◽  
Oceanic Waveguide ◽  
Spectral Correlation ◽  
Correlation Properties

LONG RANGE CORRELATION PROPERTIES OF AFTERSHOCK RELAXATION SIGNALS

Fractals ◽  
1995 ◽  
Vol 03 (04) ◽  
pp. 839-847 ◽  
Author(s):  
A. VESPIGNANI ◽  
A. PETRI ◽  
A. ALIPPI ◽  
G. PAPARO ◽  
M. COSTANTINI
Keyword(s):  
Time Series ◽  
Acoustic Emission ◽  
Statistical Analysis ◽  
Power Spectrum ◽  
Power Law ◽  
Amplitude Distribution ◽  
Relaxation Processes ◽  
Critical Dynamics ◽  
Range Correlation ◽  
Correlation Properties

Relaxation processes taking place after microfracturing of laboratory samples give rise to ultrasonic acoustic emission signals. Statistical analysis of the resulting time series has revealed many features which are characteristic of critical phenomena. In particular, the autocorrelation functions obey a power-law behavior, implying a power spectrum of the kind 1/f. Also the amplitude distribution N(V) of such signals follows a power law, and the obtained exponents are consistent with those found in other experiments: N(V) dV≃V–γ dV, with γ=1.7±0.2. We also analyzed the distribution N(τ) of the delay time τ between two consecutive acoustic emission events. We found that a N(τ) distribution rather close to a power law constitutes a common feature of all the recorded signals. These experimental results can be considered as a striking evidence for a critical dynamics underlying the microfracturing processes.

The Multi-Dependent Hurst Exponent in Traffic Time Series

2010 ◽  
Vol 20-23 ◽  
pp. 346-351
Author(s):  
Ke Qiang Dong ◽  
Peng Jian Shang ◽  
Hong Zhang
Keyword(s):  
Time Series ◽  
Long Range ◽  
Hurst Exponent ◽  
Short Range ◽  
A Priori ◽  
Correlated Data ◽  
Nonstationary Time Series ◽  
Traffic Time Series ◽  
Correlation Exponent ◽  
Correlation Properties

We propose a new method called the multi-dependent Hurst exponent to investigate the correlation properties of the nonstationary time series. The method is validated with the artificial series including both short-range correlated data and long-range correlated data. The results indicate that the multi-dependent Hurst exponents fluctuate around the a-priori known correlation exponent H. Application to traffic time series is also presented, and comparison is made between the artificial time series and traffic time series.

Remote acoustic classification of marine sediments with application to offshore Newfoundland

1983 ◽  
Vol 20 (7) ◽  
pp. 1195-1211 ◽  
Author(s):  
N. A. Cochrane ◽  
A. D. Dunsiger
Keyword(s):  
Marine Sediments ◽  
Classification Scheme ◽  
Spatial Coherence ◽  
Unconsolidated Sediments ◽  
Limited Area ◽  
Acoustic Source ◽  
Shallow Marine Sediments ◽  
Correlation Properties ◽  
Acoustic Classification

Shallow marine sediments can be remotely classified by the spatial correlation properties of their seismic reflection signatures provided one uses a highly repetitive broadband acoustic source. A classification scheme defined by three spatial coherence parameters is shown capable of automatically differentiating between several formations of unconsolidated sediments in a limited area of offshore Newfoundland. The consistency and generality of the technique are explored and comparisons with standard echogram interpretation are made.

ANALYSIS OF CORRELATION PROPERTIES IN GEOELECTRICAL DATA

Fractals ◽  
2003 ◽  
Vol 11 (01) ◽  
pp. 27-38 ◽  
Author(s):  
GERARDO COLANGELO ◽  
VINCENZO LAPENNA ◽  
LUCIANO TELESCA
Keyword(s):  
Time Series ◽  
Detrended Fluctuation Analysis ◽  
Southern Italy ◽  
Fluctuation Analysis ◽  
Scaling Exponents ◽  
Long Range Correlations ◽  
The Mean ◽  
Correlation Properties ◽  
Seismic Area ◽  
Detrended Fluctuation

This paper considers four geoelectrical time series, measured in a seismic area of Southern Italy. Lomb Periodogram method, Higuchi analysis, Detrended Fluctuation Analysis (DFA) and the mean distance spanned within time L are used to discuss the correlation properties of these signals. The values of the scaling exponents from these methods of the geoelectrical data indicate that the long-range correlations are present. Furthermore, it is found that these correlations are all linear.

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