Power Spectra Analysis of Aeromagnetic Data and KTB Susceptibility Logs, and their Implication for Fractal Behavior of Crustal Magnetization

1998 ◽  
Vol 151 (1) ◽  
pp. 147-159 ◽  
Author(s):  
Shaohua Zhou ◽  
Hans Thybo
Keyword(s):  
Power Spectra ◽  
Aeromagnetic Data ◽  
Spectra Analysis ◽  
Crustal Magnetization

Chaotic vibrations of carbon nanotubes subjected to a traversing force considering nonlocal elasticity theory

2021 ◽  
pp. 239779142110633
Author(s):  
Reza Ebrahimi
Keyword(s):  
Nonlocal Parameter ◽  
Power Spectra ◽  
Beam Theory ◽  
Nonlocal Elasticity Theory ◽  
Effective Control ◽  
Maximum Lyapunov Exponent ◽  
Harmonic Force ◽  
Spectra Analysis ◽  
Chaotic Vibrations ◽  
Euler Bernoulli Beam

The existence of chaos in the lateral vibration of the carbon nanotube (CNT) can contribute to source of instability and inaccuracy within the nano mechanical systems. So, chaotic vibrations of a simply supported CNT which is subjected to a traversing harmonic force are studied in this paper. The model of the system is formulated by using nonlocal Euler–Bernoulli beam theory. The equation of motion is solved using the Rung–Kutta method. The effects of the nonlocal parameter, velocity and amplitude of the traversing harmonic force on the nonlinear dynamic response of the system are analyzed by the bifurcation diagrams, phase plane portrait, power spectra analysis, Poincaré map and the maximum Lyapunov exponent. The results indicate that the nonlocal parameter, velocity and amplitude of the traversing harmonic force have considerable effects on the bifurcation behavior and can be used as effective control parameters for avoiding chaos.

STATISTICAL MODELS FOR INTERPRETING AEROMAGNETIC DATA

Geophysics ◽  
1970 ◽  
Vol 35 (2) ◽  
pp. 293-302 ◽  
Author(s):  
A. Spector ◽  
F. S. Grant
Keyword(s):  
Power Spectrum ◽  
Central America ◽  
Power Spectra ◽  
Power Spectrum Analysis ◽  
Aeromagnetic Data ◽  
Mathematical Basis ◽  
Map Interpretation ◽  
Horizontal Size ◽  
Spectrum Characteristics ◽  
Depth Extent

A mathematical basis for the application of power spectrum analysis to aeromagnetic map interpretation is developed. An ensemble of blocks of varying depth, width, thickness, and magnetization is considered as a statistical model. With the use of the fundamental postulate of statistical mechanics, a formula which can be used to analyze the power spectrum of an aeromagnetic map is developed. The influences of horizontal size, depth, thickness, and depth extent of the blocks on the shape of the power spectrum are assessed. Examples which include power spectra of maps from Canada and Central America demonstrate the application of the approach. In the cases studied a double ensemble of blocks appears to best explain the observed power spectrum characteristics.

Autofocusing based on power-spectra analysis

1994 ◽  
Vol 33 (26) ◽  
pp. 6210 ◽  
Author(s):  
Suganda Jutamulia ◽  
Toshimitsu Asakura ◽  
R. D. Bahuguna ◽  
Panfilo C. De Guzman
Keyword(s):  
Power Spectra ◽  
Spectra Analysis

scholarly journals The diagnostic value of power spectra analysis of the sleep electroencephalography in narcoleptic patients

2015 ◽  
Vol 16 (12) ◽  
pp. 1516-1527 ◽  
Author(s):  
Julie Anja Engelhard Christensen ◽  
Emil Gammelmark Schreiner Munk ◽  
Paul E. Peppard ◽  
Terry Young ◽  
Emmanuel Mignot ◽  
...  
Keyword(s):  
Power Spectra ◽  
Diagnostic Value ◽  
Spectra Analysis

Fractal stochastic modeling of aeromagnetic data

Geophysics ◽  
1991 ◽  
Vol 56 (11) ◽  
pp. 1706-1715 ◽  
Author(s):  
Mark E. Gregotski ◽  
Olivia Jensen ◽  
Jafar Arkani‐Hamed
Keyword(s):  
Power Spectra ◽  
Innovation Process ◽  
Original Data ◽  
Dimensional System ◽  
Deterministic System ◽  
System Function ◽  
Aeromagnetic Data ◽  
Near Surface ◽  
Traditional Assumption ◽  
Fractal Noise

We present a convolutional linear data model for the processing of aeromagnetic data. The model assumes that the data derive from the superposition of a deterministic system function and a stochastic innovation process. The two‐dimensional system function is described by a four‐pass autoregressive (AR) filtering procedure and is radially symmetric. The innovation process represents the distribution of near‐surface magnetic sources and is modeled as a spectrally self‐scaling (i.e., fractal) noise. The appropriate fractal noise is determined by examining aeromagnetic power spectra from various areas of the Canadian Shield. The AR coefficients of the system are determined using an iterative deconvolution procedure. For computational convenience, we make the traditional assumption of a spectrally white innovation, but modify the data prior to its deconvolution by prewhitening the assumed fractal innovation. The recovered system function is then removed from the original data in order to produce the fractal stochastic surface. This deconvolution technique is applied to two aeromagnetic maps from northeastern Ontario, Canada and is shown to be effective in delineating lithologies and enhancing magnetic field anomalies. We propose a particular statistical description of near‐surface magnetic sources for modeling aeromagnetic data in “shield‐type” geologic environments.

Power Spectra Analysis of Levator Veli Palatini Muscle Electromyogram During Velopharyngeal Closure for Swallowing, Speech, and Blowing

Dysphagia ◽  
2007 ◽  
Vol 22 (2) ◽  
pp. 135-139 ◽  
Author(s):  
Kanji Nohara ◽  
Yasuko Kotani ◽  
Maki Ojima ◽  
Yasuhiro Sasao ◽  
Takashi Tachimura ◽  
...  
Keyword(s):  
Power Spectra ◽  
Spectra Analysis ◽  
Levator Veli Palatini ◽  
Velopharyngeal Closure

scholarly journals Identification of Physical Components in Pulsar Emission

2000 ◽  
Vol 177 ◽  
pp. 177-178 ◽  
Author(s):  
J.H. Seiradakis ◽  
A. Karastergiou ◽  
M. Kramer ◽  
D. Psaltis
Keyword(s):  
Radio Telescope ◽  
High Frequency ◽  
Power Spectra ◽  
Emission Characteristics ◽  
Pulsar Emission ◽  
Spectra Analysis ◽  
Physical Components

AbstractWe have used power spectra analysis on high frequency (1.4 GHz) data, obtained with the Effelsberg 100m radio-telescope in order to investigate the emission characteristics of pulsars. This analysis has not only revealed the prominent periodicities of the fluctuating components, but has also proven a powerful tool for identifying weak and often unresolved components and their longitudinal location within the integrated pulsar profile. Furthermore, close examination of the properties of the fluctuating components indicates physical connections between them, giving new insight to the structure of the emitting region.

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