scholarly journals Estimating the power spectra of unevenly sampled X-ray time series: unresolved Gaussian fitting to the autocorrelation function

1994 ◽  
Vol 271 (4) ◽  
pp. 899-909 ◽  
Author(s):  
M. R. Merrifield ◽  
I. M. McHardy
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Power Spectra ◽  
X Ray ◽  
Gaussian Fitting

scholarly journals Analysis of the power spectra, autocorrelation function and EEG time-series signal of a network of leaky integrate-and-fire neurons with conductance-based synapses

2009 ◽  
Vol 10 (S1) ◽  
Author(s):  
Andre DH Peterson ◽  
Hamish Meffin ◽  
Anthony N Burkitt ◽  
Iven MY Mareels ◽  
David B Grayden ◽  
...  
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Power Spectra ◽  
Integrate And Fire

scholarly journals Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

2017 ◽  
Vol 17 (5) ◽  
pp. 3317-3338 ◽  
Author(s):  
Bomidi Lakshmi Madhavan ◽  
Hartwig Deneke ◽  
Jonas Witthuhn ◽  
Andreas Macke
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Multiresolution Analysis ◽  
Global Radiation ◽  
Power Spectra ◽  
Spatiotemporal Variability ◽  
Dense Network ◽  
Point Measurement ◽  
Single Station ◽  
Sky Conditions

Abstract. The time series of global radiation observed by a dense network of 99 autonomous pyranometers during the HOPE campaign around Jülich, Germany, are investigated with a multiresolution analysis based on the maximum overlap discrete wavelet transform and the Haar wavelet. For different sky conditions, typical wavelet power spectra are calculated to quantify the timescale dependence of variability in global transmittance. Distinctly higher variability is observed at all frequencies in the power spectra of global transmittance under broken-cloud conditions compared to clear, cirrus, or overcast skies. The spatial autocorrelation function including its frequency dependence is determined to quantify the degree of similarity of two time series measurements as a function of their spatial separation. Distances ranging from 100 m to 10 km are considered, and a rapid decrease of the autocorrelation function is found with increasing frequency and distance. For frequencies above 1∕3 min−1 and points separated by more than 1 km, variations in transmittance become completely uncorrelated. A method is introduced to estimate the deviation between a point measurement and a spatially averaged value for a surrounding domain, which takes into account domain size and averaging period, and is used to explore the representativeness of a single pyranometer observation for its surrounding region. Two distinct mechanisms are identified, which limit the representativeness; on the one hand, spatial averaging reduces variability and thus modifies the shape of the power spectrum. On the other hand, the correlation of variations of the spatially averaged field and a point measurement decreases rapidly with increasing temporal frequency. For a grid box of 10 km  ×  10 km and averaging periods of 1.5–3 h, the deviation of global transmittance between a point measurement and an area-averaged value depends on the prevailing sky conditions: 2.8 (clear), 1.8 (cirrus), 1.5 (overcast), and 4.2 % (broken clouds). The solar global radiation observed at a single station is found to deviate from the spatial average by as much as 14–23 (clear), 8–26 (cirrus), 4–23 (overcast), and 31–79 W m−2 (broken clouds) from domain averages ranging from 1 km  ×  1 km to 10 km  ×  10 km in area.

Log-log scale roughness spectroscopy of surfaces

1993 ◽  
Vol 51 ◽  
pp. 224-225
Author(s):  
P. Fraundorf ◽  
B. Armbruster
Keyword(s):  
Power Spectrum ◽  
Autocorrelation Function ◽  
Power Spectra ◽  
Scanning Force Microscopy ◽  
Scanning Tunneling ◽  
Tunneling Microscopy ◽  
Force Microscopy ◽  
Scanning Force ◽  
Lateral Structure ◽  
Scale Roughness

Optical interferometry, confocal light microscopy, stereopair scanning electron microscopy, scanning tunneling microscopy, and scanning force microscopy, can produce topographic images of surfaces on size scales reaching from centimeters to Angstroms. Second moment (height variance) statistics of surface topography can be very helpful in quantifying “visually suggested” differences from one surface to the next. The two most common methods for displaying this information are the Fourier power spectrum and its direct space transform, the autocorrelation function or interferogram. Unfortunately, for a surface exhibiting lateral structure over several orders of magnitude in size, both the power spectrum and the autocorrelation function will find most of the information they contain pressed into the plot’s origin. This suggests that we plot power in units of LOG(frequency)≡-LOG(period), but rather than add this logarithmic constraint as another element of abstraction to the analysis of power spectra, we further recommend a shift in paradigm.

Intervention Modeling

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Moving Average ◽  
Intervention Model ◽  
Noise Component ◽  
Autoregressive Integrated Moving Average ◽  
Noise Function ◽  
Modeling Strategy ◽  
The Impact ◽  
True Structure

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.

scholarly journals Aperiodic Flux Variability in A 0535+262

1996 ◽  
Vol 165 ◽  
pp. 313-319
Author(s):  
Mark H. Finger ◽  
Robert B. Wilson ◽  
B. Alan Harmon ◽  
William S. Paciesas
Keyword(s):  
Neutron Star ◽  
Gamma Ray ◽  
Beat Frequency ◽  
Power Spectra ◽  
Center Frequency ◽  
X Ray ◽  
Binary Pulsar ◽  
Transient Source ◽  
Flux Variability ◽  
Burst And Transient Source

A “giant” outburst of A 0535+262, a transient X-ray binary pulsar, was observed in 1994 February and March with the Burst and Transient Source Experiment (BATSE) onboard the Compton Gamma-Ray Observatory. During the outburst power spectra of the hard X-ray flux contained a QPO-like component with a FWHM of approximately 50% of its center frequency. Over the course of the outburst the center frequency rose smoothly from 35 mHz to 70 mHz and then fell to below 40 mHz. We compare this QPO frequency with the neutron star spin-up rate, and discuss the observed correlation in terms of the beat frequency and Keplerian frequency QPO models in conjunction with the Ghosh-Lamb accretion torque model.

scholarly journals A minimal timescale for the continuum in 4U 1608-52 and Aql X-1

2021 ◽  
Vol 502 (1) ◽  
pp. L72-L78
Author(s):  
K Mohamed ◽  
E Sonbas ◽  
K S Dhuga ◽  
E Göğüş ◽  
A Tuncer ◽  
...  
Keyword(s):  
Black Hole ◽  
Neutron Star ◽  
Power Spectra ◽  
Light Curves ◽  
State Transitions ◽  
Strong Positive Correlation ◽  
Present Evidence ◽  
X Ray ◽  
X Ray Binaries ◽  
The Continuum

ABSTRACT Similar to black hole X-ray binary transients, hysteresis-like state transitions are also seen in some neutron-star X-ray binaries. Using a method based on wavelets and light curves constructed from archival Rossi X-ray Timing Explorer observations, we extract a minimal timescale over the complete range of transitions for 4U 1608-52 during the 2002 and 2007 outbursts and the 1999 and 2000 outbursts for Aql X-1. We present evidence for a strong positive correlation between this minimal timescale and a similar timescale extracted from the corresponding power spectra of these sources.

scholarly journals SARIMA Approach to Generating Synthetic Monthly Rainfall in the Sinú River Watershed in Colombia

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 602
Author(s):  
Luisa Martínez-Acosta ◽  
Juan Pablo Medrano-Barboza ◽  
Álvaro López-Ramos ◽  
John Freddy Remolina López ◽  
Álvaro Alberto López-Lambraño
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Autocorrelation Function ◽  
Information Criterion ◽  
Monthly Rainfall ◽  
Statistical Characteristics ◽  
Rainfall Time Series ◽  
River Watershed ◽  
Statistical Measures ◽  
Sarima Models

Seasonal Auto Regressive Integrative Moving Average models (SARIMA) were developed for monthly rainfall time series. Normality of the rainfall time series was achieved by using the Box Cox transformation. The best SARIMA models were selected based on their autocorrelation function (ACF), partial autocorrelation function (PACF), and the minimum values of the Akaike Information Criterion (AIC). The result of the Ljung–Box statistical test shows the randomness and homogeneity of each model residuals. The performance and validation of the SARIMA models were evaluated based on various statistical measures, among these, the Student’s t-test. It is possible to obtain synthetic records that preserve the statistical characteristics of the historical record through the SARIMA models. Finally, the results obtained can be applied to various hydrological and water resources management studies. This will certainly assist policy and decision-makers to establish strategies, priorities, and the proper use of water resources in the Sinú river watershed.

scholarly journals A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms

2021 ◽  
Vol 32 (3) ◽  
Author(s):  
Dimitrios Bellos ◽  
Mark Basham ◽  
Tony Pridmore ◽  
Andrew P. French
Keyword(s):  
Time Series ◽  
Knowledge Transfer ◽  
Semantic Segmentation ◽  
Real World Data ◽  
Transfer Scheme ◽  
X Ray ◽  
Segmentation Accuracy ◽  
X Ray Computed ◽  
Temporal Events ◽  
Time Critical

AbstractOver recent years, many approaches have been proposed for the denoising or semantic segmentation of X-ray computed tomography (CT) scans. In most cases, high-quality CT reconstructions are used; however, such reconstructions are not always available. When the X-ray exposure time has to be limited, undersampled tomograms (in terms of their component projections) are attained. This low number of projections offers low-quality reconstructions that are difficult to segment. Here, we consider CT time-series (i.e. 4D data), where the limited time for capturing fast-occurring temporal events results in the time-series tomograms being necessarily undersampled. Fortunately, in these collections, it is common practice to obtain representative highly sampled tomograms before or after the time-critical portion of the experiment. In this paper, we propose an end-to-end network that can learn to denoise and segment the time-series’ undersampled CTs, by training with the earlier highly sampled representative CTs. Our single network can offer two desired outputs while only training once, with the denoised output improving the accuracy of the final segmentation. Our method is able to outperform state-of-the-art methods in the task of semantic segmentation and offer comparable results in regard to denoising. Additionally, we propose a knowledge transfer scheme using synthetic tomograms. This not only allows accurate segmentation and denoising using less real-world data, but also increases segmentation accuracy. Finally, we make our datasets, as well as the code, publicly available.

An Experimental Study of the Forced Response of Pre- and Post-Critical Plates

1995 ◽  
Author(s):  
Kevin D. Murphy ◽  
Lawrence N. Virgin ◽  
Stephen A. Rizzi
Keyword(s):  
Experimental Study ◽  
Time Series ◽  
Lyapunov Exponent ◽  
Small Amplitude ◽  
Narrow Band ◽  
Power Spectra ◽  
Forced Response ◽  
Acoustic Excitation ◽  
Rectangular Plates ◽  
Auto Correlation

Abstract Experimental results are presented which characterize the dynamic response of homogeneous, fully clamped, rectangular plates to narrow band acoustic excitation and uniform thermal loads. Using time series, pseudo-phase projections, power spectra and auto-correlation functions, small amplitude vibrations are considered about both the pre- and post-critical states. These techniques are then employed to investigate the snap-through response. The results for snap-through suggest that the motion is temporally complex and a Lyapunov exponent calculation confirms that the motion is chaotic. Finally, a snap-through boundary is mapped in the (ω, SPL) parameter space separating the regions of snap-through and no snap-through.

Sign in / Sign up

Export Citation Format

Share Document