Maximum Autocorrelation Factorial Kriging
Nielsen, Allan Aasbjerg; Conradsen, Knut; Pedersen, John L.;
2000-01-01
This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from an...
Functional Maximum Autocorrelation Factors
Larsen, Rasmus; Nielsen, Allan Aasbjerg
2005-01-01
\\verb+~+\\$\\backslash\\$cite{ramsay97} to functional maximum autocorrelation factors (MAF)\\verb+~+\\$\\backslash\\$cite{switzer85,larsen2001d}. We apply the method to biological shapes as well as reflectance spectra. {\\$\\backslash\\$bf Methods}. MAF seeks linear combination of the original variables that maximize autocorrelation between...
Low autocorrelation binary sequences
Packebusch, Tom; Mertens, Stephan
2016-04-01
Binary sequences with minimal autocorrelations have applications in communication engineering, mathematics and computer science. In statistical physics they appear as groundstates of the Bernasconi model. Finding these sequences is a notoriously hard problem, that so far can be solved only by exhaustive search. We review recent algorithms and present a new algorithm that finds optimal sequences of length N in time O(N {1.73}N). We computed all optimal sequences for N≤slant 66 and all optimal skewsymmetric sequences for N≤slant 119.
Decomposition using Maximum Autocorrelation Factors
Larsen, Rasmus
2002-01-01
, normally we have an ordering of landmarks (variables) along the contour of the objects. For the case with observation ordering the maximum autocorrelation factor (MAF) transform was proposed for multivariate imagery in\\verb+~+\\$\\backslash\\$cite{switzer85}. This corresponds to a R-mode analyse of the data...
Autocorrelated residuals of robust regression
Kalina, Jan
Slaný : Melandrium, 2013 - (Löster, T.; Pavelka, T.), s. 551-560 ISBN 978-80-86175-87-4. [International Days of Statistics and Economics /7./. Prague (CZ), 19.09.2013-21.09.2013] Grant ostatní: GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : linear regression * robust statistics * diagnostics * autocorrelation Subject RIV: BB - Applied Statistics, Operational Research http://msed.vse.cz/files/2013/1-Kalina-Jan-paper.pdf
Autocorrelation Measures for the Quadratic Assignment Problem
Chicano, Francisco; Luque, Gabriel; Alba, Enrique
2012-01-01
In this article we provide an exact expression for computing the autocorrelation coefficient $\\xi$ and the autocorrelation length $\\ell$ of any arbitrary instance of the Quadratic Assignment Problem (QAP) in polynomial time using its elementary landscape decomposition. We also provide empirical evidence of the autocorrelation length conjecture in QAP and compute the parameters $\\xi$ and $\\ell$ for the 137 instances of the QAPLIB. Our goal is to better characterize the difficulty of this impor...
Parallel auto-correlative statistics with VTK.
Pebay, Philippe Pierre [Kitware, France; Bennett, Janine Camille
2013-08-01
This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.
Measurement of surface plasmon autocorrelation functions
Lemke, Christoph; Leißner, Till; Klick, Alwin;
2013-01-01
In this paper we demonstrate the realization of an autocorrelator for the characterization of ultrashort surface plasmon polariton (SPP) pulses. A wedge shaped structure is used to continuously increase the time delay between two interfering SPPs. The autocorrelation signal is monitored by non-li......-linear two-photon photoemission electron microscopy. The presented approach is applicable to other SPP sensitive detection schemes that provide only moderate spatial resolution and may therefore be of general interest in the field of ultrafast plasmonics.......In this paper we demonstrate the realization of an autocorrelator for the characterization of ultrashort surface plasmon polariton (SPP) pulses. A wedge shaped structure is used to continuously increase the time delay between two interfering SPPs. The autocorrelation signal is monitored by non...
A simple method to estimate interwell autocorrelation
Pizarro, J.O.S.; Lake, L.W. [Univ. of Texas, Austin, TX (United States)
1997-08-01
The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.
Spatial Autocorrelation Analysis of Migration and Selection
Sokal, R R; Jacquez, G M; Wooten, M. C.
1989-01-01
We test various assumptions necessary for the interpretation of spatial autocorrelation analysis of gene frequency surfaces, using simulations of Wright's isolation-by-distance model with migration or selection superimposed. Increasing neighborhood size enhances spatial autocorrelation, which is reduced again for the largest neighborhood sizes. Spatial correlograms are independent of the mean gene frequency of the surface. Migration affects surfaces and correlograms when immigrant gene freque...
Linear Prediction Using Refined Autocorrelation Function
M. Shahidur Rahman
2007-07-01
Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.
Autocorrelation of Sequences Generated by Single Cycle T-Functions
Wang Yan; Hu Yupu; Li Shunbo; Yang Yang
2011-01-01
Cryptographic properties of the single cycle T-function's output sequences are investigated.Bounds of autocorrelation functions of the kth coordinate sequence and bounds of state output sequence are calculated respectively.The Maximum Sidelobe Ratio (MSR) of the kth coordinate sequence and the MSR of state output sequence are given respectively.The bounds of autocorrelation functions show that the values of autocorrelation functions are large when shifts are small.Comparisons of the autocorrelations between the state output sequence and coordinate output sequence are illustrated.The autocorrelation properties demonstrate that T-functions have cryptographic weaknesses and the illustration result shows coordinate output sequences have better autocorrelation than that of state output sequences.
Inference for local autocorrelations in locally stationary models
Zhao, Zhibiao
2014-01-01
For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address important hypothesis testing problems, such as whether the local autocorrelation process is indeed time-varying and whether the local autocorrelation is zero. In particular, our result provides a...
Development of SHG autocorrelation system for JAERI FEL
Kikuzawa, N.; Yamauchi, T.; Nagai, R.; Minehara, E. J. [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
2000-07-01
A second-order autocorrelator based on second-generation (SHG) in a CdTe crystal has been developing for measurement of FEL pulse duration in FIR region. The conversion efficiency of SHG was experimentally obtained to be {approx}3xl0{sup -5}/(MWcm{sup 2}). This report describes experimental results of the SHG autocorrelator. (author)
Balance Maintenance in the Upright Body Position: Analysis of Autocorrelation
Stodolka¹ Jacek
2016-04-01
Full Text Available The present research aimed to analyze values of the autocorrelation function measured for different time values of ground reaction forces during stable upright standing. It was hypothesized that if recording of force in time depended on the quality and way of regulating force by the central nervous system (as a regulator, then the application of autocorrelation for time series in the analysis of force changes in time function would allow to determine regulator properties and its functioning. The study was performed on 82 subjects (students, athletes, senior and junior soccer players and subjects who suffered from lower limb injuries. The research was conducted with the use of two Kistler force plates and was based on measurements of ground reaction forces taken during a 15 s period of standing upright while relaxed. The results of the autocorrelation function were statistically analyzed. The research revealed a significant correlation between a derivative extreme and velocity of reaching the extreme by the autocorrelation function, described as gradient strength. Low correlation values (all statistically significant were observed between time of the autocorrelation curve passing through 0 axis and time of reaching the first peak by the said function. Parameters computed on the basis of the autocorrelation function are a reliable means to evaluate the process of flow of stimuli in the nervous system. Significant correlations observed between the parameters of the autocorrelation function indicate that individual parameters provide similar properties of the central nervous system.
Autocorrelation in queuing network-type production systems - revisited
Nielsen, Erland Hejn
2007-01-01
In managing production systems, a strong emphasis is placed on the reduction of variance in specific transformation processes (e.g. for quality control purposes) and on controlling the level of variability in general, as for instance with the Bullwhip effect. However, the possible disturbing......, either production managers are missing important aspects in production planning, or the 'realistic' autocorrelation patterns inherent in actual production setups are not like those considered in the literature. In this paper, relevant and 'realistic' types of autocorrelation schemes are characterised and...... their levels discussed. The paper puts previous works on the impact of autocorrelation in queuing networks in perspective for production systems....
Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection
Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle
2015-01-01
Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of phenotyp
Consequences of spatial autocorrelation for niche-based models
Segurado, P.; Araújo, Miguel B.; Kunin, W. E.
2006-01-01
of significance based on randomizations were obtained. 3. Spatial autocorrelation was shown to represent a serious problem for niche-based species' distribution models. Significance values were found to be inflated up to 90-fold. 4. In general, GAM and CTA performed better than GLM, although all three methods...... autocorrelated variables, these need to be adjusted. The reliability and value of niche-based distribution models for management and other applied ecology purposes can be improved if certain techniques and procedures, such as the null model approach recommended in this study, are implemented during the model......1. Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2. Analyses were based...
Mode Analysis with Autocorrelation Method (Single Time Series) in Tokamak
Saadat, Shervin; Salem, Mohammad K.; Goranneviss, Mahmoud; Khorshid, Pejman
2010-08-01
In this paper plasma mode analyzed with statistical method that designated Autocorrelation function. Auto correlation function used from one time series, so for this purpose we need one Minov coil. After autocorrelation analysis on mirnov coil data, spectral density diagram is plotted. Spectral density diagram from symmetries and trends can analyzed plasma mode. RHF fields effects with this method ate investigated in IR-T1 tokamak and results corresponded with multichannel methods such as SVD and FFT.
Use of autocorrelation of wavelet coefficients for fault diagnosis
Rafiee, J.; Tse, P. W.
2009-07-01
This paper presents a novel time-frequency-based feature recognition system for gear fault diagnosis using autocorrelation of continuous wavelet coefficients (CWC). Furthermore, it introduces an original mathematical approximation of gearbox vibration signals which approximates sinusoidal components of noisy vibration signals generated from gearboxes, including incipient and serious gear failures using autocorrelation of CWC. First, the drawbacks of the continuous wavelet transform (CWT) have been eliminated using autocorrelation function. Secondly, the autocorrelation of CWC is introduced as an original pattern for fault identification in machine condition monitoring. Thirdly, a sinusoidal summation function consisting of eight terms was used to approximate the periodic waveforms generated by autocorrelation of CWC for normal gearboxes (NGs) as well as occurrences of incipient and severe gear fault (e.g. slight-worn, medium-worn, and broken-tooth gears). In other words, the size of vibration signals can be reduced with minimal loss of significant frequency content by means of the sinusoidal approximation of generated autocorrelation waveforms of CWC as reported in this paper.
A method for detecting positive growth autocorrelation without marking individuals.
Mollie E Brooks
Full Text Available In most ecological studies, within-group variation is a nuisance that obscures patterns of interest and reduces statistical power. However, patterns of within-group variability often contain information about ecological processes. In particular, such patterns can be used to detect positive growth autocorrelation (consistent variation in growth rates among individuals in a cohort across time, even in samples of unmarked individuals. Previous methods for detecting autocorrelated growth required data from marked individuals. We propose a method that requires only estimates of within-cohort variance through time, using maximum likelihood methods to obtain point estimates and confidence intervals of the correlation parameter. We test our method on simulated data sets and determine the loss in statistical power due to the inability to identify individuals. We show how to accommodate nonlinear growth trajectories and test the effects of size-dependent mortality on our method's accuracy. The method can detect significant growth autocorrelation at moderate levels of autocorrelation with moderate-sized cohorts (for example, statistical power of 80% to detect growth autocorrelation ρ (2 = 0.5 in a cohort of 100 individuals measured on 16 occasions. We present a case study of growth in the red-eyed tree frog. Better quantification of the processes driving size variation will help ecologists improve predictions of population dynamics. This work will help researchers to detect growth autocorrelation in cases where marking is logistically infeasible or causes unacceptable decreases in the fitness of marked individuals.
Spatial Autocorrelation and Uncertainty Associated with Remotely-Sensed Data
Daniel A. Griffith
2016-06-01
Full Text Available Virtually all remotely sensed data contain spatial autocorrelation, which impacts upon their statistical features of uncertainty through variance inflation, and the compounding of duplicate information. Estimating the nature and degree of this spatial autocorrelation, which is usually positive and very strong, has been hindered by computational intensity associated with the massive number of pixels in realistically-sized remotely-sensed images, a situation that more recently has changed. Recent advances in spatial statistical estimation theory support the extraction of information and the distilling of knowledge from remotely-sensed images in a way that accounts for latent spatial autocorrelation. This paper summarizes an effective methodological approach to achieve this end, illustrating results with a 2002 remotely sensed-image of the Florida Everglades, and simulation experiments. Specifically, uncertainty of spatial autocorrelation parameter in a spatial autoregressive model is modeled with a beta-beta mixture approach and is further investigated with three different sampling strategies: coterminous sampling, random sub-region sampling, and increasing domain sub-regions. The results suggest that uncertainty associated with remotely-sensed data should be cast in consideration of spatial autocorrelation. It emphasizes that one remaining challenge is to better quantify the spatial variability of spatial autocorrelation estimates across geographic landscapes.
Monitoring autocorrelated process: A geometric Brownian motion process approach
Li, Lee Siaw; Djauhari, Maman A.
2013-09-01
Autocorrelated process control is common in today's modern industrial process control practice. The current practice of autocorrelated process control is to eliminate the autocorrelation by using an appropriate model such as Box-Jenkins models or other models and then to conduct process control operation based on the residuals. In this paper we show that many time series are governed by a geometric Brownian motion (GBM) process. Therefore, in this case, by using the properties of a GBM process, we only need an appropriate transformation and model the transformed data to come up with the condition needs in traditional process control. An industrial example of cocoa powder production process in a Malaysian company will be presented and discussed to illustrate the advantages of the GBM approach.
Autocorrelation in queuing network type production systems - revisited
Nielsen, Erland Hejn
Abstract When discussing flow-control matters with production managers , it is noteworthy that whereas there is normally great emphasis on the reduction of variance of specific transformation processes (quality control) as well as on level variability in general, as for instance represented by the...... Bullwhip effect, the possible disturbing interference, which potentially could arise due to autocorrelation (variability dependence over time) in otherwise level-stable demand streams of events in the production flows, does not seem to attract much attention, actually almost no attention at all. From the...... literature it is well known that the impact of certain types of autocorrelation in queuing systems (Livny, Melamed and Tsiolis, 1993) can lead to a fairly dramatic deterioration of the system performance compared to an event-independence case. Also, a study on the effect of autocorrelated demand in JIT...
Variance of size-age curves: Bootstrapping with autocorrelation
Bullock, S.H.; Turner, R.M.; Hastings, J.R.; Escoto-Rodriguez, M.; Lopez, Z.R.A.; Rodrigues-Navarro, J. L.
2004-01-01
We modify a method of estimating size-age relations from a minimal set of individual increment data, recognizing that growth depends not only on size but also varies greatly among individuals and is consistent within an individual for several to many time intervals. The method is exemplified with data from a long-lived desert plant and a range of autocorrelation factors encompassing field-measured values. The results suggest that age estimates based on size and growth rates with only moderate autocorrelation are subject to large variation, which raises major problems for prediction or hindcasting for ecological analysis or management.
Thirty-two phase sequences design with good autocorrelation properties
S P Singh; K Subba Rao
2010-02-01
Polyphase Barker Sequences are ﬁnite length, uniform complex sequences; the magnitude of their aperiodic autocorrelation sidelobes are bounded by 1. Such sequences have been used in numerous real-world applications such as channel estimation, radar and spread spectrum communication. In this paper, thirty-two phase Barker sequences up to length 24 with an alphabet size of only 32 are presented. The sequences from length 25 to 289 have autocorrelation properties better than well-known Frank codes. Because of the complex structure the sequences are very difﬁcult to detect and analyse by an enemy’s electronic support measures (ESMs). The synthesized sequences are promising for practical application to radar and spread spectrum communication systems. These sequences are found using the Modiﬁed Simulated Annealing Algorithm (MSAA). The convergence rate of the algorithm is good.
Biometric feature extraction using local fractal auto-correlation
Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)
New Approaches for Calculating Moran's Index of Spatial Autocorrelation
Chen, Yanguang
2016-01-01
Spatial autocorrelation plays an important role in geographical analysis, however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be...
Improved Branch-and-Bound for Low Autocorrelation Binary Sequences
Prestwich, S. D.
2013-01-01
The Low Autocorrelation Binary Sequence problem has applications in telecommunications, is of theoretical interest to physicists, and has inspired many optimisation researchers. Metaheuristics for the problem have progressed greatly in recent years but complete search has not progressed since a branch-and-bound method of 1996. In this paper we find four ways of improving branch-and-bound, leading to a tighter relaxation, faster convergence to optimality, and better empirical scalability.
Velocity Autocorrelation and Harmonic Motion in Supercooled Nondiffusing Monatomic Liquids
Chisolm, Eric D.; Clements, Brad E.; Wallace, Duane C.
2000-01-01
Studies of the many-body potential surface of liquid sodium have shown that it consists of a great many intersecting nearly harmonic valleys, a large fraction of which have the same frequency spectra. This suggests that a sufficiently supercooled state of this system, remaining in a single valley, would execute nearly harmonic motion. To test this hypothesis, we have compared $\\hat{Z}(t)$, the normalized velocity autocorrelation function, calculated from MD simulations to that predicted under...
A Statistical Approach to Autocorrelation Detection of Low Frequency Earthquakes
Aguiar, A. C.; Beroza, G. C.
2012-12-01
We have analyzed tremor data during the April, 2006 tremor episode in the Nankai Trough in SW Japan using the auto-correlation approach of Brown et al. (2008), which detects low frequency earthquakes (LFEs) based on pair-wise matching. We have found that the statistical behavior of the autocorrelations of each station is different and for this reason we have based our LFE detection method on the autocorrelation of each station individually. Analyzing one station at a time assures that the detection threshold will only depend on the station being analyzed. Once detections are found on each station individually, using a low detection threshold based on a Gaussian distribution of the correlation coefficients, the results are compared within stations and declared a detection if they are found in a statistically significant number of the stations, following multinomial statistics. We have compared our detections using the single station method to the detections found by Shelly et al. (2007) for the 2006 April 16 events and find a significant number of similar detections as well as many new detections that were not found using templates from known LFEs. We are working towards developing a sound statistical basis for event detection. This approach should improve our ability to detect LFEs within weak tremor signals where they are not already identified, and should be applicable to earthquake swarms and sequences in general.
Auto-correlation analysis of ocean surface wind vectors
Abhijit Sarkar; Sujit Basu; A K Varma; Jignesh Kshatriya
2002-09-01
The nature of the inherent temporal variability of surface winds is analyzed by comparison of winds obtained through different measurement methods. In this work, an auto-correlation analysis of a time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time series data available for 240 hours in the month of May, 1999 were subjected to an auto-correlation analysis. The analysis indicates an exponential fall of the auto- correlation in the first few hours with a decorrelation time scale of about 6 hours. For a meaningful comparison between satellite derived products and in situ data, satellite data acquired at different time intervals should be used with appropriate `weights', rather than treating the data as concurrent in time. This paper presents a scheme for temporal weighting using the auto-correlation analysis. These temporal `weights' can potentially improve the root mean square (rms) deviation between satellite and in situ measurements. A case study using the TRMM Microwave Imager (TMI) and Indian Ocean buoy wind speed data resulted in an improvement of about 10%.
Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection.
Chevin, Luis-Miguel; Visser, Marcel E; Tufto, Jarle
2015-09-01
Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of phenotypic selection, which is a major determinant of eco-evolutionary dynamics in changing environments. We introduce a new method for measuring variable phenotypic selection using random regression. We rely on model selection to assess the support for stabilizing selection, and for a moving optimum that may include a trend plus (possibly autocorrelated) fluctuations. The environmental sensitivity of selection also can be estimated by including an environmental covariate. After testing our method on extensive simulations, we apply it to breeding time in a great tit population in the Netherlands. Our analysis finds support for an optimum that is well predicted by spring temperature, and occurs about 33 days before a peak in food biomass, consistent with what is known from the biology of this species. We also detect autocorrelated fluctuations in the optimum, beyond those caused by temperature and the food peak. Because our approach directly estimates parameters that appear in theoretical models, it should be particularly useful for predicting eco-evolutionary responses to environmental change. PMID:26227394
Auto-correlation Properties of Scattering Light in Ultrasound-modulated Random Media
ZHANG Xiqin; XING Da; LIU Ying; MA Shining
2001-01-01
In this paper, the auto-correlation properties of scattering light in random media modulated by ultrasound were studied. The expression of temporal auto-correlation function of scattering light amplitude in the ultrasound-modulated media was presented. The results show that the auto-correlation function is modulated as the ultrasound is introduced into the media and the modulation amplitude decays with correlation time. The influences of ultrasound amplitude, Brownian diffusion coefficient, scattering and absorption coefficients on auto-correlation function were discussed. The auto-correlation imaging of an object hidden in random media was also studied by the use of Monte Carlo simulations.
Distributions of Autocorrelated First-Order Kinetic Outcomes: Illness Severity.
James D Englehardt
Full Text Available Many complex systems produce outcomes having recurring, power law-like distributions over wide ranges. However, the form necessarily breaks down at extremes, whereas the Weibull distribution has been demonstrated over the full observed range. Here the Weibull distribution is derived as the asymptotic distribution of generalized first-order kinetic processes, with convergence driven by autocorrelation, and entropy maximization subject to finite positive mean, of the incremental compounding rates. Process increments represent multiplicative causes. In particular, illness severities are modeled as such, occurring in proportion to products of, e.g., chronic toxicant fractions passed by organs along a pathway, or rates of interacting oncogenic mutations. The Weibull form is also argued theoretically and by simulation to be robust to the onset of saturation kinetics. The Weibull exponential parameter is shown to indicate the number and widths of the first-order compounding increments, the extent of rate autocorrelation, and the degree to which process increments are distributed exponential. In contrast with the Gaussian result in linear independent systems, the form is driven not by independence and multiplicity of process increments, but by increment autocorrelation and entropy. In some physical systems the form may be attracting, due to multiplicative evolution of outcome magnitudes towards extreme values potentially much larger and smaller than control mechanisms can contain. The Weibull distribution is demonstrated in preference to the lognormal and Pareto I for illness severities versus (a toxicokinetic models, (b biologically-based network models, (c scholastic and psychological test score data for children with prenatal mercury exposure, and (d time-to-tumor data of the ED01 study.
Distributions of Autocorrelated First-Order Kinetic Outcomes: Illness Severity
Englehardt, James D.
2015-01-01
Many complex systems produce outcomes having recurring, power law-like distributions over wide ranges. However, the form necessarily breaks down at extremes, whereas the Weibull distribution has been demonstrated over the full observed range. Here the Weibull distribution is derived as the asymptotic distribution of generalized first-order kinetic processes, with convergence driven by autocorrelation, and entropy maximization subject to finite positive mean, of the incremental compounding rates. Process increments represent multiplicative causes. In particular, illness severities are modeled as such, occurring in proportion to products of, e.g., chronic toxicant fractions passed by organs along a pathway, or rates of interacting oncogenic mutations. The Weibull form is also argued theoretically and by simulation to be robust to the onset of saturation kinetics. The Weibull exponential parameter is shown to indicate the number and widths of the first-order compounding increments, the extent of rate autocorrelation, and the degree to which process increments are distributed exponential. In contrast with the Gaussian result in linear independent systems, the form is driven not by independence and multiplicity of process increments, but by increment autocorrelation and entropy. In some physical systems the form may be attracting, due to multiplicative evolution of outcome magnitudes towards extreme values potentially much larger and smaller than control mechanisms can contain. The Weibull distribution is demonstrated in preference to the lognormal and Pareto I for illness severities versus (a) toxicokinetic models, (b) biologically-based network models, (c) scholastic and psychological test score data for children with prenatal mercury exposure, and (d) time-to-tumor data of the ED01 study. PMID:26061263
Spectral velocity estimation using autocorrelation functions for sparse data sets
2006-01-01
The distribution of velocities of blood or tissue is displayed using ultrasound scanners by finding the power spectrum of the received signal. This is currently done by making a Fourier transform of the received signal and then showing spectra in an M-mode display. It is desired to show a B......-mode image for orientation, and data for this has to acquired interleaved with the flow data. The power spectrum can be calculated from the Fourier transform of the autocorrelation function Ry (k), where its span of lags k is given by the number of emission N in the data segment for velocity estimation. The...... lag corresponds to the difference in pulse number, so that for lag k data from emission i is correlated with i + k. The autocorrelation for lag k can be averaged over N-k pairs of emissions. It is possible to calculate Ry (k) for a sparse set of emissions, as long as all combinations of emissions...
Complex singularities of the fluid velocity autocorrelation function
Chtchelkatchev, N. M.; Ryltsev, R. E.
2015-11-01
There are intensive debates regarding the nature of supercritical fluids: if their evolution from liquid-like to gas-like behavior is a continuous multistage process or there is a sharp well-defined crossover. Velocity auto-correlation function Z is the established detector of evolution of fluid particles dynamics. Usually, complex singularities of correlation functions give more information. For this reason, we investigate Z in complex plane of frequencies using numerical analytic continuation. We have found that naive picture with few isolated poles fails describing Z(ω) of one-component Lennard-Jones (LJ) fluid. Instead, we see the singularity manifold forming branch cuts extending approximately parallel to the real frequency axis. That suggests LJ velocity autocorrelation function is a multivalued function of complex frequency. The branch cuts are separated from the real axis by the well-defined "gap" whose width corresponds to an important time scale of a fluid characterizing crossover of system dynamics from kinetic to hydrodynamic regime. Our working hypothesis is that the branch cut origin is related to competition between one-particle dynamics and hydrodynamics. The observed analytic structure of Z is very stable under changes in the temperature; it survives at temperatures two orders of magnitude higher than the critical one.
Spatial autocorrelation approaches to testing residuals from least squares regression
Chen, Yanguang
2015-01-01
In statistics, the Durbin-Watson test is always employed to detect the presence of serial correlation of residuals from a least squares regression analysis. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the Durbin-Watson will be ineffectual because the value of Durbin-Watson's statistic depends on the sequences of data point arrangement. Based on the ideas from spatial autocorrelation, this paper presents two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then on the analogy of the Durbin-Watson statistic, a serial correlation index is constructed. As a case, the two statistics are applied to the spatial sample of 29 China's regions. These results show th...
Impact of Autocorrelation on Principal Components and Their Use in Statistical Process Control
Vanhatalo, Erik; Kulahci, Murat
2015-01-01
well understood nor properly documented. This article illustrates through simulations the impact of autocorrelation on the descriptive ability of PCA and on the monitoring performance using PCA-based SPC when autocorrelation is ignored. In the simulations, cross-correlated and autocorrelated data are...... generated using a stationary first-order vector autoregressive model. The results show that the descriptive ability of PCA may be seriously affected by autocorrelation causing a need to incorporate additional principal components to maintain the model's explanatory ability. When all variables have equal...... coefficients in a diagonal autoregressive coefficient matrix, the descriptive ability is intact, while a significant impact occurs when the variables have different degrees of autocorrelation. We also illustrate that autocorrelation may impact PCA-based SPC and cause lower false alarm rates and delayed shift...
Auto-correlation Function Study of Scattered Light Intensity
Sun, Y
2005-01-01
In this work, the particle size distribution measured using the dynamic light scattering (DLS) technique is compared with that obtained from the static light scattering (SLS) technique or provided by the supplier measured using the Transmission Electron Microscopy (TEM) technique for dilute Poly($N$-isopropylacrylamide) microgel and standard polystyrene latex samples in dispersion respectively. The results show that the narrow particle size distribution that can be measured accurately using the SLS technique is not suited to the determination by the DLS technique and the particle size distribution obtained from the DLS technique is different from the value provided by the supplier. With the assistance of the simulated data of the normalized time auto-correlation function of the scattered light intensity $g^{(2)}(\\tau)$, the effects of the particle size distribution on the nonexponentiality of $g^{(2)}(\\tau)$ measured at a scattering angle of 30$^\\mathrm o$ are investigated. The analysis reveals that the influ...
Receiver structure from teleseisms: Autocorrelation and cross correlation
Sun, Weijia; Kennett, B. L. N.
2016-06-01
We present a way of characterizing the structure beneath a seismic station, by exploiting stacked correlograms of three-component records from teleseismic events. This seismic daylight imaging approach exploits the extraction of reflection and conversion information from teleseismic coda via tensor autocorrelation. The approach is illustrated for a number of Australian stations in a variety of tectonic environments using hundreds of teleseismic events, to extract P and S reflectivity and converted Ps and Sp information. The results show a very good agreement with prior knowledge across Australia. Compared with the classical receiver function, the broader-frequency band of 0.5-4.0 Hz provides additional information on finer-scale structure.
Generalised partial autocorrelations and the mutual information between past and future
Proietti, Tommaso; Luati, Alessandra
generalized partial autocorrelations as the partial autocorrelation coefficients of an auxiliary process, we derive their properties and relate them to essential features of the original process. Based on a parameterisation suggested by Barndorff-Nielsen and Schou (1973) and on Whittle likelihood, we develop...
MATLAB-Based Program for Teaching Autocorrelation Function and Noise Concepts
Jovanovic Dolecek, G.
2012-01-01
An attractive MATLAB-based tool for teaching the basics of autocorrelation function and noise concepts is presented in this paper. This tool enhances traditional in-classroom lecturing. The demonstrations of the tool described here highlight the description of the autocorrelation function (ACF) in a general case for wide-sense stationary (WSS)…
Geographic autocorrelation analysis of the lung cancer mortality in Uruguay
Objective: To analyze the geographical distribution of mortality from lung cancer in Uruguay, using spatial autocorrelation indicators, in order to identify regions of high and low risk in the period 1989-2008. Methodology: 1989-2008 interval was analyzed by grouping the data in the following periods: 1989-1991,1992-1994,1995-1997,1998-2000,2001-2003 and 2004-2008. As indicator risk S MR (Standardized Mortality Ratio) was used, with reference to the country as a entirety. The analysis was performed by calculating the index I and correlation plots space (both methods according Mo ran) for each period and the corresponding maps. The significance was determined by permutations, considering level 0.05 significance. Results: The results of the correlation coefficients for different periods were, in Men: 1989 -1991 (R = 0.29, p <0.05), 1992 -1994 (I = 0.11, N S), 1995 -1997 (R = 0.31, p <0.05); 1998 - 2000 (R = 0.24, p <0.05); 2000 - 2003 (R = 0.19, p <0.05); 2004 -2008 (R = 0.24, N S). In women: 1989 -1991 (R = -0.18, N S), 1992 -1994 (R = -0.16, N S), 1995-1997 (I = 0.18, N S); 1998 - 2000 (R = 0.06, N S); 2001-2003 (R = -0.16, N S), 2004 -2008 (I = 0.02, N S), 1989-2003 (R = -0.03, N S). Men in those departments where they met more risks Artigas were low (SM R = 0.52; 0.57; 0.61; 0.61; 0.60; 0.69), Salto (SM R = 0.52; 0.57; 0.58; 0.68; 0.76; 0.75), Black River (SM R = 0.69; 0.73; 0.76; 0.93; 0.73; 1.29) and Paysandu (SMR = 0.87; 0.85; 0.96; 0.79; 0.89; 0.92) in the respective periods. In women the 0.55; 0.78) Also, in the respective periods. Given the low number of cases in women the period 1989-2003 was also considered together to obtain one SMR Black River = 0.63 and jumped SMR = 0.68. Conclusions: In men, the existence of spatial autocorrelation was identified statistically significant, with stable results in the last 2 decades analyzed. This was not observed in women. The results found in males suggest the existence a region of lower mortality from lung cancer
An Autocorrelative Approach for EMG Time-Frequency Analysis
Mohannad K. Sabir
2013-01-01
Full Text Available As they are the smallest functional parts of the muscle, motor units (MUs are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detected signals with various degrees of automation. This paper investigates the application of autocorrelation function (ACF method to decompose EMG signals to their frequency components. It was found that using the proposed method gives a quite good frequency resolution as compared to that resulting from using short time fast Fourier transform (STFFT; thus more MUs can be distinguished.
Palm Tree Detection Using Circular Autocorrelation of Polar Shape Matrix
Manandhar, A.; Hoegner, L.; Stilla, U.
2016-06-01
Palm trees play an important role as they are widely used in a variety of products including oil and bio-fuel. Increasing demand and growing cultivation have created a necessity in planned farming and the monitoring different aspects like inventory keeping, health, size etc. The large cultivation regions of palm trees motivate the use of remote sensing to produce such data. This study proposes an object detection methodology on the aerial images, using shape feature for detecting and counting palm trees, which can support an inventory. The study uses circular autocorrelation of the polar shape matrix representation of an image, as the shape feature, and the linear support vector machine to standardize and reduce dimensions of the feature. Finally, the study uses local maximum detection algorithm on the spatial distribution of standardized feature to detect palm trees. The method was applied to 8 images chosen from different tough scenarios and it performed on average with an accuracy of 84% and 76.1%, despite being subjected to different challenging conditions in the chosen test images.
Auto-correlation analysis of wave heights in the Bay of Bengal
Abhijit Sarkar; Jignesh Kshatriya; K Satheesan
2006-04-01
Time series observations of signiﬁcant wave heights in the Bay of Bengal were subjected to auto-correlation analysis to determine temporal variability scale.The analysis indicates an exponential fall of auto-correlation in the ﬁrst few hours with a decorrelation time scale of about six hours.A similar ﬁgure was found earlier for ocean surface winds.The nature of variation of auto-correlation with time lags was also found to be similar for winds and wave heights.
Adaptive endpoint detection of seismic signal based on auto-correlated function
Based on the analysis of auto-correlation function, the notion of the distance between auto-correlation function was quoted, and the characterization of the noise and the signal with noise were discussed by using the distance. Then, the method of auto- adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low signal with noise ratio circumstance
Influence of laser pulse on the autocorrelation function of H in a strong electric field
Lifei Wang; Guangcan Yang
2009-01-01
The autocorrelation function of electronic wave packet of hydrogen atom in a strong electric field below the zero-field ionization threshold is investigated in the formalism of semiclassical theory. It is found that the autocorrelation depends on the applied laser pulse significantly. In the case of narrow laser pulse, the reviving peaks in the autocorrelation can be attributed to the closed orbits of electrons, which are related to the classical dynamics of the system. But this correspondence is wiped out with increasing the laser width because of the interference among the adjacent reviving peaks.
Spatial Autocorrelation of Cancer Incidence in Saudi Arabia
Khalid Al-Ahmadi
2013-12-01
Full Text Available Little is known about the geographic distribution of common cancers in Saudi Arabia. We explored the spatial incidence patterns of common cancers in Saudi Arabia using spatial autocorrelation analyses, employing the global Moran’s I and Anselin’s local Moran’s I statistics to detect nonrandom incidence patterns. Global ordinary least squares (OLS regression and local geographically-weighted regression (GWR were applied to examine the spatial correlation of cancer incidences at the city level. Population-based records of cancers diagnosed between 1998 and 2004 were used. Male lung cancer and female breast cancer exhibited positive statistically significant global Moran’s I index values, indicating a tendency toward clustering. The Anselin’s local Moran’s I analyses revealed small significant clusters of lung cancer, prostate cancer and Hodgkin’s disease among males in the Eastern region and significant clusters of thyroid cancers in females in the Eastern and Riyadh regions. Additionally, both regression methods found significant associations among various cancers. For example, OLS and GWR revealed significant spatial associations among NHL, leukemia and Hodgkin’s disease (r² = 0.49–0.67 using OLS and r² = 0.52–0.68 using GWR and between breast and prostate cancer (r² = 0.53 OLS and 0.57 GWR in Saudi Arabian cities. These findings may help to generate etiologic hypotheses of cancer causation and identify spatial anomalies in cancer incidence in Saudi Arabia. Our findings should stimulate further research on the possible causes underlying these clusters and associations.
Autocorrelation analysis of plasma plume oscillations in deep penetration laser welding
Mrňa, Libor; Šarbort, Martin; Řeřucha, Jan
Munich: WLT, 2015. s. 75. [LiM 2015. Lasers in Manufacturing Conference. 22.06.2015-25.06.2015, Munich] Institutional support: RVO:68081731 Keywords : autocorrelation analysis * laser welding Subject RIV: BH - Optics, Masers, Lasers
Calculation of the Autocorrelation Function of the Stochastic Single Machine Infinite Bus System
Ghanavati, Goodarz; Lakoba, Taras; Cotilla-Sanchez, Eduardo
2013-01-01
Critical slowing down (CSD) is the phenomenon in which a system recovers more slowly from small perturbations. CSD, as evidenced by increasing signal variance and autocorrelation, has been observed in many dynamical systems approaching a critical transition, and thus can be a useful signal of proximity to transition. In this paper, we derive autocorrelation functions for the state variables of a stochastic single machine infinite bus system (SMIB). The results show that both autocorrelation and variance increase as this system approaches a saddle-node bifurcation. The autocorrelation functions help to explain why CSD can be used as an indicator of proximity to criticality in power systems revealing, for example, how nonlinearity in the SMIB system causes these signs to appear.
A broadly tunable autocorrelator for ultra-short, ultra-high power infrared optical pulses
Szarmes, E.B.; Madey, J.M.J. [Duke Univ., Durham, NC (United States)
1995-12-31
We describe the design of a crossed-beam, optical autocorrelator that uses an uncoated, birefringent beamsplitter to split a linearly polarized incident pulse into two orthogonally polarized pulses, and a Type II, SHG crystal to generate the intensity autocorrelation function. The uncoated beamsplitter accommodates extremely broad tunability while precluding any temporal distortion of ultrashort optical pulses at the dielectric interface, and the specific design provides efficient operation between 1 {mu}m and 4 {mu}m. Furthermore, the use of Type II SHG completely eliminates any single-beam doubling, so the autocorrelator can be operated at very shallow crossed-beam angles without generating a background pedestal. The autocorrelator has been constructed and installed in the Mark III laboratory at Duke University as a broadband diagnostic for ongoing compression experiments on the chirped-pulse FEL.
Spectra of empirical autocorrelation matrices: A random-matrix-theory-inspired perspective
Jamali, Tayeb; Jafari, G. R.
2015-07-01
We construct an autocorrelation matrix of a time series and analyze it based on the random-matrix theory (RMT) approach. The autocorrelation matrix is capable of extracting information which is not easily accessible by the direct analysis of the autocorrelation function. In order to provide a precise conclusion based on the information extracted from the autocorrelation matrix, the results must be first evaluated. In other words they need to be compared with some sort of criterion to provide a basis for the most suitable and applicable conclusions. In the context of the present study, the criterion is selected to be the well-known fractional Gaussian noise (fGn). We illustrate the applicability of our method in the context of stock markets. For the former, despite the non-Gaussianity in returns of the stock markets, a remarkable agreement with the fGn is achieved.
G. Carl
2008-04-01
Full Text Available Species distributional data based on lattice data often display spatial autocorrelation. In such cases, the assumption of independently and identically distributed errors can be violated in standard regression models. Based on a recently published review on methods to account for spatial autocorrelation, we describe here a new statistical approach which relies on the theory of wavelets. It provides a powerful tool for removing spatial autocorrelation without any prior knowledge of the underlying correlation structure. Our wavelet-revised model (WRM is applied to artificial datasets of species’ distributions, for both presence/absence (binary response and species abundance data (Poisson or normally distributed response. Making use of these published data enables us to compare WRM to other recently tested models and to recommend it as an attractive option for effective and computationally efficient autocorrelation removal.
Application of autocorrelation method on ionospheric short-term forecasting in China
LIU Ruiyuan; LIU Shunlin; XU Zhonghua; WU Jian; WANG Xianyi; ZHANG Beichen; HU Hongqiao
2006-01-01
Adopting the autocorrelation method in the ionospheric short-term forecasting, we put forward a simple and practical forecasting method―the sectional autocorrelation method, that is, for predictions of one hour to four hours ahead the autocorrelation coefficient of RDF with the "iteration" method is selected, for prediction of more than four hours ahead, the autocorrelation coefficient of f0F2 with the "at once" method is used. The prediction precisions have been quantitatively estimated based on the data from Chongqing and Guangzhou Ionosonde Stations. It is shown that the method is much improved for the predictions of one hour to four hours ahead. For the predictions of more than four hours ahead the prediction error reaches a saturation value, which is still lower than that of the "median" method. This new method could also be applied to the short-term forecasting of other ionospheric parameters.
Sun, Guanghao; Matsui, Takemi
2015-08-01
Noncontact measurement of respiratory rate using Doppler radar will play a vital role in future clinical practice. Doppler radar remotely monitors the tiny chest wall movements induced by respiration activity. The most competitive advantage of this technique is to allow users fully unconstrained with no biological electrode attachments. However, the Doppler radar, unlike other contact-type sensors, is easily affected by the random body movements. In this paper, we proposed a time domain autocorrelation model to process the radar signals for rapid and stable estimation of the respiratory rate. We tested the autocorrelation model on 8 subjects in laboratory, and compared the respiratory rates detected by noncontact radar with reference contact-type respiratory effort belt. Autocorrelation model showed the effects of reducing the random body movement noise added to Doppler radar's respiration signals. Moreover, the respiratory rate can be rapidly calculated from the first main peak in the autocorrelation waveform within 10 s. PMID:26737655
An algorithm to solve autocorrelation matrix singular value based on SNR estimation
赵继军; 张曙光; 赵文玉
2009-01-01
SNR estimation of communication signals is important to improve demodulation performance and channel quality of communication system,thus it is an important research issue of communication field.According to the core problem of autocorrelation matrix singular value in SNR estimation process,through making use of householder transforming autocorrelation matrix into tridiagonal matrix,and by using the relation of corresponding characteristic equation coefficients and singular value,a numerical algorithm is gi...
Yibo Liu; Xianjin Huang; Xiaofeng Zhao
2012-01-01
A spatial autocorrelation analysis method is adopted to process the spatial dynamic change of industrial Chemical Oxygen Demand (COD) discharge in China over the past 15 years. Studies show that amount and intensity of industrial COD discharges are on a decrease, and the tendency is more remarkable for discharge intensity. There are large differences between inter-provincial discharge amount and intensity, and with different spatial differentiation features. Global spatial autocorrelation ana...
On the Potential of the Excluded Volume and Auto-Correlation as Neuromorphometric Descriptors
Costa, L. da F.; Barbosa, M S; Coupez, V.
2005-01-01
This work investigates at what degree two neuromorphometric measurements, namely the autocorrelation and the excluded volume of a neuronal cell can influence the characterization and classification of such a type of cells. While the autocorrelation function presents good potential for quantifying the dendrite-dendrite connectivity of cells in mosaic tilings, the excluded volume, i.e. the amount of the surround space which is geometrically not accessible to an axon or dendrite, provides a comp...
Kirichenko, N.F.; Kutsenko, A.A.; Lepekha, P.P. [Kiev State Univ. (Ukraine)
1994-06-05
New results and algorithms are obtained for classifting characteristics of planar representations by the method of autocorrelation functions. Theorems are proven on the geometric content of an arbitrary autocorrelation function for various surfaces of planar representations. New algorithms are proposed for normalizing representations and for computing characteristics which are invariant relative to the transfortnation groups of a plane-parallel translation, rotation, and change of scale. 2 refs., 4 figs.
Vercken, Elodie; Fauvergue, Xavier; Ris, Nicolas; Crochard, Didier; Mailleret, Ludovic
2015-07-01
Environmental variation is classically expected to affect negatively population growth and to increase extinction risk, and it has been identified as a major determinant of establishment failures in the field. Yet, recent theoretical investigations have shown that the structure of environmental variation and more precisely the presence of positive temporal autocorrelation might alter this prediction. This is particularly likely to affect the establishment dynamics of biological control agents in the field, as host-parasitoid interactions are expected to induce temporal autocorrelation in host abundance. In the case where parasitoid populations display overcompensatory dynamics, the presence of such positive temporal autocorrelation should increase their establishment success in a variable environment. We tested this prediction in laboratory microcosms by introducing parasitoids to hosts whose abundances were manipulated to simulate uncorrelated or positively autocorrelated variations in carrying capacity. We found that environmental variability decreased population size and increased parasitoid population variance, which is classically expected to extinction risk. However, although exposed to significant environmental variation, we found that parasitoid populations experiencing positive temporal autocorrelation in host abundance were more likely to persist than populations exposed to uncorrelated variation. These results confirm that environmental variation is a key determinant of extinction dynamics that can have counterintuitive effects depending on its autocorrelation structure. PMID:26257880
LIU Zhong-gang; LI Man-chun; SUN Yan; MA Wen-bo
2006-01-01
This paper uses a spatial statistics method based on the calculation of spatial autocorrelation as a possible approach for modeling and quantifying the distribution of urban land price in Changzhou City, Jiangsu Province.GIS and spatial statistics provide a useful way for describing the distribution of urban land price both spatially and temporally, and have proved to be useful for understanding land price distribution pattern better. In this paper, we apply the statistical analysis method to 8379 urban land price samples collected from Changzhou Land Market, and it is turned out that the proposed approach can effectively identify the spatial clusters and local point patterns in dataset and forms a general method for conceptualizing the land price structure. The results show that land price structure in Changzhou City is very complex and that even where there is a high spatial autocorrelation, the land price is still relatively heterogeneous. Furthermore, lands for different uses have different degrees of spatial autocorrelation. Spatial autocorrelation of commercial lands is more intense than that of residential and industrial lands in regional central district. This means that treating land price as integration of homogeneous units can limit analysis of pattern, over-simplifying the structure of land price, but the methods, just as the autocorrelation approaches, are useful tools for quantifying the variables of land price.
Lorant, V; Thomas, I; Deliège, D; Tonglet, R
2001-12-01
This paper aims at investigating whether the relationship between mortality and socio-economic deprivation is affected by the spatial autocorrelation of ecological data. A simple model is used in which mortality (all-ages and premature) is the dependent variable, and deprivation, morbidity and other socio-economic indicators are the explanatory variables. Deprivation is measured by the Townsend index; the other socio-economic variables are the median income, unequal income distribution (Gini coefficient) and population density. Morbidity is estimated on the basis of hospital admission rates and overweight prevalence. Spatial autocorrelation is measured by the Moran's I coefficient. All mortality and morbidity variables have significant, positive, and moderate-to-high spatial autocorrelation. Two multivariate models are explored: a weighted least-squares model ignoring spatial autocorrelation and a simultaneous autoregressive model. The paper concludes that spatial autocorrelation has a significant impact on the relationship between mortality and socio-economic variables. Future ecological models intended to inform health resources allocation need to pay greater attention to the spatial dimension of the data used. PMID:11762895
Adaptive endpoint detection of seismic signal based on auto-correlated function
There are certain shortcomings for the endpoint detection by time-waveform envelope and/or by checking the travel table (both labelled as the artificial detection method). Based on the analysis of the auto-correlation function, the notion of the distance between auto-correlation functions was quoted, and the characterizations of the noise and the signal with noise were discussed by using the distance. Then, the method of auto-adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low SNR circumstance
Nanoscale and femtosecond optical autocorrelator based on a single plasmonic nanostructure
We demonstrated a nanoscale size, ultrafast and multiorder optical autocorrelator with a single plasmonic nanostructure for measuring the spatio-temporal dynamics of femtosecond laser light. As a nanostructure, we use a split hole resonator (SHR), which was made in an aluminium nanofilm. The Al material yields the fastest response time (100 as). The SHR nanostructure ensures a high nonlinear optical efficiency of the interaction with laser radiation, which leads to (1) the second, (2) the third harmonics generation and (3) the multiphoton luminescence, which, in turn, are used to perform multi-order autocorrelation measurements. The nano-sized SHR makes it possible to conduct autocorrelation measurements (i) with a subwavelength spatial resolution and (ii) with no significant influence on the duration of the laser pulse. The time response realized by the SHR nanostructure is about 10 fs. (letter)
Construction of SDE-based wind speed models with exponential autocorrelation
Miñano, Rafael Zárate
2015-01-01
This paper provides a systematic method to build wind speed models based on stochastic differential equations (SDEs). The resulting models produce stochastic processes with a given probability distribution and exponential decaying autocorrelation function. The only information needed to build the models is the probability density function of the wind speed and its autocorrelation coefficient. Unlike other methods previously proposed in the literature, the proposed method leads to models able to reproduce an exact exponential autocorrelation even if the probability distribution is not Gaussian. A sufficient condition for the property above is provided. The paper includes the explicit formulation of SDE-based wind speed models obtained from several probability distributions used in the literature to describe different wind speed behaviors.
Deblauwe, Vincent; Kennel, Pol; Couteron, Pierre
2012-01-01
Background Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. Methodology/Principal Findings The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. Conclusions/Significance The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for
Spectral Velocity Estimation using the Autocorrelation Function and Sparse data Sequences
Jensen, Jørgen Arendt
both the B-mode frame rate, and at the same time have the highest possible $f_{prf}$ only limited by the depth of investigation, are, thus, of great interest. The power spectrum can be calculated from the Fourier transform of the autocorrelation function $R_r(k)$. The lag $k$ corresponds to the......, be used for estimating $R_r(k)$. The approach has been investigated using Field II simulation of the flow in the carotid and femoral arteries. A 5 MHz linear array transducer with 128 elements, a pitch of $\\lambda$ and an element height of 5 mm was simulated. The autocorrelation was calculated from...
A Comparison of Decision Methods for C _{pk} When Data are Autocorrelated
Lundkvist, Peder; Vannman, Kerstin; Kulahci, Murat
2012-01-01
In many industrial applications, autocorrelated data are becoming increasingly common due to, for example, on-line data collection systems with high-frequency sampling. Therefore, the basic assumption of independent observations for process capability analysis is not valid. The purpose of this...... article is to compare decision methods using the process capability index C-pk when data are autocorrelated. This is done through a case study followed by a simulation study. In the simulation study the actual significance level and power of the decision methods are investigated. The outcome of the...
van Mantgem, P.J.; Schwilk, D.W.
2009-01-01
Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.
Evaluating multi-exposure speckle imaging estimates of absolute autocorrelation times.
Kazmi, S M Shams; Wu, Rebecca K; Dunn, Andrew K
2015-08-01
Multi-exposure speckle imaging (MESI) is a camera-based flow-imaging technique for quantitative blood-flow monitoring by mapping the speckle-contrast dependence on camera exposure duration. The ability of laser speckle contrast imaging to measure the temporal dynamics of backscattered and interfering coherent fields, in terms of the accuracy of autocorrelation measurements, is a major unresolved issue in quantitative speckle flowmetry. MESI fits for a number of parameters including an estimate of the electric field autocorrelation decay time from the imaged speckles. We compare the MESI-determined correlation times in vitro and in vivo with accepted true values from direct temporal measurements acquired with a photon-counting photon-multiplier tube and an autocorrelator board. The correlation times estimated by MESI in vivo remain on average within 14±11% of those obtained from direct temporal autocorrelation measurements, demonstrating that MESI yields highly comparable statistics of the time-varying fields that can be useful for applications seeking not only quantitative blood flow dynamics but also absolute perfusion. PMID:26258378
Li, Chuan; Liang, Ming; Zhang, Yi; Hou, Shumin
2012-08-01
Fault features of rolling element bearings can be reflected by geometrical structures of the bearing vibration signals. These symptoms, however, often spread over various morphological scales without a known pattern. For this reason, we propose a multi-scale autocorrelation via morphological wavelet slices (MAMWS) approach to detect bearing fault signatures. The vibration measurement of a bearing is decomposed using morphological stationary wavelet with different resolutions of structuring elements. The extracted temporal components are then transformed to form a frequency-domain view of morphological slices by the Fourier transform. Although this three-dimensional representation is more intuitive in terms of fault diagnosis, the existence of the noise may reduce its readability. Hence the autocorrelation function is exploited to produce a multi-scale autocorrelation spectrogram from which the maximal autocorrelation values of all frequencies are aggregated into an ichnographical spectral representation. Accordingly the fault signature is highlighted for easy diagnosis of bearing faults. The effectiveness of the proposed approach has been demonstrated by both the simulation and experimental signal analyses.
Velocity-Autocorrelation Function in Liquids, Deduced from Neutron Incoherent Scattering Results
Carneiro, Kim
1976-01-01
The Fourier transform p(ω) of the velocity-autocorrelation function is derived from neutron incoherent scattering results, obtained from the two liquids Ar and H2. The quality and significance of the results are discussed with special emphasis on the long-time t-3/2 tail, found in computer...
Crude oil market efficiency and modeling. Insights from the multiscaling autocorrelation pattern
Empirical research on market inefficiencies focuses on the detection of autocorrelations in price time series. In the case of crude oil markets, statistical support is claimed for weak efficiency over a wide range of time-scales. However, the results are still controversial since theoretical arguments point to deviations from efficiency as prices tend to revert towards an equilibrium path. This paper studies the efficiency of crude oil markets by using lagged detrended fluctuation analysis (DFA) to detect delay effects in price autocorrelations quantified in terms of a multiscaling Hurst exponent (i.e., autocorrelations are dependent of the time scale). Results based on spot price data for the period 1986-2009 indicate important deviations from efficiency associated to lagged autocorrelations, so imposing the random walk for crude oil prices has pronounced costs for forecasting. Evidences in favor of price reversion to a continuously evolving mean underscores the importance of adequately incorporating delay effects and multiscaling behavior in the modeling of crude oil price dynamics. (author)
Exponential decay rate of partial autocorrelation coefficients of ARMA and short-memory processes
Takemura, Akimichi
2015-01-01
We present a short proof of the fact that the exponential decay rate of partial autocorrelation coefficients of a short-memory process, in particular an ARMA process, is equal to the exponential decay rate of the coefficients of its infinite autoregressive representation.
Wen Dong; Kun Yang; Quan-Li Xu; Yu-Lian Yang
2015-01-01
This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression anal...
Phase II monitoring of auto-correlated linear profiles using linear mixed model
Narvand, A.; Soleimani, P.; Raissi, Sadigh
2013-05-01
In many circumstances, the quality of a process or product is best characterized by a given mathematical function between a response variable and one or more explanatory variables that is typically referred to as profile. There are some investigations to monitor auto-correlated linear and nonlinear profiles in recent years. In the present paper, we use the linear mixed models to account autocorrelation within observations which is gathered on phase II of the monitoring process. We undertake that the structure of correlated linear profiles simultaneously has both random and fixed effects. The work enhanced a Hotelling's T 2 statistic, a multivariate exponential weighted moving average (MEWMA), and a multivariate cumulative sum (MCUSUM) control charts to monitor process. We also compared their performances, in terms of average run length criterion, and designated that the proposed control charts schemes could effectively act in detecting shifts in process parameters. Finally, the results are applied on a real case study in an agricultural field.
Improved preservation of autocorrelative structure in surrogate data using an initial wavelet step
C. J. Keylock
2008-06-01
Full Text Available Surrogate data generation algorithms are useful for hypothesis testing or for generating realisations of a process for data extension or modelling purposes. This paper tests a well known surrogate data generation method against a stochastic and also a hybrid wavelet-Fourier transform variant of the original algorithm. The data used for testing vary in their persistence and intermittency, and include synthetic and actual data. The hybrid wavelet-Fourier algorithm outperforms the others in its ability to match the autocorrelation function of the data, although the advantages decrease for high intermittencies and when attention is only directed towards the early part of the autocorrelation function. The improved performance is attributed to the wavelet step of the algorithm.
Ghanavati, Goodarz; Lakoba, Taras I; Cotilla-Sanchez, Eduardo
2013-01-01
Many dynamical systems, including power systems, recover from perturbations more slowly as they approach critical transitions---a phenomenon known as critical slowing down. If the system is stochastically forced, autocorrelation and variance in time-series data from the system often increase before the transition, potentially providing an early warning of coming danger. In some cases, these statistical patterns are sufficiently strong, and occur sufficiently far from the transition, that they can be used to predict the distance between the current operating state and the critical point. In other cases CSD comes too late to be a good indicator. In order to better understand the extent to which CSD can be used as an indicator of proximity to bifurcation in power systems, this paper derives autocorrelation functions for three small power system models, using the stochastic differential algebraic equations (SDAE) associated with each. The analytical results, along with numerical results from a larger system, show...
OFDM Signal Detector Based on Cyclic Autocorrelation Function and its Properties
Z. Fedra
2011-12-01
Full Text Available This paper is devoted to research of the general and particular properties of the OFDM signal detector based on the cyclic autocorrelation function. The cyclic autocorrelation function is estimated using DFT. The parameters of the testing signal have been chosen according to 802.11g WLAN. Some properties are described analytically; all events are examined via computer simulations. It is shown that the detector is able to detect an OFDM signal in the case of multipath propagation, inexact frequency synchronization and without time synchronization. The sensitivity of the detector could be decreased in the above cases. An important condition for proper value of the detector sampling interval was derived. Three types of the channels were studied and compared. Detection threshold SNR=-9 dB was found for the signal under consideration and for two-way propagation.
Wang, Mingyi; Zeng, Yaguang; Dong, Nannan; Liao, Riwei; Yang, Guojian
2016-03-01
We propose a full-field optical method for the label-free and quantitative mapping of the velocities of red blood cells (RBCs) in capillaries. It integrates spatiotemporal demodulation and an autocorrelation algorithm, and measures RBC velocity according to the ratio of RBC length to lag time. Conventionally, RBC length is assumed to be a constant and lag time is taken as a variable, while our method treats both of them as variables. We use temporal demodulation and the Butterworth spatial filter to separate RBC signal from background signal, based on which we obtain the RBC length by image segmentation and lag time by autocorrelation analysis. The RBC velocity calculated now is more accurate. The validity of our method is verified by an in vivo experiment on a mouse ear. Owing to its higher image signal-to-noise ratio, our method can be used for mapping RBC velocity in the turbid tissue case.
Development of autocorrelator for hard X-ray free electron laser. Study on alignment procedure
X-ray free electron laser (XFEL) sources, which produce unprecedented brilliant, transversely coherent, and ultra-short x-ray pulses, are the powerful tools for exploring new possibilities in ultrafast science with hard x rays. A split-delay optics called autocorrelator provides two replica pulses with time delay precisely controlled, which is essential to realize XFEL pump and XFEL probe experiments. In order to overlap two XFEL pulses sufficiently, precise tuning of crystal angles is required. We investigated influences of each angular error to pointing displacement of XFEL beams and the tolerated error calculated by ray trace method was ±0.07 μrad at Japan's XFEL facility, SACLA. We also present some alignment methods to parallelize the two beams after autocorrelator precisely. (author)
Murthy, Garimella Rama
2012-01-01
In this research paper, the relationship between finite / countable state space stochastic processes and point processes is explored. Utilizing the known relationship between Poisson processes and continuous time Markov chains, finite / countable state space random processes are related to continuous time Markov Chains. Based on the known results for binary random processes, characterization of auto-correlation function of finite state space random processes is explored. An important characte...
A new method to determine scintillator decay time and space correlation of radiation is described. The method is based on an autocorrelation delayed-coincidence time spectrometer and it has been applied to measure the decay time of inorganic and organic scintillators in a range from tens of nanoseconds to a few microseconds. Results with NAFTALEN and CsI(Tl) show decay times of τ=75.0(8) ns and 998(15) ns, respectively
Self-organization theory based on autocorrelations and demonstrations by simulations
Kondoh, Yoshiomi; Yamaguchi, Masanori; Yokozuka, Katsuhisa [Gunma Univ., Kiryu (Japan). Faculty of Engineering
1997-12-31
A general theory of self-organization based on autocorrelations is presented. The general theory is applied to compressible resistive MHD plasmas. It is shown by 3D MHD simulations that the self-organized relaxed state depends on the spatial profile of resistivity. It is also shown by 3D MHD simulations that although there is no magnetic helicity injection, the toroidal current J{sub z} is actually induced by the process of relaxation without helicity invariance. (author)
Border effects and spatial autocorrelation in the supply of network infrastructure
Wintershoven, Patrick; Rietveld, Piet
1997-01-01
In this paper we analyze the supply of network infrastructure at the regional level. Special attention is paid to spatial autocorrelation aspects. A method is developed to test which impact international borders have on the supply of network infrastructure in border regions. An empirical illustration is given for the regions in the EU. We find that in the case of railways spatial spill-overs are indeed significant. However, the hypothesis that border effects play a role in railway densities h...
Songhurst, Anna; Coulson, Tim
2014-01-01
Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human–wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative...
Cross-Autocorrelation between Small and Large Cap Portfolios in the German and Turkish Stock Markets
Erdinc Altay
2003-01-01
This paper studies the cross-autocorrelation structure in the German and Turkish stock markets by using daily portfolio returns. We find the evidence that large cap portfolios lead small cap portfolios in both subperiods of German stock market but this structure is seen only in the first subperiod of Turkish stock market. Analysing the market-wide and portfolio-specific information effects on portfolio returns shows that above stated lead-lag relation is associated with the market-wide inform...
A new radial strain and strain rate estimation method using autocorrelation for carotid artery
Ye, Jihui; Kim, Hoonmin; Park, Jongho; Yeo, Sunmi; Shim, Hwan; Lim, Hyungjoon; Yoo, Yangmo
2014-03-01
Atherosclerosis is a leading cause of cardiovascular disease. The early diagnosis of atherosclerosis is of clinical interest since it can prevent any adverse effects of atherosclerotic vascular diseases. In this paper, a new carotid artery radial strain estimation method based on autocorrelation is presented. In the proposed method, the strain is first estimated by the autocorrelation of two complex signals from the consecutive frames. Then, the angular phase from autocorrelation is converted to strain and strain rate and they are analyzed over time. In addition, a 2D strain image over region of interest in a carotid artery can be displayed. To evaluate the feasibility of the proposed radial strain estimation method, radiofrequency (RF) data of 408 frames in the carotid artery of a volunteer were acquired by a commercial ultrasound system equipped with a research package (V10, Samsung Medison, Korea) by using a L5-13IS linear array transducer. From in vivo carotid artery data, the mean strain estimate was -0.1372 while its minimum and maximum values were -2.961 and 0.909, respectively. Moreover, the overall strain estimates are highly correlated with the reconstructed M-mode trace. Similar results were obtained from the estimation of the strain rate change over time. These results indicate that the proposed carotid artery radial strain estimation method is useful for assessing the arterial wall's stiffness noninvasively without increasing the computational complexity.
What autocorrelation tells us about motor variability: insights from dart throwing.
van Beers, Robert J; van der Meer, Yor; Veerman, Richard M
2013-01-01
In sports such as golf and darts it is important that one can produce ballistic movements of an object towards a goal location with as little variability as possible. A factor that influences this variability is the extent to which motor planning is updated from movement to movement based on observed errors. Previous work has shown that for reaching movements, our motor system uses the learning rate (the proportion of an error that is corrected for in the planning of the next movement) that is optimal for minimizing the endpoint variability. Here we examined whether the learning rate is hard-wired and therefore automatically optimal, or whether it is optimized through experience. We compared the performance of experienced dart players and beginners in a dart task. A hallmark of the optimal learning rate is that the lag-1 autocorrelation of movement endpoints is zero. We found that the lag-1 autocorrelation of experienced dart players was near zero, implying a near-optimal learning rate, whereas it was negative for beginners, suggesting a larger than optimal learning rate. We conclude that learning rates for trial-by-trial motor learning are optimized through experience. This study also highlights the usefulness of the lag-1 autocorrelation as an index of performance in studying motor-skill learning. PMID:23691199
Tiao, G.C.; Daming, Xu; Pedrick, J.H.; Xiaodong, Zhu (Univ. of Chicago, IL (USA)); Reinsel, G.C. (Univ. of Wisconsin, Madison (USA)); Miller, A.J.; DeLuisi, J.J. (National Oceanic and Atmospheric Administration, Boulder, CO (USA)); Mateer, C.L. (Atmospheric Environment Service, Ottawa, Ontario (Canada)); Wuebbles, D.J. (Lawrence Livermore National Lab., CA (USA))
1990-11-20
This paper is concerned with temporal data requirements for the assessment of trends and for estimating spatial correlations of atmospheric species. The authors examine statistically three basic issues: (1) the effect of autocorrelations in monthly observations and the effect of the length of data record on the precision of trend estimates, (2) the effect of autocorrelations in the daily data on the sampling frequency requirements with respect to the representativeness of monthly averages for trend estimation, and (3) the effect of temporal sampling schemes on estimating spatial correlations of atmospheric species in neighboring stations. The principal findings are (1) the precision of trend estimates depends critically on the magnitude of auto-correlations in the monthly observations, (2) this precision is insensitive to the temporal sampling rates of daily measurements under systematic sampling, and (3) the estimate of spatial correlation between two neighboring stations is insensitive to temporal sampling rate under systematic sampling, but is sensitive to the time lag between measurements taken at the two stations. These results are based on methodological considerations as well as on empirical analysis of total and profile ozone and rawinsonde temperature data from selected ground stations.
What autocorrelation tells us about motor variability: insights from dart throwing.
Robert J van Beers
Full Text Available In sports such as golf and darts it is important that one can produce ballistic movements of an object towards a goal location with as little variability as possible. A factor that influences this variability is the extent to which motor planning is updated from movement to movement based on observed errors. Previous work has shown that for reaching movements, our motor system uses the learning rate (the proportion of an error that is corrected for in the planning of the next movement that is optimal for minimizing the endpoint variability. Here we examined whether the learning rate is hard-wired and therefore automatically optimal, or whether it is optimized through experience. We compared the performance of experienced dart players and beginners in a dart task. A hallmark of the optimal learning rate is that the lag-1 autocorrelation of movement endpoints is zero. We found that the lag-1 autocorrelation of experienced dart players was near zero, implying a near-optimal learning rate, whereas it was negative for beginners, suggesting a larger than optimal learning rate. We conclude that learning rates for trial-by-trial motor learning are optimized through experience. This study also highlights the usefulness of the lag-1 autocorrelation as an index of performance in studying motor-skill learning.
Spatial autocorrelation method using AR model; Kukan jiko sokanho eno AR model no tekiyo
Yamamoto, H.; Obuchi, T.; Saito, T. [Iwate University, Iwate (Japan). Faculty of Engineering
1996-05-01
Examination was made about the applicability of the AR model to the spatial autocorrelation (SAC) method, which analyzes the surface wave phase velocity in a microtremor, for the estimation of the underground structure. In this examination, microtremor data recorded in Morioka City, Iwate Prefecture, was used. In the SAC method, a spatial autocorrelation function with the frequency as a variable is determined from microtremor data observed by circular arrays. Then, the Bessel function is adapted to the spatial autocorrelation coefficient with the distance between seismographs as a variable for the determination of the phase velocity. The result of the AR model application in this study and the results of the conventional BPF and FFT method were compared. It was then found that the phase velocities obtained by the BPF and FFT methods were more dispersed than the same obtained by the AR model. The dispersion in the BPF method is attributed to the bandwidth used in the band-pass filter and, in the FFT method, to the impact of the bandwidth on the smoothing of the cross spectrum. 2 refs., 7 figs.
Lagged Poincar\\'{e} and auto-correlation analysis of Heart rate variability in diabetes
Ghatak, S K
2010-01-01
The heart rate variability (HRV) in diabetic human subjects, has been analyzed using lagged Poincar\\'{e} plot, auto-correlation and the detrended fluctuation analysis methods. The parameters $SD1$, and $SD12 (= SD1/SD2)$ for Poincar\\'{e} plot for diabetic are lower than that for non-diabetic subjects and reverse is case for $SD2$ for all lagged number (m). The slope and the curvature of the plot SD12 vs m is much reduced for diabetic subject. The scatter plot of two successive interbeat intervals points out smaller variability in diabetic heart. The detrended fluctuation exponent has a higher value for diabetic group. The auto-correlation function of the deviation of interbeat interval in diabetic group shows highly correlated pattern when compared to that of normal one. The study suggests that the curvature of $SD12$ and auto-correlation method appear to be better way to assess the alteration of regulatory system on heart dynamics in diabetic condition.
Interferometric autocorrelation of an attosecond pulse train calculated using feasible formulae
The autocorrelation trace of an attosecond pulse train (APT) directly revealed the pulse envelope in our recent experiment on measuring the two-photon Coulomb explosion of a nitrogen molecule as a correlation signal. Although the spatial overlap of the two replicas of the APT in the correlation measurement was only achieved near the focal region owing to the spatial split of the measured APT field, which is a situation quite different from that of the correlation measurement using a Michelson interferometer, the interference fringes clearly appeared on the correlation envelope and provedthe odd symmetry of the electric field to the time translation with a half-period of the driving laser field. In this paper, we show a simple and practical analysis for the propagation and the nonlinear interaction of an APT to simulate the experimental result of the interferometric autocorrelation of the spatially split APT. The spatial convolution of the focused electric field is essential for obtaining the fringes. We also discuss how the autocorrelation should be described in the context of the second-order perturbation theory within a dipole approximation
Adaptive non-collinear autocorrelation of few-cycle pulses with an angular tunable bi-mirror
Treffer, A., E-mail: treffer@mbi-berlin.de; Bock, M.; König, S.; Grunwald, R. [Max Born Institute for Nonlinear Optics and Short-Pulse Spectroscopy, Max Born Strasse 2A, D-12489 Berlin (Germany); Brunne, J.; Wallrabe, U. [Laboratory for Microactuators, Department of Microsystems Engineering, IMTEK, University of Freiburg, Georges-Koehler-Allee 102, Freiburg 79110 (Germany)
2016-02-01
Adaptive autocorrelation with an angular tunable micro-electro-mechanical system is reported. A piezo-actuated Fresnel bi-mirror structure was applied to measure the second order autocorrelation of near-infrared few-cycle laser pulses in a non-collinear setup at tunable superposition angles. Because of enabling measurements with variable scaling and minimizing the influence of distortions by adaptive self-reconstruction, the approach extends the capability of autocorrelators. Flexible scaling and robustness against localized amplitude obscurations are demonstrated. The adaptive reconstruction of temporal frequency information by the Fourier analysis of autocorrelation data is shown. Experimental results and numerical simulations of the beam propagation and interference are compared for variable angles.
Chen, Xuan; Goodwin, Barry K.
2012-01-01
Our study focuses on modeling wildfire damage in the State of Florida. The approach is to evaluate wildfire risks in a spatio-temporal framework. A block bootstrapping method has been proposed to construct a statistical model accounting for explanatory variables while adjusting for spatial and temporal autocorrelation. Although the bootstrap (Efron 1979) method can handle independent observations well, the strong autocorrelation of wildfire risks brings about a major challenge. Motivated by b...
McKee, K. F.; Waite, G. P.; Richardson, J. P.
2012-12-01
We used the Green's functions from auto-correlations and cross-correlations of seismic ambient noise to monitor temporal velocity changes in the subsurface at Villarrica Volcano in the Southern Andes of Chile. Campaigns were conducted from March to October 2010 and February to April 2011 with 8 broadband and 6 short-period stations, respectively. We prepared the data by removing the instrument response, normalizing with a root-mean-square method, whitening the spectra, and filtering from 1 to 10 Hz. This frequency band was chosen based on the relatively high background noise level in that range. Hour-long auto- and cross-correlations were computed and the Green's functions stacked by day and total time. To track the temporal velocity changes we stretched a 24 hour moving window of correlation functions from 90% to 110% of the original and cross correlated them with the total stack. The average increase in velocity gleaned from the auto-correlations during the 2010 array was 0.13%, as seen in the figure. Cross-correlations from station V01, near the summit, to the other stations show comparable increases in velocity. We attribute this change to the closing of cracks in the subsurface due either to seasonal snow loading or regional tectonics. In addition to the common increase in velocity across the stations, there are excursions in velocity on the same order lasting several days. Amplitude decreases as the station's distance from the vent increases suggesting these excursions may be attributed to changes within the volcanic edifice. Two occurrences are highlighted in the figure in which it is seen that the amplitudes at stations V06 and V07, the stations farthest from the vent, are smaller. Similar short temporal excursions were seen in the auto-correlations from 2011, however, there was little to no increase in the overall velocity.ercent change in velocity at Villarrica Volcano, Chile from March to October 2010 (stations offset by 0.2%)
De Pretto, Lucas R.; Nogueira, Gesse E. C.; Freitas, Anderson Z.
2016-04-01
Functional modalities of Optical Coherence Tomography (OCT) based on speckle analysis are emerging in the literature. We propose a simple approach to the autocorrelation of OCT signal to enable volumetric flow rate differentiation, based on decorrelation time. Our results show that this technique could distinguish flows separated by 3 μl/min, limited by the acquisition speed of the system. We further perform a B-scan of gradient flow inside a microchannel, enabling the visualization of the drag effect on the walls.
Observation and analysis of an interferometric autocorrelation trace of an attosecond pulse train
We report the direct observation of phase locking between adjacent pulses in an attosecond pulse train (APT) via interferometric autocorrelation (IAC). In this measurement, the Coulomb explosion of N2 caused by two-photon absorption is utilized as correlated signals between two replicas of the APT that are the outcome of the spatial division of the APT in the interferometer. The analysis of IAC by the spatial division of the APT is consistent with the experimental trace of the IAC, and yields the duration of the pulse in the APT of 320 attoseconds, which corresponds to a 1.3 cycle period of the carrier frequency of the harmonic field
A second-order autocorrelator for single-shot measurement of femtosecond laser pulse durations
M Raghuramaiah; A K Sharma; P A Naik; P D Gupta; R A Ganeev
2001-12-01
A second-order autocorrelator for single-shot measurement of ultrashort laser pulse durations has been set up. It is based on recording the spatial proﬁle of non-collinear phase-matched second harmonic generation in a KDP crystal using a CCD camera-framegrabber combination. Performance of the system is described from measurement of 250 femtosecond transform-limited laser pulses from a passively mode-locked, diode pumped Nd:glass laser. It can also be used for measurement of picosecond laser pulses in the multi-shot scanning mode.
New autocorrelation technique for the IR FEL optical pulse width measurements
Amirmadhi, F.; Brau, K.A.; Becker, C. [Vanderbilt Univ., Nashville, TN (United States)] [and others
1995-12-31
We have developed a new technique for the autocorrelation measurement of optical pulse width at the Vanderbilt University FEL center. This method is based on nonlinear absorption and transmission characteristics of semiconductors such as Ge, Te and InAs suitable for the wavelength range from 2 to over 6 microns. This approach, aside being simple and low cost, removes the phase matching condition that is generally required for the standard frequency doubling technique and covers a greater wavelength range per nonlinear material. In this paper we will describe the apparatus, explain the principal mechanism involved and compare data which have been acquired with both frequency doubling and two-photon absorption.
Fifth-order intensity autocorrelations based on six-wave mixing of femtosecond laser pulses
Gaižauskas, Eugenijus; Steponkevičius, KÈ©stutis; Vaičaitis, Virgilijus
2016-02-01
It is shown both experimentally and by numerical simulations that fifth-order intensity autocorrelations of femtosecond laser pulses can be obtained from two-beam noncollinear six-wave mixing in air. A numerical analysis of competing direct and six-wave-assisted third-harmonic-generation pathways showed that these measurements are suitable for the background-free temporal characterization of laser pulses. Reshaping of the pulse and 10 fs subpulse formation during the primary stages of light filamentation were observed using the proposed method.
Blood vector velocity estimation using an autocorrelation approach: In vivo Investigation
Udesen, Jesper; Bachmann, Michael; Rue, Kristina;
2005-01-01
transverse oscillation (TO) method) based on an autocorrelation approach. The TO method makes use of a double oscillating pulse-echo field which is created by manipulating the receive apodization function. Two receive beams are beamformed, where the lateral distance between the two beams corresponds to a 90...... deg phase shift in the lateral direction. The TO method works at angles where conventional methods fails to estimate any blood movement, i.e. when the angle between the ultrasound beam and the velocity vector is approximately 90 deg. In this paper the first in-vivo color flow map (CFM) images are...
Cross-Autocorrelation of Dual-Listed Stock Portfolio Returns: Evidence from the Chinese Stock Market
Daxue Wang
2006-01-01
In this paper, we apply a GARCH model to examine the cross-autocorrelation pattern between daily returns of portfolios composed of dual-listed stocks in Chinese stock market, before and after China opened its once foreign-exclusive B-share market. A lead-lag relationship between the A-share and B-share portfolio returns is identified during our sample periods, with the A-share portfolio leading the B-share portfolio. Upon the opening of B-share market, a change from underreaction to overreact...
Large Zero Autocorrelation Zone of Golay Sequences and $4^q$-QAM Golay Complementary Sequences
Gong, Guang; Yang, Yang
2011-01-01
Sequences with good correlation properties have been widely adopted in modern communications, radar and sonar applications. In this paper, we present our new findings on some constructions of single $H$-ary Golay sequence and $4^q$-QAM Golay complementary sequence with a large zero autocorrelation zone, where $H\\ge 2$ is an arbitrary even integer and $q\\ge 2$ is an arbitrary integer. Those new results on Golay sequences and QAM Golay complementary sequences can be explored during synchronization and detection at the receiver end and thus improve the performance of the communication system.
Blood vector velocity estimation using an autocorrelation approach: In vivo Investigation
Udesen, Jesper; Bachmann, Michael; Rue, Kristina; Jensen, Jørgen Arendt
transverse oscillation period of 1 mm was created in the lateral pulse-echo field by manipulating the receive apodization function. Echo-canceling was performed by subtracting a line from the sampled data, where the line was a linear fit to the sampled data. Three different scan areas were selected: 1) The...... transverse oscillation (TO) method) based on an autocorrelation approach. The TO method makes use of a double oscillating pulse-echo field which is created by manipulating the receive apodization function. Two receive beams are beamformed, where the lateral distance between the two beams corresponds to a 90...
HOU Yuexian; HE Pilian
2005-01-01
There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this paper introduces a universal method to achieve nonlinear models identification. Two key quantities, which are called nonlinear irreducible auto-correlation (NIAC) and generalized nonlinear irreducible auto-correlation (GNIAC), are defined and discussed. NIAC and GNIAC correspond with intrinstic irreducible auto-dependency (IAD) and generalized irreducible auto-dependency (GIAD) of time series respectively. By investigating the evolving trend of NIAC and GNIAC, the optimal auto-regressive order of nonlinear auto-regressive models could be determined naturally. Subsequently, an efficient algorithm computing NIAC and GNIAC is discussed. Experiments on simulating data sets and typical nonlinear prediction models indicate remarkable correlation between optimal auto-regressive order and the highest order that NIAC-GNIAC have a remarkable non-zero value, therefore demonstrate the validity of the proposal in this paper.
On the Decay Ratio Determination in BWR Stability Analysis by Auto-Correlation Function Techniques
A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. These models, corrected for signal filtering and including a background term under the peak in the PSD, are then least-squares fitted to the ACF of the previously filtered neutron signal, in order to determine the oscillation frequency and the decay ratio. Our method uses fast Fourier transform techniques with signal segmentation for filtering and ACF estimation. Gliding 'short-term' ACF estimates on a record allow the evaluation of uncertainties. Numerical results are given which have been obtained from neutron data of the recent Forsmark I and Forsmark II NEA benchmark project. Our results are compared with those obtained by other participants in the benchmark project. The present PSI report is an extended version of the publication K. Behringer, D. Hennig 'A novel auto-correlation function method for the determination of the decay ratio in BWR stability studies' (Behringer, Hennig, 2002)
Liu, Xiaofeng; Bo, Lin; Luo, Honglin
2016-04-01
In this paper, smoothing localized directional cyclic autocorrelation (SLDCA) is proposed as a novel time-frequency distribution to analyze the vibration signal of rotor-bearing system in oil-film instability. Based on the cyclostationarity of real-valued signal, directional cyclic autocorrelation (DCA) is defined for the complex-valued signal. In order to suppress the cross-term interferences, the DCA is localized and filtered with two-dimensional time-frequency window which allows the smoothing kernel function to adapt to the signal time-frequency-varying characteristics. And then the localized DCA is smoothed by the localized optimal radially Gaussian kernel and cascaded to produce the SLDCA with high time-frequency resolution and less susceptibility to cross-term interferences. The application of SLDCA in the oil-film instability analysis verifies that the SLDCA can not only precisely detect the instantaneous frequency information in the time-frequency distribution with high resolution and robustness to the noises and cross-terms, but also provide the phase coupling information of rotor instantaneous planar motion by which the directivity and shape of the planar motion can be determined.
Two photon double ionization of He+: autocorrelation of soft X-ray FEL pulses
In order to perform jitter-free X-ray pump and probe experiments at the Free Electron Laser in Hamburg (FLASH) as well as to characterize the temporal structure of its high power pulses a novel beam splitter and delay unit (autocorrelator) has been designed and constructed. Based on geometrical beam splitting by a mirror edge the apparatus covers the XUV energy range up to photon energies of 200 eV providing a total delay of about 20 picoseconds with sub-femtosecond resolution. As a first test the pulse length of the FEL pulses has been measured at 24 nm. While the nonlinear autocorrelation in the UV and visible regions is a well established method to determine the duration of laser pulse there is a lack of efficient nonlinear detection processes in the soft X-ray regime. In this first experiments the pulse length of the FEL pulses provided at 24 nm are measured by double ionization of He, yielding a duration of (30±5) fs
Broadband short pulse measurement by autocorrelation with a sum-frequency generation set-up
Glotin, F.; Jaroszynski, D.; Marcouille, O. [LURE, Orsay (France)] [and others
1995-12-31
Previous spectral and laser pulse length measurements carried out on the CLIO FEL at wavelength {lambda}=8.5 {mu}m suggested that very short light pulses could be generated, about 500 fs wide (FWHM). For these measurements a Michelson interferometer with a Te crystal, as a non-linear detector, was used as a second order autocorrelation device. More recent measurements in similar conditions have confirmed that the laser pulses observed are indeed single: they are not followed by other pulses distant by the slippage length N{lambda}. As the single micropulse length is likely to depend on the slippage, more measurements at different wavelengths would be useful. This is not directly possible with our actual interferometer set-up, based on a phase-matched non-linear crystal. However, we can use the broadband non-linear medium provided by one of our users` experiments: Sum-Frequency Generation over surfaces. With such autocorrelation set-up, interference fringes are no more visible, but this is largely compensated by the frequency range provided. First tests at 8 {mu}m have already been performed to validate the technic, leading to results similar to those obtained with our previous Michelson set-up.
da Silva Filho, Paulo Cavalcante; da Silva, Francisco Raimundo; Corso, Gilberto
2016-07-01
In this study, we analyzed the autocorrelation among four ultraviolet (UV) radiation data sets obtained at 305 nm, 320 nm, 340 nm, and 380 nm. The data were recorded at ground level at the INPE climate station in Natal, RN, Brazil, which is a site close to the equator. The autocorrelations were computed by detrended fluctuation analysis (DFA) to estimate the index α. We found that the fluctuations in the UV radiation data were fractal, with scale-free behavior at a DFA index α ≃ 0.7. In addition, we performed a power law spectral analysis, which showed that the power spectrum exhibited a power law behavior with an exponent of β ≃ 0.45. Given that the theoretical result is β = 2 α - 1, these two results are in good agreement. Moreover, the application of the DFA method to the UV radiation data required detrending using a polynomial with an order of at least eight, which was related to the complex daily solar radiation curve obtained at ground level in a tropical region. The results indicated that the α exponent of UV radiation is similar to other climatic records such as air temperature, wind, or rain, but not solar activity.
Ha, Jong M.; Youn, Byeng D.; Oh, Hyunseok; Han, Bongtae; Jung, Yoongho; Park, Jungho
2016-03-01
We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.
Autocorrelation-based estimate of particle image density for diffraction limited particle images
In particle image velocimetry (PIV), the number of particle images per interrogation region, or particle image density, impacts the strength of the correlation and, as a result, the number of valid vectors and the measurement uncertainty. For some uncertainty methods, an a priori estimate of the uncertainty of PIV requires knowledge of the particle image density. An autocorrelation-based method for estimating the local, instantaneous, particle image density is presented. The method assumes that the particle images are diffraction limited and thus Gaussian in shape. Synthetic images are used to develop an empirical relationship between the autocorrelation peak magnitude and the particle image density, particle image diameter, particle image intensity, and interrogation region size. This relationship is tested using experimental images. The experimental results are compared to particle image densities obtained through implementing a local maximum method and are found to be more robust. The effect of varying particle image intensities was also investigated and is found to affect the measurement of the particle image density. Knowledge of the particle image density in PIV facilitates uncertainty estimation, and can alert the user that particle image density is too low or too high, even if these conditions are intermittent. This information can be used as a new vector validation criterion for PIV processing. In addition, use of this method is not limited to PIV, but it can be used to determine the density of any image with diffraction limited particle images. (paper)
Gur, Berke M; Niezrecki, Christopher
2007-07-01
Recent interest in the West Indian manatee (Trichechus manatus latirostris) vocalizations has been primarily induced by an effort to reduce manatee mortality rates due to watercraft collisions. A warning system based on passive acoustic detection of manatee vocalizations is desired. The success and feasibility of such a system depends on effective denoising of the vocalizations in the presence of high levels of background noise. In the last decade, simple and effective wavelet domain nonlinear denoising methods have emerged as an alternative to linear estimation methods. However, the denoising performances of these methods degrades considerably with decreasing signal-to-noise ratio (SNR) and therefore are not suited for denoising manatee vocalizations in which the typical SNR is below 0 dB. Manatee vocalizations possess a strong harmonic content and a slow decaying autocorrelation function. In this paper, an efficient denoising scheme that exploits both the autocorrelation function of manatee vocalizations and effectiveness of the nonlinear wavelet transform based denoising algorithms is introduced. The suggested wavelet-based denoising algorithm is shown to outperform linear filtering methods, extending the detection range of vocalizations. PMID:17614478
Hutmacher, Matthew M
2016-06-01
Longitudinal models of binary or ordered categorical data are often evaluated for adequacy by the ability of these to characterize the transition frequency and type between response states. Drug development decisions are often concerned with accurate prediction and inference of the probability of response by time and dose. A question arises on whether the transition probabilities need to be characterized adequately to ensure accurate response prediction probabilities unconditional on the previous response state. To address this, a simulation study was conducted to assess bias in estimation, prediction and inferences of autocorrelated latent variable models (ALVMs) when the transition probabilities are misspecified due to ill-posed random effects structures, inadequate likelihood approximation or omission of the autocorrelation component. The results may be surprising in that these suggest that characterizing autocorrelation in ALVMs is not as important as specifying a suitably rich random effects structure. PMID:27007275
On the use of the simple and partial Mantel tests in presence of spatial auto-correlation
Guillot, Gilles; Rousset, Francois
2011-01-01
The Mantel test is routinely used in many areas of biology and environmental sciences to assess the signicance of the association between two or more matrices of distances relative to the same pairs of indi- viduals. This test is a valid statistical procedure to test the auto-correlation of a...... single (possibly multivariate) variable. This includes the widely used test of isolation-by-distance in population genetics. However, we show that contrarily to a widely shared belief, the simple and partial Mantel tests are not valid statistical procedures to assess the signicance of the correlation...... between two variables structured in space. Under a fairly general model, simulations show that the Mantel tests provide an excess of Type I error whose magnitude increases with the intensity of the spatial auto-correlation. The Mantel tests should not be used in case auto-correlation is suspected in both...
Sim, K S; Lim, M S; Yeap, Z X
2016-07-01
A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. PMID:26871742
Oren, C.; Nowack, R. L.
2015-12-01
It is known that the positive lags of the auto-correlation for the seismic transmission response of a layered medium correspond to the reflection seismogram (Claerbout, 1968). In this study, we investigate the use of ambient seismic noise recorded at selected broadband USArray EarthScope Transportable Array (TA) stations to obtain effective reflection seismograms for frequencies up to 1 Hz. The goal is to determine the most suitable parameters used for the processing of ambient seismic noise for the identification of crustal and upper mantle reflections and to minimize unwanted artifacts in the noise correlations. In order to best retrieve the body-wave components of the Green's function beneath a station, a number of processing steps are required. We first remove the instrument response and apply a temporal normalization to remove the effects of the most energetic sources. Next we implement spectral whitening. We test several operators for the spectral whitening where the undulations of the power spectrum are related to the strengths of later arrivals in the auto-correlation. Different filters are then applied to the auto-correlation functions, including Gaussian and zero phase Butterworth filters, in order to reduce the effect of side lobes. Hourly auto-correlations are then stacked for up to one year. On the final stack, Automatic Gain Control (AGC) is applied to equalize the correlation amplitudes in the time domain. The robustness of the resulting ambient noise auto-correlation is first tested on selected TA stations in Nevada, where we are able to identify PmP and SmS arrivals similar to those found by Tibuleac and von Seggern (2012). We then investigate noise auto-correlations applied to selected USArray TA stations in the central US.
Autocorrelation measurement of an ultra-short optical pulse using an electrically focus-tunable lens
Serna, Juan; Hamad, Abdullatif; Rueda, Edgar; Garcia, Hernando
2015-10-01
In this communication, a novel technique to measure the temporal width of an ultra-short optical pulse using an electrically focus-tunable lens (EFTL) is proposed and implemented (no need for a mechanical translation stage). The principle is based on the time delay experienced by the pulse when it passes through the deformed membrane of the EFTL as the focal length changes by an applied current. The resolution of the system is approximately 0.23 fs, with a total time delay of 0.69 ps. A typical autocorrelation can be performed in less than 5 s with an excellent Signal to Noise Ratio. The same technique can be implemented to study ultrafast phenomena like electronic relaxation or ultrafast fluorescence in a pump-probe configuration.
Le Marec, Andréa; Guilbaud, Olivier; Larroche, Olivier; Klisnick, Annie
2016-07-15
We study how the degree of temporal coherence of plasma-based extreme ultraviolet lasers operated in the amplification of the spontaneous emission mode is encoded in the shape of the linear autocorrelation function, which is obtained from the variation of the fringe visibility while varying the delay in a variable path-difference interferometer. We discuss the implications of this effect when the technique is used to infer the spectral properties of the source. Our numerical simulations, based on a partial coherence model developed by other authors for x-ray free electron lasers, are in good agreement with previously reported sets of measurements, illustrating similar statistical properties for both sources. PMID:27420542
Autocorrelation function of channel matrix in few-mode fibers with strong mode coupling.
Hu, Qian; Shieh, William
2013-09-23
Channel matrix plays a critical role in receiver design and ultimate channel performance. To fully describe the channel matrix of a few-mode fiber (FMF), we choose the generalized high-dimensional Gell-Mann matrices, an equivalent of the 2-dimensional Pauli matrices used for a single-mode fiber (SMF), as the basis for the channel matrix decomposition. The frequency dependence of channel matrix can be studied in terms of the autocorrelation function (ACF), showing how fast channel changes in frequency domain. In this paper, we derive a canonical stochastic differential equation (SDE) for the FMF channel matrix in the regime of strong coupling. With the SDE, we develop an analytical form for the ACF of FMF channel matrix, from which the channel correlation bandwidth is obtained. PMID:24104107
Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns
Paul Holloway
2015-05-01
Full Text Available In this paper we explore relationships between bird species richness and environmental factors in New York State, focusing particularly on how spatial scale, autocorrelation and nonstationarity affect these relationships. We used spatial statistics, Getis-Ord Gi*(d, to investigate how spatial scale affects the measurement of richness “hot-spots” and “cold-spots” (clusters of high and low species richness, respectively and geographically weighted regression (GWR to explore scale dependencies and nonstationarity in the relationships between richness and environmental variables such as climate and plant productivity. Finally, we introduce a geovisualization approach to show how these relationships are affected by spatial scale in order to understand the complex spatial patterns of species richness.
The autocorrelated noise filtering problem: the ISMC filter in a specific case of distance measuring
Prattico, Flavio
2013-01-01
In a previous paper we were working on a electronic travel aid for blind people based on infrared sensors. The signals coming from them are affected by a great noise that also with the use of low pass filter cannot be clean well. Motivated by the improvement of the system, in this paper we show a novelty way to filter autocorrelated noise based on a probabilistic description of the process. We apply an indexed semi-Markov model in order to filter the signal coming from the infrared sensor. We conduce first of all a data analysis on the noise in order to understand well its form. We give the general formulation of the new ISMC filter and at last we compare the results with a particular kind of Kalman filter for the specific stochastic application.
FPGA implementation of a 32x32 autocorrelator array for analysis of fast image series
Buchholz, Jan; Mocsár, Gábor; Kreith, Balázs; Charbon, Edoardo; Vámosi, György; Kebschull, Udo; Langowski, Jörg
2011-01-01
With the evolving technology in CMOS integration, new classes of 2D-imaging detectors have recently become available. In particular, single photon avalanche diode (SPAD) arrays allow detection of single photons at high acquisition rates (\\geq 100 kfps), which is about two orders of magnitude higher than with currently available cameras. Here we demonstrate the use of a SPAD array for imaging fluorescence correlation spectroscopy (imFCS), a tool to create 2D maps of the dynamics of fluorescent molecules inside living cells. Time-dependent fluorescence fluctuations, due to fluorophores entering and leaving the observed pixels, are evaluated by means of autocorrelation analysis. The multi-{\\tau} correlation algorithm is an appropriate choice, as it does not rely on the full data set to be held in memory. Thus, this algorithm can be efficiently implemented in custom logic. We describe a new implementation for massively parallel multi-{\\tau} correlation hardware. Our current implementation can calculate 1024 corre...
Statistical modelling of tropical cyclone tracks: modelling the autocorrelation in track shape
Hall, T; Hall, Tim; Jewson, Stephen
2005-01-01
We describe results from the third stage of a project to build a statistical model for hurricane tracks. In the first stage we modelled the unconditional mean track. In the second stage we modelled the unconditional variance of fluctuations around the mean. Now we address the question of how to model the autocorrelations in the standardised fluctuations. We perform a thorough diagnostic analysis of these fluctuations, and fit a type of AR(1) model. We then assess the goodness of fit of this model in a number of ways, including an out-of-sample comparison with a simpler model, an in-sample residual analysis, and a comparison of simulated tracks from the model with the observed tracks. Broadly speaking, the model captures the behaviour of observed hurricane tracks. In detail, however, there are a number of systematic errors.
Self-Calibration for 3-point Intrinsic Alignment Auto-Correlations in Weak Lensing Surveys
Troxel, M A
2012-01-01
The weak lensing signal (cosmic shear) has been shown to be strongly contaminated by the various types of galaxy intrinsic alignment (IA) correlations, which poses a barrier to precision weak lensing measurements. The redshift dependence of the IA signal has been used at the 2-point level to reduce this contamination by only measuring cross-correlations between large redshift bins, which significantly reduces the galaxy intrinsic ellipticity - intrinsic ellipticity (II) correlation. A self-calibration technique based on the redshift dependences of the IA correlations has also been proposed as a means to remove the 2-point IA contamination from the lensing signal. We explore here the redshift dependences of the IA and lensing bispectra in order to propose a self-calibration of the IA auto-correlations at the 3-point level (i.e. GGI, GII, and III), which can be well understood without the assumption of any particular IA model. We find that future weak lensing surveys will be able to measure the distinctive IA r...
Shiue, Ren-Jye; Gao, Yuanda; Wang, Yifei; Peng, Cheng; Robertson, Alexander D; Efetov, Dmitri K; Assefa, Solomon; Koppens, Frank H L; Hone, James; Englund, Dirk
2015-11-11
Graphene and other two-dimensional (2D) materials have emerged as promising materials for broadband and ultrafast photodetection and optical modulation. These optoelectronic capabilities can augment complementary metal-oxide-semiconductor (CMOS) devices for high-speed and low-power optical interconnects. Here, we demonstrate an on-chip ultrafast photodetector based on a two-dimensional heterostructure consisting of high-quality graphene encapsulated in hexagonal boron nitride. Coupled to the optical mode of a silicon waveguide, this 2D heterostructure-based photodetector exhibits a maximum responsivity of 0.36 A/W and high-speed operation with a 3 dB cutoff at 42 GHz. From photocurrent measurements as a function of the top-gate and source-drain voltages, we conclude that the photoresponse is consistent with hot electron mediated effects. At moderate peak powers above 50 mW, we observe a saturating photocurrent consistent with the mechanisms of electron-phonon supercollision cooling. This nonlinear photoresponse enables optical on-chip autocorrelation measurements with picosecond-scale timing resolution and exceptionally low peak powers. PMID:26372880
Detecting Anomaly Regions in Satellite Image Time Series Based on Sesaonal Autocorrelation Analysis
Zhou, Z.-G.; Tang, P.; Zhou, M.
2016-06-01
Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1) it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2) it is flexible to meet some requirement (e.g., z-value or significance level) of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3) it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.
A spatial, electro-optical autocorrelation (EOA) interferometer using the vertically polarized lobes of coherent transition radiation (CTR) has been developed as a single-shot electron bunch length monitor at an optical beam port downstream the 100 MeV preinjector LINAC of the Swiss Light Source. This EOA monitor combines the advantages of step-scan interferometers (high temporal resolution) [D. Mihalcea et al., Phys. Rev. ST Accel. Beams 9, 082801 (2006) and T. Takahashi and K. Takami, Infrared Phys. Technol. 51, 363 (2008)] and terahertz-gating technologies [U. Schmidhammer et al., Appl. Phys. B: Lasers Opt. 94, 95 (2009) and B. Steffen et al., Phys. Rev. ST Accel. Beams 12, 032802 (2009)] (fast response), providing the possibility to tune the accelerator with an online bunch length diagnostics. While a proof of principle of the spatial interferometer was achieved by step-scan measurements with far-infrared detectors, the single-shot capability of the monitor has been demonstrated by electro-optical correlation of the spatial CTR interference pattern with fairly long (500 ps) neodymium-doped yttrium aluminum garnet (Nd:YAG) laser pulses in a ZnTe crystal. In single-shot operation, variations of the bunch length between 1.5 and 4 ps due to different phase settings of the LINAC bunching cavities have been measured with subpicosecond time resolution.
SPEECH ENHANCEMENT BASED ON DYNAMIC NOISE ESTIMATION WITHIN AUTO-CORRELATION DOMAIN
吴亚栋; 吴旭辉
2002-01-01
Most noise suppression algorithms of single channel use the mean of noisy segments to estimate the characteristics of noise spectrum, ignoring the estimation of noise in speech segments. Therefore, when the energy level of noise varies with the time, the performance of removing noise will be degraded. To solve this problem, a speech enhancement approach based on dynamic noise estimation within correlation domain was proposed. This method exploits the characteristics that noise energy mainly concentrates on 0 th-order correlation coefficients, signal is auto-correlated but signal and noise, noise and noise are uncorrelated, then estimates and decomposes the noise, thus helps to solve the above-mentioned problem. The results of recognition experiments on speech signals of 15 Chinese cities' names corrupted by noise of exhibition hall shows, this approach is better than SS (Spectral Subtraction) method, adapts better to the variances of energy levels of speech signal corrupted by noise, has some practicability to improve the robustness of recognition systems under noisy environment.
Simultaneous measurement of particle velocity and size based on gray difference and autocorrelation
无
2010-01-01
The gray of two images of a same particle taken by a digital camera with different exposure times is different too. Based on the gray difference of particle images in a double-exposed photo and autocorrelation processing of digital images,this paper proposes a method for measuring particle velocities and sizes simultaneously. This paper also introduces the theoretical foundation of this method,the process of particle imaging and image processing,and the simultaneous measurement of velocity and size of a low speed flow field with 35 μm and 75 μm standard particles. The graphical measurement results can really reflect the flow characteristics of the flow field. In addition,although the measured velocity and size histograms of these two kinds of standard particles are slightly wider than the theoretical ones,they are all still similar to the normal distribution,and the peak velocities and diameters of the histograms are consistent with the default values. Therefore,this measurement method is capable of providing moderate measurement accuracy,and it can be further developed for high-speed flow field measurements.
Fleming, C H; Fagan, W F; Mueller, T; Olson, K A; Leimgruber, P; Calabrese, J M
2016-03-01
An animal's trajectory is a fundamental object of interest in movement ecology, as it directly informs a range of topics from resource selection to energy expenditure and behavioral states. Optimally inferring the mostly unobserved movement path and its dynamics from a limited sample of telemetry observations is a key unsolved problem, however. The field of geostatistics has focused significant attention on a mathematically analogous problem that has a statistically optimal solution coined after its inventor, Krige. Kriging revolutionized geostatistics and is now the gold standard for interpolating between a limited number of autocorrelated spatial point observations. Here we translate Kriging for use with animal movement data. Our Kriging formalism encompasses previous methods to estimate animal's trajectories--the Brownian bridge and continuous-time correlated random walk library--as special cases, informs users as to when these previous methods are appropriate, and provides a more general method when they are not. We demonstrate the capabilities of Kriging on a case study with Mongolian gazelles where, compared to the Brownian bridge, Kriging with a more optimal model was 10% more precise in interpolating locations and 500% more precise in estimating occurrence areas. PMID:27197385
Popkov, Artem
2016-01-01
The article contains information about acoustic emission signals analysing using autocorrelation function. Operation factors were analysed, such as shape of signal, the origins time and carrier frequency. The purpose of work is estimating the validity of correlations methods analysing signals. Acoustic emission signal consist of different types of waves, which propagate on different trajectories in object of control. Acoustic emission signal is amplitude-, phase- and frequency-modeling signal. It was described by carrier frequency at a given point of time. Period of signal make up 12.5 microseconds and carrier frequency make up 80 kHz for analysing signal. Usage autocorrelation function like indicator the origin time of acoustic emission signal raises validity localization of emitters.
Mertens, Kristof; Vaesen, Inge; Löffel, Jenny; Kemps, Bart; Kamers, Bram; Zoons, Johan; Darius, Paul; Decuypere, Eddy; De Baerdemaeker, Josse; Ketelaere, Bart de
2009-01-01
Monitoring livestock production processes by means of statistical control charts can provide an important support for management. The non-stationary and autocorrelated characteristics of most data originating from such processes impede the direct introduction of these data into control charts. To deal with these characteristics Engineering Process Control strategies can be applied. Stationarity was achieved by modelling and subtracting the time dependent trend using a non-linear m...
On the use of the simple and partial Mantel tests in presence of spatial auto-correlation
Guillot, Gilles; Rousset, Francois
2011-01-01
The Mantel test is routinely used in many areas of biology and environmental sciences to assess the signicance of the association between two or more matrices of distances relative to the same pairs of indi- viduals. This test is a valid statistical procedure to test the auto-correlation of a single (possibly multivariate) variable. This includes the widely used test of isolation-by-distance in population genetics. However, we show that contrarily to a widely shared belief, the simple and par...
Passow, Christopher; Hagen, Borge ten; Löwen, Hartmut; Wagner, Joachim
2015-01-01
We provide a theoretical analysis for the intermediate scattering function typically measured in depolarized dynamic light scattering experiments. We calculate the field autocorrelation function $g_1^{\\rm VH}(Q,t)$ in dependence on the wave vector $Q$ and the time $t$ explicitly in a vertical-horizontal scattering geometry for differently shaped solids of revolution. The shape of prolate cylinders, spherocylinders, spindles, and double cones with variable aspect ratio is expanded in rotationa...
Amirataee, Babak; Montaseri, Majid; Sanikhani, Hadi
2015-07-01
Reference evapotranspiration (ET0) is considered a key parameter for evaluating the climatic changes as well as spatial and temporal patterns of parameters influencing the eco-hydrological processes. The analysis of trend variations of this index can be used to determine appropriate strategies in planning and management of water resources. In this paper, the trend variations of monthly and annual ET0 in Urmia Lake basin, located in the northwest of Iran, have been analyzed using data from 14 synoptic stations in the study area. Regarding the significant effect of autocorrelation coefficients with different lags on trend variations of ET0, this paper has resorted to modified Mann-Kendall test via eliminating the significance effect of autocorrelation coefficients with different lags to analyze the trend variations. Furthermore, Theil-Sen estimator has been used to determine the slope of trend line of ET0. The results indicated an increasing trend in ET0 values at all the studied stations. Having used the modified Mann-Kendall test, the values of significant increasing (positive) trend, which were estimated using common Mann-Kendall test, dramatically decreased. As such, the values of only 7 stations have been significant at 95 % level. The results confirmed the need for eliminating the significance effect of autocorrelation coefficients with different lags to determine and evaluate the trend of hydrological variables.
Zhang, Ningyu; Cheng, Chuanfu; Teng, Shuyun; Chen, Xiaoyi; Xu, Zhizhan
2007-09-01
A new approach based on the gated integration technique is proposed for the accurate measurement of the autocorrelation function of speckle intensities scattered from a random phase screen. The Boxcar used for this technique in the acquisition of the speckle intensity data integrates the photoelectric signal during its sampling gate open, and it repeats the sampling by a preset number, m. The average analog of the m samplings output by the Boxcar enhances the signal-to-noise ratio by √{m}, because the repeated sampling and the average make the useful speckle signals stable, while the randomly varied photoelectric noise is suppressed by 1/√{m}. In the experiment, we use an analog-to-digital converter module to synchronize all the actions such as the stepped movement of the phase screen, the repeated sampling, the readout of the averaged output of the Boxcar, etc. The experimental results show that speckle signals are better recovered from contaminated signals, and the autocorrelation function with the secondary maximum is obtained, indicating that the accuracy of the measurement of the autocorrelation function is greatly improved by the gated integration technique.
New speckle analysis method for optical coherence tomography signal based on autocorrelation
De Pretto, Lucas R.; Nogueira, Gesse E. C.; Freitas, Anderson Z.
2015-06-01
Optical Coherence Tomography (OCT) is a noninvasive imaging technique with high resolution widely used for in vivo applications. Nonetheless, OCT is prone to speckle, a granular noise that degrades the OCT signal. Speckle statistics may, nevertheless, reveal information regarding the scatterers from which it originates. This fact is exploited by techniques such as Speckle Variance-OCT (SVOCT). SVOCT, however, doesn't provide quantitative information, which is a major drawback for the use of speckle based techniques on OCT. In the present work we attack this problem, proposing a new method for analysis of speckle in OCT signal, based on autocorrelation. We associate the changes in decorrelation time of the signal with the changes in flow velocity. It is expected that greater velocities result in lower decorrelation times. To verify that, milk was pumped through a microchannel at different velocities, and the decorrelation time was computed for a single point in the center of the microchannel, sampled at 8 kHz rate. Our results suggest that for flows rates greater than 1 μl/min it is possible to associate decorrelation time with flow velocity, while velocities below that value are not distinguishable, supposedly due to the Brownian motion. For flow rates above 50 μl/min our acquisition rate doesn't get enough sampling information, as the decorrelation time gets too low. These results indicate that Speckle based techniques may be used to get quantitative information of flow in OCT samples, which can be used to assist in many diagnostics modalities, as well as map such flow regions.
Paul, Joseph S; Al Nashash, Hasan; Luft, Andreas R; Le, Thinh M
2006-07-01
Statistically mapped speckle autocorrelation images (SAR) were used to track the hemodynamically active perfusion regions in the rat cortex during and following DC current stimulation with high transverse spatial resolution (38 um). The SAR images provided a spatio-temporal information about the net activation patterns of Cerebral Blood Flow (CBF) changes over a period of time as against those changes for each frame interval estimated using spatial contrasts derived from the first order spatial statistics. Thus the information about the relative maxima of perfusion during a Transient Hyperaemic Episode (THE) across different regions in the imaging window could be identified without the need for actually having to estimate the spatial contrast maps of the imaged region for each frame contained in the time window of observation. With the application of DC stimulation, the regions with a high correlation in the temporal fluctuations were representative of the areas that underwent least changes in activation. By varying the intensity of stimulation, THEs were observed for stimulation current densities in the range 0.1-3.8 mA/mm2 using both the derived speckle contrast maps and concurrently on a Laser Doppler Flow meter, with its probe positioned 1 mm from the site of stimulation. For current densities below the lower threshold of stimulation, the SAR images revealed an unprecedented reduction in the surge amplitude at sites distal to the region of stimulation. This was accompanied by an increase in pixel areas representing minimally active regions of perfusion ("perfusion islets") with no identifiable peak in the hemodynamic responses estimated from speckle contrast variations. The SAR images can be a useful tool for visualization of slow wave perfusion dynamics during cortical stimulation. PMID:16786397
Songhurst, Anna; Coulson, Tim
2014-03-01
Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions. PMID:25035800
Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign.
Sliwoski, Gregory; Mendenhall, Jeffrey; Meiler, Jens
2016-03-01
Quantitative structure-activity relationship (QSAR) is a branch of computer aided drug discovery that relates chemical structures to biological activity. Two well established and related QSAR descriptors are two- and three-dimensional autocorrelation (2DA and 3DA). These descriptors encode the relative position of atoms or atom properties by calculating the separation between atom pairs in terms of number of bonds (2DA) or Euclidean distance (3DA). The sums of all values computed for a given small molecule are collected in a histogram. Atom properties can be added with a coefficient that is the product of atom properties for each pair. This procedure can lead to information loss when signed atom properties are considered such as partial charge. For example, the product of two positive charges is indistinguishable from the product of two equivalent negative charges. In this paper, we present variations of 2DA and 3DA called 2DA_Sign and 3DA_Sign that avoid information loss by splitting unique sign pairs into individual histograms. We evaluate these variations with models trained on nine datasets spanning a range of drug target classes. Both 2DA_Sign and 3DA_Sign significantly increase model performance across all datasets when compared with traditional 2DA and 3DA. Lastly, we find that limiting 3DA_Sign to maximum atom pair distances of 6 Å instead of 12 Å further increases model performance, suggesting that conformational flexibility may hinder performance with longer 3DA descriptors. Consistent with this finding, limiting the number of bonds in 2DA_Sign from 11 to 5 fails to improve performance. PMID:26721261
Near surface velocity structure of Pacaya volcano using spatial autocorrelation method
Kenyon, L. M.; Waite, G. P.; Manzoni, P.
2011-12-01
Pacaya Volcano, Guatemala is a basaltic volcano in the Central American arc characterized by persistent degassing and nearly continuous nonharmonic tremor, coupled at times with lava effusion and/or coincident strombolian-style explosions. A moderate (VEI 2-3) eruption on 27 May 2010 destroyed part of the edifice and was followed by the opening of a new vent ~1.6 km south-southeast of the edifice. This change in activity prompted a field campaign, highlighted by the deployment of a small-aperture array of seismometers 1.1 km west of the summit in January 2011. The semi-circular array consisted of 11 short-period three-component seismometers with an aperture of 300 m and irregular radii of about 70 m and 150 m. During the deployment, we recorded primarily narrow-band tremor of volcanic and anthropogenic origin. We used the spatial auto-correlation (SPAC) method to generate band-limited dispersion curves from the tremor data and then inverted the dispersion curves for a velocity model. From 23 - 24 January we identified 16 segments of 300 s each using spectrograms, within which there were no events defined as LP, VLP or VT earthquakes. These were also periods during which there was little narrow-band tremor. The lack of directional dependence on the correlations confirms that there were no strong localized tremor sources. Because the station spacing was not ideal for SPAC analysis, we combined results for seven different radii, with a minimum of 3 station pairs each. The number of station pairs for each radius is given in parentheses after the distance: 73 (6), 82 (3), 100 (4), 133 (4), 145 (4), 153 (4) and 212 m (4). There are a total of 29 pairs of stations. The dispersion curve model found using only the vertical component shows Rayleigh wave velocities ranging from 1200 m/s at 1.5 Hz to 250 m/s at 8 Hz. The observed dispersion curve velocity range is consistent with other previously studied volcanoes where low velocities are found in the top 300 m. An analysis of
2016-01-01
factor of the journal in which a reporting statement was published was shown to influence the number of citations that statement will gather over time. Similarly, the number of article accesses also influenced the number of citations, although to a lesser extent than the impact factor. This demonstrates that citation counts are not purely a reflection of scientific merit and the impact factor is, in fact, auto-correlated. PMID:27069817
Shanahan, Daniel R
2016-01-01
journal in which a reporting statement was published was shown to influence the number of citations that statement will gather over time. Similarly, the number of article accesses also influenced the number of citations, although to a lesser extent than the impact factor. This demonstrates that citation counts are not purely a reflection of scientific merit and the impact factor is, in fact, auto-correlated. PMID:27069817
Rompotis, Dimitrios
2016-02-15
In this work, a single-shot temporal metrology scheme operating in the vacuum-extreme ultraviolet spectral range has been designed and experimentally implemented. Utilizing an anti-collinear geometry, a second-order intensity autocorrelation measurement of a vacuum ultraviolet pulse can be performed by encoding temporal delay information on the beam propagation coordinate. An ion-imaging time-of-flight spectrometer, offering micrometer resolution has been set-up for this purpose. This instrument enables the detection of a magnified image of the spatial distribution of ions exclusively generated by direct two-photon absorption in the combined counter-propagating pulse focus and thus obtain the second-order intensity autocorrelation measurement on a single-shot basis. Additionally, an intense VUV light source based on high-harmonic generation has been experimentally realized. It delivers intense sub-20 fs Ti:Sa fifth-harmonic pulses utilizing a loose-focusing geometry in a long Ar gas cell. The VUV pulses centered at 161.8 nm reach pulse energies of 1.1 μJ per pulse, while the corresponding pulse duration is measured with a second-order, fringe-resolved autocorrelation scheme to be 18 ± 1 fs on average. Non-resonant, two-photon ionization of Kr and Xe and three-photon ionization of Ne verify the fifth-harmonic pulse intensity and indicate the feasibility of multi-photon VUV pump/VUV probe studies of ultrafast atomic and molecular dynamics. Finally, the extended functionally of the counter-propagating pulse metrology approach is demonstrated by a single-shot VUV pump/VUV probe experiment aiming at the investigation of ultrafast dissociation dynamics of O{sub 2} excited in the Schumann-Runge continuum at 162 nm.
In this work, a single-shot temporal metrology scheme operating in the vacuum-extreme ultraviolet spectral range has been designed and experimentally implemented. Utilizing an anti-collinear geometry, a second-order intensity autocorrelation measurement of a vacuum ultraviolet pulse can be performed by encoding temporal delay information on the beam propagation coordinate. An ion-imaging time-of-flight spectrometer, offering micrometer resolution has been set-up for this purpose. This instrument enables the detection of a magnified image of the spatial distribution of ions exclusively generated by direct two-photon absorption in the combined counter-propagating pulse focus and thus obtain the second-order intensity autocorrelation measurement on a single-shot basis. Additionally, an intense VUV light source based on high-harmonic generation has been experimentally realized. It delivers intense sub-20 fs Ti:Sa fifth-harmonic pulses utilizing a loose-focusing geometry in a long Ar gas cell. The VUV pulses centered at 161.8 nm reach pulse energies of 1.1 μJ per pulse, while the corresponding pulse duration is measured with a second-order, fringe-resolved autocorrelation scheme to be 18 ± 1 fs on average. Non-resonant, two-photon ionization of Kr and Xe and three-photon ionization of Ne verify the fifth-harmonic pulse intensity and indicate the feasibility of multi-photon VUV pump/VUV probe studies of ultrafast atomic and molecular dynamics. Finally, the extended functionally of the counter-propagating pulse metrology approach is demonstrated by a single-shot VUV pump/VUV probe experiment aiming at the investigation of ultrafast dissociation dynamics of O2 excited in the Schumann-Runge continuum at 162 nm.
Fu, Z.; Zhang, Z.; Chan, SC
2013-01-01
This paper introduces a new method for adaptively estimating the time-varying autocorrelation (TV-AC) of nonstationary signals and studies its application to time-frequency analysis. The proposed method employs local estimation with a sliding window having a certain bandwidth to estimate the TV-AC locally. The window bandwidths are selected adaptively by a local plug-in rule to address the bias and variance tradeoff problem. Further, based on the proposed adaptive TV-AC estimation, a new time...
Boute, Robert; Disney, Stephen; Lambrecht, Marc; Van Houdt, Benny
2010-01-01
In this paper we study a two-echelon supply chain with a retailer serving a consumer who is sensitive to marketing and pricing promotions. This results in either positively or negatively autocorrelated demand. Based on the observed consumer demand, the retailer replenishes with an adaptive order-up-to inventory policy satisfying a pre-specified fill rate. We assume the manufacturer produces the retailer’s orders on a make-to-order basis and he decides on the lead time based on the retailer...
Mode-coupling theory of the stress-tensor autocorrelation function of a dense binary fluid mixture
Sinha, Supurna; Marchetti, M. Cristina
2005-01-01
We present a generalized mode-coupling theory for a dense binary fluid mixture. The theory is used to calculate molecular-scale renormalizations to the stress-tensor autocorrelation function (STAF) and to the long-wavelength zero-frequency shear viscosity. As in the case of a dense simple fluid, we find that the STAF appears to decay as $t^{-3/2}$ over an intermediate range of time. The coefficient of this long-time tail is more than two orders of magnitude larger than that obtained from conv...
Mei-Yu LEE
2014-11-01
Full Text Available This paper investigates the effect of the nonzero autocorrelation coefficients on the sampling distributions of the Durbin-Watson test estimator in three time-series models that have different variance-covariance matrix assumption, separately. We show that the expected values and variances of the Durbin-Watson test estimator are slightly different, but the skewed and kurtosis coefficients are considerably different among three models. The shapes of four coefficients are similar between the Durbin-Watson model and our benchmark model, but are not the same with the autoregressive model cut by one-lagged period. Second, the large sample case shows that the three models have the same expected values, however, the autoregressive model cut by one-lagged period explores different shapes of variance, skewed and kurtosis coefficients from the other two models. This implies that the large samples lead to the same expected values, 2(1 – ρ0, whatever the variance-covariance matrix of the errors is assumed. Finally, comparing with the two sample cases, the shape of each coefficient is almost the same, moreover, the autocorrelation coefficients are negatively related with expected values, are inverted-U related with variances, are cubic related with skewed coefficients, and are U related with kurtosis coefficients.
Chong, E. Z.; Watson, T. F.; Festy, F., E-mail: frederic.festy@kcl.ac.uk [Biomaterials, Biomimetics and Biophotonics Division, King' s College London—Dental Institute, SE1 9RT London (United Kingdom)
2014-08-11
Semiconductor materials which exhibit two-photon absorption characteristic within a spectral region of interest can be useful in building an ultra-compact interferometric autocorrelator. In this paper, we report on the evidence of a nonlinear absorption process in GaP photodiodes which was exploited to measure the temporal profile of femtosecond Ti:sapphire laser pulses with a tunable peak wavelength above 680 nm. The two-photon mediated conductivity measurements were performed at an average laser power of less than a few tenths of milliwatts. Its suitability as a single detector in a broadband autocorrelator setup was assessed by investigating the nonlinear spectral sensitivity bandwidth of a GaP photodiode. The highly favourable nonlinear response was found to cover the entire tuning range of our Ti:sapphire laser and can potentially be extended to wavelengths below 680 nm. We also demonstrated the flexibility of GaP in determining the optimum compensation value of the group delay dispersion required to restore the positively chirped pulses inherent in our experimental optical system to the shortest pulse width possible. With the rise in the popularity of nonlinear microscopy, the broad two-photon response of GaP and the simplicity of this technique can provide an alternative way of measuring the excitation laser pulse duration at the focal point of any microscopy systems.
Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.
2016-01-01
Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.
Schulte, Stephan
2011-07-11
The history of cosmic rays started in the beginning of the 20th century. Since then one of the main questions is their origin. Due to the very low flux at the highest energies huge areas have to be instrumented to answer this question. For this purpose the distribution of the arrival directions of cosmic rays is studied. The largest experiment so far is the Pierre Auger Observatory, located in the Pampa in western Argentina with an area of about 3000 km{sup 2}. In recent years it provided many major contributions to the field of cosmic ray physics and its data is the basis of this work. Among other things a correlation analysis of Ultra High Energy Cosmic Rays (UHECRs) with Active Galactic Nuclei (AGN) was performed leading to the first evidence that UHECRs are not isotropically distributed. Here the distribution of arrival directions of cosmic rays at the highest energies (>50 EeV) is examined by using autocorrelation methods to check whether it is compatible with the isotropic expectation or not.This thesis is organised as follows: in the first two chapters a short introduction to the topic is given, followed by a more general discussion on cosmic rays including models of acceleration, possible sources and the propagation of UHECRs in the third chapter. The fourth chapter focuses on the detector design of the Pierre Auger Observatory and event reconstruction at highest energies. Special attention is paid to the monitoring of the High Elevation Auger Telescopes (HEAT). It is a low energy enhancement of the observatory consisting of three tiltable fluorescence telescopes. The calibration of the new sensor setups is described as well as the installation in each HEAT shelter. The next chapter starts with a detailed description of the underlying ideas and motivations of autocorrelation methods: a representation of the 2pt-Correlation Function and its extension, a Minimum Spanning Tree and a Cluster Algorithm with different weighting procedures. The principle of each
The history of cosmic rays started in the beginning of the 20th century. Since then one of the main questions is their origin. Due to the very low flux at the highest energies huge areas have to be instrumented to answer this question. For this purpose the distribution of the arrival directions of cosmic rays is studied. The largest experiment so far is the Pierre Auger Observatory, located in the Pampa in western Argentina with an area of about 3000 km2. In recent years it provided many major contributions to the field of cosmic ray physics and its data is the basis of this work. Among other things a correlation analysis of Ultra High Energy Cosmic Rays (UHECRs) with Active Galactic Nuclei (AGN) was performed leading to the first evidence that UHECRs are not isotropically distributed. Here the distribution of arrival directions of cosmic rays at the highest energies (>50 EeV) is examined by using autocorrelation methods to check whether it is compatible with the isotropic expectation or not.This thesis is organised as follows: in the first two chapters a short introduction to the topic is given, followed by a more general discussion on cosmic rays including models of acceleration, possible sources and the propagation of UHECRs in the third chapter. The fourth chapter focuses on the detector design of the Pierre Auger Observatory and event reconstruction at highest energies. Special attention is paid to the monitoring of the High Elevation Auger Telescopes (HEAT). It is a low energy enhancement of the observatory consisting of three tiltable fluorescence telescopes. The calibration of the new sensor setups is described as well as the installation in each HEAT shelter. The next chapter starts with a detailed description of the underlying ideas and motivations of autocorrelation methods: a representation of the 2pt-Correlation Function and its extension, a Minimum Spanning Tree and a Cluster Algorithm with different weighting procedures. The principle of each method
Guarini, E.; Neumann, M.; Bafile, U.; Celli, M.; Colognesi, D.; Bellissima, S.; Farhi, E.; Calzavara, Y.
2016-06-01
Very recently we showed that quantum centroid molecular dynamics (CMD) simulations of the velocity autocorrelation function provide, through the Gaussian approximation (GA), an appropriate representation of the single-molecule dynamic structure factor of liquid H2, as witnessed by a straightforward absolute-scale agreement between calculated and experimental values of the total neutron cross section (TCS) at thermal and epithermal incident energies. Also, a proper quantum evaluation of the self-dynamics was found to guarantee, via the simple Sköld model, a suitable account of the distinct (intermolecular) contributions that influence the neutron TCS of para-H2 for low-energy neutrons (below 10 meV). The very different role of coherent nuclear scattering in D2 makes the neutron response from this liquid much more extensively determined by the collective dynamics, even above the cold neutron range. Here we show that the Sköld approximation maintains its effectiveness in producing the correct cross section values also in the deuterium case. This confirms that the true key point for reliable computational estimates of the neutron TCS of the hydrogen liquids is, together with a good knowledge of the static structure factor, the modeling of the self part, which must take into due account quantum delocalization effects on the translational single-molecule dynamics. We demonstrate that both CMD and ring polymer molecular dynamics (RPMD) simulations provide similar results for the velocity autocorrelation function of liquid D2 and, consequently, for the neutron double differential cross section and its integrals. This second investigation completes and reinforces the validity of the proposed quantum method for the prediction of the scattering law of these cryogenic liquids, so important for cold neutron production and related condensed matter research.
Sofia, Giulia; Marinello, Francesco; Tarolli, Paolo
2014-05-01
Terraces represent an outstanding example that displays centuries of a ubiquitous human-Earth interaction, in a very specific and productive way, and they are a significant part of numerous local economies. They, in fact, optimise the local resources for agricultural purposes, but also exploit marginal landscapes, expanding local populations. The ubiquity, variety, and importance of terraces have motivated studies designed to understand them better both as cultural and ecological features, but also as elements that can deeply influence runoff generation and propagation, contributing to local instabilities, and triggering or aggravating land degradation processes. Their vulnerability in the face of fast-growing urban settlements and the changes in agricultural practices is also well known, prompting protection measures strongly supported by local communities, but also by national and international projects. This work explores the spatial heterogeneity of terraced landscapes, identifying a proper indicator able to discriminate a terraced landscape respect to a more natural one. Recognizing and characterizing terraced areas can offer important multi-temporal insights into issues such as agricultural sustainability, indigenous knowledge systems, human-induced impact on soil degradation or erosive and landslide processes, geomorphological and pedologic processes that influence soil development, and climatic and biodiversity changes. More in detail, the present work introduces a new morphological indicator from LiDAR, effectively implementable for the automatic characterization of terraced landscapes. For the study, we tested the algorithm for environments that differ in term of natural morphology and terracing system. Starting from a LiDAR Digital Terrain Models (DTM), we considered the local auto-correlation (~local self-similarity) of the slope, calculating the correlation between a slope patch and its surrounding areas. We define the resulting map as the "Slope Local
Letcher, Benjamin; Hocking, Daniel; O'Neill, K.; Whiteley, Andrew R.; Nislow, Keith H.; O'Donnell, Matthew
2016-01-01
Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59 °C), identified a clear warming trend (0.63 °C · decade-1) and a widening of the synchronized period (29 d · decade-1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (~ 0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (~ 0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.
Cuoco, A; Haugbølle, T; Kachelrieß, M; Serpico, P D
2009-01-01
We perform an autocorrelation study of the Auger data with the aim to constrain the number density ns of ultrahigh energy cosmic ray (UHECR) sources, estimating at the same time the effect on ns of the systematic energy scale uncertainty and of the distribution of UHECR. The use of global analysis has the advantage that no biases are introduced, either in ns or in the related error bar, by the a priori choice of a single angular scale. The case of continuous, uniformly distributed sources is nominally disfavored at 99% CL and the fit improves if the sources follow the large-scale structure of matter in the universe. The best-fit values obtained for the number density of proton sources are within a factor ~2 around ns 1 × 10–4Mpc–3 and depend mainly on the Auger energy calibration scale, with lower densities being preferred if the current scale is correct. The data show no significant small-scale clustering on scales smaller than a few degrees. This might be interpreted as a signature of magnetic smearing...
HUANG Wei; NAKAMORI Yoshiteru; WANG Shouyang
2004-01-01
Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to finance, time series forecasting is perhaps one of the most challenging issues. Considering the features of neural networks, we propose a general approach called Autocorrelation Criterion (AC) to determine the inputs variables for a neural network. The purpose is to seek optimal lag periods, which are more predictive and less correlated. AC is a data-driven approach in that there is no prior assumption about the models for time series under study. So it has extensive applications and avoids a lengthy experimentation and tinkering in input selection. We apply the approach to the determination of input variables for foreign exchange rate forecasting and conduct comparisons between AC and information-based in-sample model selection criterion. The experiment results show that AC outperforms information-based in-sample model selection criterion.
Sato, Shin-ichi; You, Jin; Jeon, Jin Yong
2007-07-01
Psychoacoustical and autocorrelation function (ACF) parameters were employed to describe the temporal fluctuations of refrigerator noise during starting, transition into/from the stationary phase and termination of operation. The temporal fluctuations of refrigerator noise include a click at start-up, followed by a rapid increase in volume, a change of pitch, and termination of the operation. Subjective evaluations of the noise of 24 different refrigerators were conducted in a real living environment. The relationship between objective measures and perceived noisiness was examined by multiple regression analysis. Sound quality indices were developed based on psychoacoustical and ACF parameters. The psychoacoustical parameters found to be important for evaluating noisiness in the stationary phase were loudness and roughness. The relationship between noisiness and ACF parameters shows that sound energy and its fluctuations are important for evaluating noisiness. Also, refrigerator sounds that had a fluctuation of pitch were rated as more annoying. The tolerance level for the starting phase of refrigerator noise was found to be 33 dBA, which is the level where 65% of the participants in the subjective tests were satisfied. PMID:17614491
D'Orazio, Dario; De Cesaris, Simona; Garai, Massimo
2011-10-01
The "effective duration" of the autocorrelation function (ACF), τ(e), is an important factor in architectural and musical acoustics. For a general application, an accurate evaluation of τ(e) is relevant. This paper is focused to the methods for the extraction of τ(e) values from the ACF. Various methods have been proposed in literature for the extraction of the τ(e) from a given signal, but these methods are not unambiguously defined or may not work properly in case of particular signals. Therefore, the general use of these methods may sometimes give rise to questionable results. In the present work, the methods existing in literature for extracting τ(e) are analyzed, their advantages and drawbacks are summarized, and finally an alternative method is proposed. The proposed algorithm is compared to those found in previous literature, applying them on the same sound signals (classic literature references and other ones publicly available on the Internet). It is shown that the results obtained with the proposed method are consistent with the results of the previous literature; moreover the proposed method may overcome some of the limitations of the existing methods. PMID:21973350
M. A. Demir
2012-04-01
Full Text Available Blind equalization is a technique for adaptive equalization of a communication channel without the use of training sequence. Although the constant modulus algorithm (CMA is one of the most popular adaptive blind equalization algorithms, because of using fixed step size it suffers from slow convergence rate. A novel enhanced variable step size CMA algorithm (VSS-CMA based on autocorrelation of error signal has been proposed to improve the weakness of CMA for application to blind equalization in this paper. The new algorithm resolves the conflict between the convergence rate and precision of the fixed step-size conventional CMA algorithm. Computer simulations have been performed to illustrate the performance of the proposed method in simulated frequency selective Rayleigh fading channels and experimental real communication channels. The obtained simulation results using single carrier (SC IEEE 802.16-2004 protocol have demonstrated that the proposed VSS-CMA algorithm has considerably better performance than conventional CMA, normalized CMA (N-CMA and the other VSS-CMA algorithms.
G A Adebayo; O Akinlade; L A Hussain
2005-02-01
The structures and autocorrelation functions of Al and Mg in the liquid state are investigated through the pair distribution function (), the diffusion coefficients as well as the shear viscosity via the Green{Kubo and Einstein relations. From the structure and the Enskog relation we determined the frequency of collisions of atoms in the first shell of () in the systems. We also discovered that the packing fraction of Lennard-Jones liquids should be approximately half the reduced density value. This approximation is accurate to within 99%. The temperature dependence of the pair distribution function and the atomic mean square displacement are investigated by performing simulations at various experimental temperatures and corresponding densities. The structures of the systems are affected by temperature via movements of atoms in the first minimum of (). The Lennard-Jones model shows that density dependence of the shear viscosity is in agreement with what is expected of simple liquids in the range of investigated temperatures and densities. In the gas limit, the Stoke-Einstein relation = B/2 is grossly overestimated by Lennard-Jones model. This could not be attributed to defficiencies in the model, as other investigators using first principle method could not obtain the gas limit of the Stoke-Einstein relation.
Passow, Christopher; ten Hagen, Borge; Löwen, Hartmut; Wagner, Joachim
2015-07-28
We provide a theoretical analysis for the intermediate scattering function typically measured in depolarized dynamic light scattering experiments. We calculate the field autocorrelation function g1(VH)(Q,t) in dependence on the wave vector Q and the time t explicitly in a vertical-horizontal scattering geometry for differently shaped solids of revolution. The shape of prolate cylinders, spherocylinders, spindles, and double cones with variable aspect ratio is expanded in rotational invariants flm(r). By Fourier transform of these expansion coefficients, a formal multipole expansion of the scattering function is obtained, which is used to calculate the weighting coefficients appearing in the depolarized scattering function. In addition to translational and rotational diffusion, especially the translational-rotational coupling of shape-anisotropic objects is considered. From the short-time behavior of the intermediate scattering function, the first cumulants Γ(Q) are calculated. In a depolarized scattering experiment, they deviate from the simple proportionality to Q(2). The coefficients flm(Q) strongly depend on the geometry and aspect ratio of the particles. The time dependence, in addition, is governed by the translational and rotational diffusion tensors, which are calculated by means of bead models for differently shaped particles in dependence on their aspect ratio. Therefore, our analysis shows how details of the particle shape--beyond their aspect ratio--can be determined by a precise scattering experiment. This is of high relevance in understanding smart materials which involve suspensions of anisotropic colloidal particles. PMID:26233160
An electrodynamic problem of laser radiation scattering in an integrated-optical waveguide containing small statistical irregularities (interface roughness and irregularities of the refractive indices of the waveguide-forming media) is considered. The possibility of using the waveguide scattering of laser radiation for extracting the information on the statistical properties of irregularities from noisy data of the scattering diagram in a far-field zone is shown. An algorithm for reconstructing the autocorrelation function of irregularities for the correlation interval changing within a wide range is described. The possibility of restoring a given Gaussian autocorrelation function that describes statistical irregularities of the waveguide substrate surface for a correlation interval changing between 10 nm and 10 μm and a high-level additive white real noise is shown by computer simulation. (laser applications and other topics in quantum electronics)
Stein, A.; Ewert, Stephan; Wiegrebe, L.
2005-01-01
, autocorrelation is applied. Considering the large overlap in pitch and modulation perception, this is not parsimonious. Two experiments are presented to investigate the interaction between carrier periodicity, which produces strong pitch sensations, and envelope periodicity using broadband stimuli. Results show......Recent temporal models of pitch and amplitude modulation perception converge on a relatively realistic implementation of cochlear processing followed by a temporal analysis of periodicity. However, for modulation perception, a modulation filterbank is applied whereas for pitch perception...
The possibility of using the waveguide scattering of laser radiation for obtaining information on the statistical properties of irregularities from the noisy data obtained in the far-field zone is shown. A complex algorithm for reconstructing the experimental autocorrelation function of the surface roughness of an integrated-optical waveguide substrate is described. This algorithm is based on a combination of the classical regularisation and quasi-optimal filtering. (waveguides)
Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian
2015-01-01
This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p railway (OR = 0.980, p prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446
Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian
2015-12-01
This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p railway (OR = 0.980, p prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446
Highlights: • We apply the equivalent and autocorrelation widths and variance to XPS narrow scans. • This approach is complementary to traditional peak fitting methods. • It is bias free and responsive to subtle chemical changes in spectra. • It has the potential for machine interpretation of spectra and quality control. • It has the potential for analysis of complex spectra and tracking charging/artifacts. - Abstract: X-ray photoelectron spectroscopy (XPS) is widely used in surface and materials laboratories around the world. It is a near surface technique, providing detailed chemical information about samples in the form of survey and narrow scans. To extract the maximum amount of information about materials it is often necessary to peak fit XPS narrow scans. And while indispensable to XPS data analysis, even experienced practitioners can struggle with their peak fitting. In our previous publication, we introduced the equivalent width (EWXPS) as both a possible machine automated method, one that requires less expert judgment for characterizing XPS narrow scans, and as an approach that may be well suited for the analysis of complex spectra. The EWXPS figure of merit was applied to four different data sets. However, as previously noted, other width functions are also regularly employed for analyzing functions. Here we evaluate two other width functions for XPS narrow scan analysis: the autocorrelation width (AWXPS) and the variance (σXPS2). These widths were applied to the same four sets of spectra studied before: (a) four C 1s narrow scans of ozone-treated carbon nanotubes (CNTs) (EWXPS: ∼2.11–2.16 eV, AWXPS: ∼3.9–4.1 eV, σXPS2: ∼5.0–5.2 eV, and a modified form of σXPS2, denoted σXPS2*: ∼6.3–6.8 eV), (b) silicon wafers with different oxide thicknesses (EWXPS: ∼1.5–2.9 eV, AWXPS: ∼2.28–4.9, and σXPS2: ∼0.7–4.9 eV), (iii) hydrogen-terminated silicon surfaces, before and after modification with pentyl groups, and after
Caballero, Julio; Fernández, Michael; González-Nilo, Fernando D
2008-06-01
2D autocorrelation, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were undertaken for a series of pyrido[2,3-d]pyrimidin-7-ones to correlate cyclin-dependent kinase (CDK) cyclin D/CDK4 inhibition with 2D and 3D structural properties of 60 known compounds. QSAR models with considerable internal as well as external predictive ability were obtained. The relevant 2D autocorrelation descriptors for modeling CDK4/D inhibitory activity were selected by linear and nonlinear genetic algorithms (GAs) using multiple linear regression (MLR) and Bayesian-regularized genetic neural network (BRGNN) approaches, respectively. Both models showed good predictive statistics; but BRGNN model enables better external predictions. A weight-based input ranking scheme and Kohonen self-organized maps (SOMs) were carried out to interpret the final net weights. The 2D autocorrelation space brings different descriptors for CDK4/D inhibition, and suggests the atomic properties relevant for the inhibitors to interact with CDK4/D active site. CoMFA and CoMSIA analyses were developed with a focus on interpretative ability using coefficient contour maps. CoMSIA produced significantly better results. The results indicate a strong correlation between the inhibitory activity of the modeled compounds and the electrostatic and hydrophobic fields around them. PMID:18468903
Benjamin G. Jacob
2010-05-01
Full Text Available Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multidrug resistant tuberculosis (MDR-TB analyses as considerable random error can occur. Therefore, when MDR-TB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e. the Moran’s coefficient was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird (spatial resolution = 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centres, using a 10 m2 grid-based algorithm. Geographical information system (GIS- gridded measurements of each health centre were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM to determine terrain covariates associated with the sampled MDRTB covariates. Pearson’s correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS® module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases, using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non
Tura Andrea
2012-02-01
Full Text Available Abstract Background Symmetry and regularity of gait are essential outcomes of gait retraining programs, especially in lower-limb amputees. This study aims presenting an algorithm to automatically compute symmetry and regularity indices, and assessing the minimum number of strides for appropriate evaluation of gait symmetry and regularity through autocorrelation of acceleration signals. Methods Ten transfemoral amputees (AMP and ten control subjects (CTRL were studied. Subjects wore an accelerometer and were asked to walk for 70 m at their natural speed (twice. Reference values of step and stride regularity indices (Ad1 and Ad2 were obtained by autocorrelation analysis of the vertical and antero-posterior acceleration signals, excluding initial and final strides. The Ad1 and Ad2 coefficients were then computed at different stages by analyzing increasing portions of the signals (considering both the signals cleaned by initial and final strides, and the whole signals. At each stage, the difference between Ad1 and Ad2 values and the corresponding reference values were compared with the minimum detectable difference, MDD, of the index. If that difference was less than MDD, it was assumed that the portion of signal used in the analysis was of sufficient length to allow reliable estimation of the autocorrelation coefficient. Results All Ad1 and Ad2 indices were lower in AMP than in CTRL (P Conclusions Without the need to identify and eliminate the phases of gait initiation and termination, twenty strides can provide a reasonable amount of information to reliably estimate gait regularity in transfemoral amputees.
We show how to implement stick boundary conditions for a spherical colloid in a solvent that is coarse-grained by the method of stochastic rotation dynamics. This allows us to measure colloidal rotational velocity auto-correlation functions by direct computer simulation. We find quantitative agreement with Enskog theory for short times and with hydrodynamic mode-coupling theory for longer times. For aqueous colloidal suspensions, the Enskog contribution to the rotational friction is larger than the hydrodynamic one when the colloidal radius drops below 35 nm
Nielsen, Erland Hejn
2004-01-01
situation or at least a very sound approximation. However, on the other hand, most actual decision making is based upon information taken from the past - where else! In fact the only real alternative that comes into my mind is to let a pair of dices fully and completely rule behaviour, but I wonder...... some arrival processes for some simulation study a thorough preliminary analysis has to be undertaken in order to uncover the basic time series nature of the interacting processes. Flexible methods for generating streams of autocorrelated variates of any desired distributional type, such as the ARTA...
Wen Dong
2015-12-01
Full Text Available This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9 human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001, migration route (OR = 0.993, p < 0.01, river (OR = 0.861, p < 0.001, lake(OR = 0.992, p < 0.001, road (OR = 0.906, p < 0.001, railway (OR = 0.980, p < 0.001, temperature (OR = 1.170, p < 0.01, precipitation (OR = 0.615, p < 0.001 and relative humidity (OR = 1.337, p < 0.001. The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101 of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70 of the predictive risk map, whereas 44.6% (45/101 of which overlaid on the high risk areas (the predictive risk > 0.70 for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%. The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9 human infections in February 2014. These results provided baseline data for the control and prevention of future human infections.
Mitzner, R.; Sorokin, A. A.; Siemer, B.; Roling, S.; Rutkowski, M.; Zacharias, H.; Neeb, M.; Noll, T.; Siewert, F.; Eberhardt, W.; Richter, M.; Juranic, P.; Tiedtke, K.; Feldhaus, J.
2009-08-01
The pulse duration of soft x-ray free-electron laser (FEL) radiation is directly measured by time-resolved observation of doubly charged helium ions at 51.8 eV. A wave front splitting autocorrelator produces two correlated FEL pulses with a resolution of better than a femtosecond. In the interesting intensity range from 1013 to 1016W/cm2 direct and sequential double ionization contribute to the ion yield which has significant influence on the correlation width, being a general feature at high photon energies. Here, a duration of τL=(29±5)fs is derived for the soft x-ray pulses at FLASH.
A program package was developed to estimate the time dependent auto-correlation function (ACF) from the time signals of soft X-ray records taken along the various lines-of-sights in JET-SHOTS, and also to estimate the time dependent Decay Ratio (DR) from that. On the basis of ACF the time dependent auto-power spectral density (APSD) was also calculated. The steps and objectives of this work were: eliminating the white detection noise, trends and slow variation from the time signals, since ordinary methods can give good estimate of the time dependent ACF and DR only for 'nearly' stationary signals, developing an automatic algorithm for finding the maxima and minima of ACF, since they are the basis for DR estimation, evaluating and testing different DR estimators for JET-SHOT, with the aim of finding parts of the signals, where the oscillating character is strong, estimating time dependent ACF and APSD that can follow the relatively fast variation in the time signal. The methods that we have developed for data processing of transient signals are: White detection noise removal and preparation for trend removal - weak components, white detection noise and high frequency components are filtered from the signal using the so-called soft-threshold wavelet filter. Removal of trends and slow variation - Three-point differentiation of the pre-filtered signal is used to remove trends and slow variation. Here we made use of the DERIV function of IDL program language. This leads to a filtered signal that has zero mean value in each time step. Calculation of the time dependent ACF - The signal treated by the two previous steps is used as the input. Calculated ACF value is added in each new time step, but the previously accumulated ACF value is multiplied by a weighting factor. Thus the new sample has 100% contribution, while the contributions from the previous samples are forgotten quickly. DR calculation - DR is a measure of the decay of oscillating ACF. This parameter was shown
带有测量误差的相关数据的CUSUM控制图%The CUSUM Control Chart for the Autocorrelated Data with Measurement Error
刘晓红; 王兆军
2009-01-01
As we know, the measurement error often exists in practice, and affects the performance of quality control in some cases. The autoregressive process with the measurement error is investigated in this paper. For detecting the step shift of the autoregressive process mean with measurement error, a CUSUM control chart based on the maximum log-likelihood ratio test is obtained. Simulated in-control and out-of-control ARL's are made for various measurement error and autocorrelation coefficients. The simulation results show that this new CUSUM scheme works well when the process is negatively autocorrelated.%实际中测量误差不仅存在而且在某些情况下还影响质量摔制的表现,本文将考虑带有测量误差的相关数据的监控问题.为检测这类数据的飘移,我们给出了一个基于极大似然比检验的CUSUM控制图及其多种情况下的可控与失控的ARL.模拟结果显示,当过程负相关时,我们提出的CUSUM控制图具有良好的表现.
Johnson, Joseph F
2011-01-01
We give Sir James Jeans's notion of 'normal state' a mathematically precise definition. We prove that normal cells of trajectories exist in the Hamiltonian heat-bath model of an assembly of linearly coupled oscillators that generates the Ornstein--Uhlenbeck process in the limit of an infinite number of degrees of freedom. This, in some special cases, verifies some far-reaching conjectures of Khintchine on the weak ergodicity of a dynamical system with a large number of degrees of freedom. In order to estimate the theoretical auto-correlation function of a time series from the sample auto-correlation function of one of its realisations, it is usually assumed without justification that the time series is ergodic. Khintchine's conjectures about dynamical systems with large numbers of degrees of freedom justifies, even in the absence of ergodicity, approximately the same conclusions. Para emplear el correlograma de los valores muestrales de un proceso estoc\\'astico para estimar su funci\\'on te\\'orica de autocorre...
Lunedei, Enrico; Albarello, Dario
2016-03-01
Synthetic dispersion curves are here computed in the frame of an ambient-vibration full-wavefield model, which relies on the description of both ambient-vibration ground displacement and its sources as stochastic fields defined on the Earth's surface, stationary in time and homogeneous in space. In this model, previously developed for computing synthetic Horizontal-to-Vertical Spectral Ratio curves, the power spectral density function and the spatial autocorrelation of the displacement are naturally described as functions of the power spectral density function of the generating forces and of the subsoil properties (via the relevant Green's function), by also accounting for spatial correlation of these forces. Dispersion curves are computed from the displacement power spectral density function and from the spatial autocorrelation according with the well-known f-k and SPAC techniques, respectively. Two examples illustrate the way this new ambient-vibration model works, showing its possible use in better understanding the role of the surface waves in forming the dispersion curves, as well as its capability to capture some remarkable experimental findings.
Kim, Joo Gon; Mukherjee, Santanu; Bates, Alex; Zickel, Benjamin; Park, Sam; Son, Byung Rak; Choi, Jae Sung; Kwon, Osung; Lee, Dong Ha; Chung, Hyun-Youl
2015-12-01
Proton exchange membrane fuel cells are a promising energy conversion device which can help to solve urgent environmental and economic problems. Among the various types of fuel cells, the air breathing proton exchange membrane fuel cell, which minimizes the balance of plant, has drawn a lot of attention due to its superior energy density. In this study a compact, air breathing, proton exchange membrane fuel cell based on Nafion and a Pt/C membrane electrode assembly was designed. The fuel cell was tested using a Scribner Associates 850e fuel cell test station. Specifically, the hydrogen fuel and oxygen starvation of the fuel cell were accurately and systematically tested and analyzed using a frequency analysis method which can analyze the input and output frequency. The analysis of the frequency variation under a fuel starvation condition was done using RMSF (root mean square frequency) and ACSD (autocorrelation standard deviation). The study reveals two significant results: first, the fuel starvations show entirely different phenomenon in both RMSF and ACSD and second, the results of the Autocorrelation show clearer results for fuel starvation detection than the results with RMSF.
Maiheu, Bino; Nele, Veldeman; Janssen, Stijn; Fierens, Frans; Trimpeneers, Elke
2010-05-01
RIO is an operational air quality interpolation model developed by VITO and IRCEL-CELINE and produces hourly maps for different pollutant concentrations such as O3, PM10 and NO2 measured in Belgium [1]. The RIO methodology consists of residual interpolation by Ordinary Kriging of the residuals of the measured concentrations and pre-determined trend functions which express the relation between land cover information derived from the CORINE dataset and measured time-averaged concentrations [2]. RIO is an important tool for the Flemish administration and is among others used to report, as is required by each member state, on the air quality status in Flanders to the European Union. We feel that a good estimate of the uncertainty of the yearly average concentration maps and the probability of norm-exceedance are both as important as the values themselves. In this contribution we will discuss the uncertainties specific to the RIO methodology, where we have both contributions from the Ordinary Kriging technique as well as the trend functions. Especially the parameterisation of the uncertainty w.r.t. the trend functions will be the key indicator for the degree of confidence the model puts into using land cover information for spatial interpolation of pollutant concentrations. Next, we will propose a method which enables us to calculate the uncertainty on the yearly average concentrations as well as the number of exceedance days, taking into account the temporal auto-correlation of the concentration fields. It is clear that the autocorrelation will have a strong impact on the uncertainty estimation [3] of yearly averages. The method we propose is based on a Monte Carlo technique that generates an ensemble of interpolation maps with the correct temporal auto-correlation structure. From a generated ensemble, the calculation of norm-exceedance probability at each interpolation location becomes quite straightforward. A comparison with the ad-hoc method proposed in [3], where
The combination of lag-k autocorrelation coefficients (LCCs) and thermogravimetric analyzer (TGA) equipment is defined here as a tool to detect and quantify adulterations of extra virgin olive oil (EVOO) with refined olive (ROO), refined olive pomace (ROPO), sunflower (SO) or corn (CO) oils, when the adulterating agents concentration are less than 14%. The LCC is calculated from TGA scans of adulterated EVOO samples. Then, the standardized skewness of this coefficient has been applied to classify pure and adulterated samples of EVOO. In addition, this chaotic parameter has also been used to quantify the concentration of adulterant agents, by using successful linear correlation of LCCs and ROO, ROPO, SO or CO in 462 EVOO adulterated samples. In the case of detection, more than 82% of adulterated samples have been correctly classified. In the case of quantification of adulterant concentration, by an external validation process, the LCC/TGA approach estimates the adulterant agents concentration with a mean correlation coefficient (estimated versus real adulterant agent concentration) greater than 0.90 and a mean square error less than 4.9%.
Stopher, Katie V; Walling, Craig A; Morris, Alison; Guinness, Fiona E; Clutton-Brock, Tim H; Pemberton, Josephine M; Nussey, Daniel H
2012-08-01
Social structure, limited dispersal, and spatial heterogeneity in resources are ubiquitous in wild vertebrate populations. As a result, relatives share environments as well as genes, and environmental and genetic sources of similarity between individuals are potentially confounded. Quantitative genetic studies in the wild therefore typically account for easily captured shared environmental effects (e.g., parent, nest, or region). Fine-scale spatial effects are likely to be just as important in wild vertebrates, but have been largely ignored. We used data from wild red deer to build "animal models" to estimate additive genetic variance and heritability in four female traits (spring and rut home range size, offspring birth weight, and lifetime breeding success). We then, separately, incorporated spatial autocorrelation and a matrix of home range overlap into these models to estimate the effect of location or shared habitat on phenotypic variation. These terms explained a substantial amount of variation in all traits and their inclusion resulted in reductions in heritability estimates, up to an order of magnitude up for home range size. Our results highlight the potential of multiple covariance matrices to dissect environmental, social, and genetic contributions to phenotypic variation, and the importance of considering fine-scale spatial processes in quantitative genetic studies. PMID:22834741
Zamani, Reza; Mirabbasi, Rasoul; Abdollahi, Sajjad; Jhajharia, Deepak
2016-03-01
Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann-Kendall tests, including (i) Mann-Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann-Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil-Sen's estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann-Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.
A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The report describes not only the method but also documents comprehensively the used and developed FORTRAN codes. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. The ACF of each model, corrected for signal filtering and with the inclusion of a background term under the peak in the PSD, is then least-squares fitted to the ACF estimated on the previously filtered neutron signals, in order to determine the oscillation frequency and the decay ratio. The procedures of filtering and ACF estimation use fast Fourier transform techniques with signal segmentation. Gliding 'short-time' ACF estimates along a signal record allow the evaluation of uncertainties. Some numerical results are given which have been obtained from neutron signal data offered by the recent Forsmark I and Forsmark II NEA benchmark project. They are compared with those from other benchmark participants using different other analysis methods. (author)
Behringer, K
2001-08-01
A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The report describes not only the method but also documents comprehensively the used and developed FORTRAN codes. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. The ACF of each model, corrected for signal filtering and with the inclusion of a background term under the peak in the PSD, is then least-squares fitted to the ACF estimated on the previously filtered neutron signals, in order to determine the oscillation frequency and the decay ratio. The procedures of filtering and ACF estimation use fast Fourier transform techniques with signal segmentation. Gliding 'short-time' ACF estimates along a signal record allow the evaluation of uncertainties. Some numerical results are given which have been obtained from neutron signal data offered by the recent Forsmark I and Forsmark II NEA benchmark project. They are compared with those from other benchmark participants using different other analysis methods. (author)
Although exogenous factors such as pollutants can act on endogenous drivers (e.g. dispersion) of populations and create spatially autocorrelated distributions, most statistical techniques assume independence of error terms. As there are no studies on metal soil pollutants and microarthropods that explicitly analyse this key issue, we completed a field study of the correlation between Oribatida and metal concentrations in litter, organic matter and soil in an attempt to account for spatial patterns of both metals and mites. The 50-m wide study area had homogenous macroscopic features, steep Pb and Cu gradients and high levels of Zn and Cd. Spatial models failed to detect metal-oribatid relationships because the observed latitudinal and longitudinal gradients in oribatid assemblages were independent of the collinear gradients in the concentration of metals. It is therefore hypothesised that other spatially variable factors (e.g. fungi, reduced macrofauna) affect oribatid assemblages, which may be influenced by metals only indirectly. - Small-scale spatial analysis suggests that metal pollution in soil may not directly affect the distribution of oribatid mites.
Caruso, Tancredi, E-mail: tancredicaruso@unisi.i [Department of Environmental Sciences ' G. Sarfatti' , University of Siena, via P.A. Mattioli no 4, 53100 Siena (Italy); Migliorini, Massimo [Department of Evolutionary Biology, University of Siena, via A. Moro no 2, 53100 Siena (Italy); Bucci, Charlie; Bargagli, Roberto [Department of Environmental Sciences ' G. Sarfatti' , University of Siena, via P.A. Mattioli no 4, 53100 Siena (Italy)
2009-11-15
Although exogenous factors such as pollutants can act on endogenous drivers (e.g. dispersion) of populations and create spatially autocorrelated distributions, most statistical techniques assume independence of error terms. As there are no studies on metal soil pollutants and microarthropods that explicitly analyse this key issue, we completed a field study of the correlation between Oribatida and metal concentrations in litter, organic matter and soil in an attempt to account for spatial patterns of both metals and mites. The 50-m wide study area had homogenous macroscopic features, steep Pb and Cu gradients and high levels of Zn and Cd. Spatial models failed to detect metal-oribatid relationships because the observed latitudinal and longitudinal gradients in oribatid assemblages were independent of the collinear gradients in the concentration of metals. It is therefore hypothesised that other spatially variable factors (e.g. fungi, reduced macrofauna) affect oribatid assemblages, which may be influenced by metals only indirectly. - Small-scale spatial analysis suggests that metal pollution in soil may not directly affect the distribution of oribatid mites.
Simonsen, I.; Hetland, Ø. S.; Kryvi, J. B.; Maradudin, A. A.
2016-04-01
An expression is obtained on the basis of phase perturbation theory for the contribution to the mean differential reflection coefficient from the in-plane co-polarized component of the light scattered diffusely from a two-dimensional randomly rough dielectric surface when the latter is illuminated by s -polarized light. This result forms the basis for an approach to inverting experimental light-scattering data to obtain the normalized-surface-height autocorrelation function of the surface. Several parametrized forms of this correlation function, and the minimization of a cost function with respect to the parameters defining these representations, are used in the inversion scheme. This approach also yields the rms height of the surface roughness, and the dielectric constant of the dielectric substrate if it is not known in advance. The input data used in validating this inversion consist of computer simulation results for surfaces defined by exponential and Gaussian surface-height correlation functions, without and with the addition of multiplicative noise, for a single or multiple angles of incidence. The reconstructions obtained by this approach are quite accurate for weakly rough surfaces, and the proposed inversion scheme is computationally efficient.
José Carlos Pereira; Arthur Oscar Schelp; Arlindo Neto Montagnoli; Ana Rita Gatto; André Augusto Spadotto; Lídia Raquel de Carvalho
2006-01-01
OBJECTIVE: To evaluate the maximum residual signal auto-correlation also known as pitch amplitude (PA) values in patients with Parkinson’s disease (PD) patients. METHOD: The signals of 21 Parkinson’s patients were compared with 15 healthy individuals, divided according age and gender. RESULTS: Statistical difference was seen between groups for PA, 0.39 for controls and 0.25 for PD. Normal value threshold was set as 0.3; (p
By using regular time-steps we define discrete-time random walks and flights on subordinate (directed) Continuous-Time Hierarchical (or Weierstrass-Mandelbrot) Walks and Flights, respectively. The obtained results can be considered as a kind of warning that indicates some persistent, nonlinear, long-term autocorrelations (artifacts) accompanying the recording of empirical high-frequency financial (and probably other types of) time-series by regular time-steps, indeed. (author)
Davarpanah, A.; Babaie, H. A.; Dai, D.
2013-12-01
Two systems of full and half grabens have been forming since the mid-Tertiary through tectonic and thermally induced extensional events in SW Montana and neighboring SE Idaho. The earlier mid-Tertiary Basin and Range (BR) tectonic event formed the NW- and NE-striking mountains around the Snake River Plain (SRP) in Idaho and SW Montana, respectively. Since the mid-Tertiary, partially synchronous with the BR event, diachronous bulging and subsidence due to the thermally induced stress field of the Yellowstone hotspot (YHS) has produced the second system of variably-oriented grabens through faulting across the older BR fault blocks. The track of the migration of the YHS is defined by the presence of six prominent volcanic calderas along the SRP which become younger toward the present location of the YHS. Graben basins bounded by both the BR faults and thermally induced cross-faults (CF) systems are now filled with Tertiary-Quaternary clastic sedimentary and volcanic-volcaniclastic rocks. Neogene mafic and felsic lava which erupted along the SRP and clastic sedimentary units (Sixmile Creek Fm., Ts) deposited in both types of graben basins were classified based on their lithology and age, and mapped in ArcGIS 10 as polygon using a combination of MBMG and USGS databases and geological maps at scales of 1:250.000, 1:100,000, and 1:48,000. The spatio-temporal distributions of the lava polygons were then analyzed applying the Global and Local Moran`s I methods to detect any possible spatial or temporal autocorrelation relative to the track of the YHS. The results reveal the spatial autocorrelation of the lithology and age of the Neogene lavas, and suggest a spatio-temporal sequence of eruption of extrusive rocks between Miocene and late Pleistocene along the SRP. The sequence of eruptions, which progressively becomes younger toward the Yellowstone National Park, may track the migration of the YSH. The sub-parallelism of the trend of the SRP with the long axis of the
陈小勇
2001-01-01
Genetic structure is defined as non-random distribution of genetic variation, and this study utilised spatial autocorrelation analysis to analyse variation among genotypes in a single population as, especially for within deme analysis, it is better than F-statistics or GST. The genotype of all individuals ≥2.5 cm DBH in a western Huangshan population of Cyclobalanopsis glauca was detected using allozyme analysis, and spatial autocorrelation of each allele was then analyzed using Moran's I. Most Moran's I values for alleles were larger than expected values, but two of the alleles had significant positive spatial autocorrelation. Detailed analysis showed that most alleles were significantly spatial-autocorrelated at short distances. A correlogram showed positive spatial autocorrelation in all alleles except Est-2-d at short distances (0-5 m). In general, Moran's I indices decreased as distance interval increased. However, the trends of different alleles varied, and therefore no dominant evolutionary factors could be identified.%以黄山一青冈(Cyclobalanopsis glauca)种群为例，研究了种群内等位基因的空间格局。在种群内，大多数等位基因的Moran's I 指数大于期望值，但只有两个等位基因存在显著的正空间自相关；如果考虑不同的无性系分株时，大多数等位基因在短距离内存在显著的空间自相关。相关图表明不同距离间隔，Moran's I 指数变化无规律，表明没有哪个进化因子起决定作用，但无性系繁殖在空间自相关中起重要作用，尤其是在近距离。
Gupta, S.; Vierkant, G. P.
2014-09-01
The evolution of the surface roughness of growing metal or semiconductor thin films provides much needed information about their growth kinetics and corresponding mechanism. While some systems show stages of nucleation, coalescence, and growth, others exhibit varying microstructures for different process conditions. In view of these classifications, we report herein detailed analyses based on atomic force microscopy (AFM) characterization to extract the surface roughness and growth kinetics exponents of relatively low boron-doped diamond (BDD) films by utilizing the analytical power spectral density (PSD) and autocorrelation function (ACF) as mathematical tools. The machining industry has applied PSD for a number of years for tool design and analysis of wear and machined surface quality. Herein, we present similar analyses at the mesoscale to study the surface morphology as well as quality of BDD films grown using the microwave plasma-assisted chemical vapor deposition technique. PSD spectra as a function of boron concentration (in gaseous phase) are compared with those for samples grown without boron. We find that relatively higher boron concentration yields higher amplitudes of the longer-wavelength power spectral lines, with amplitudes decreasing in an exponential or power-law fashion towards shorter wavelengths, determining the roughness exponent ( α ≈ 0.16 ± 0.03) and growth exponent ( β ≈ 0.54), albeit indirectly. A unique application of the ACF, which is widely used in signal processing, was also applied to one-dimensional or line analyses (i.e., along the x- and y-axes) of AFM images, revealing surface topology datasets with varying boron concentration. Here, the ACF was used to cancel random surface "noise" and identify any spatial periodicity via repetitive ACF peaks or spatially correlated noise. Periodicity at shorter spatial wavelengths was observed for no doping and low doping levels, while smaller correlations were observed for relatively
Huesca, Margarita; Merino-de-Miguel, Silvia; Eklundh, Lars; Litago, Javier; Cicuéndez, Victor; Rodríguez-Rastrero, Manuel; Ustin, Susan L.; Palacios-Orueta, Alicia
2015-12-01
Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of "optical types" (OT), meaning "optically distinguishable functional types", as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation. This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MODIS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found. Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less
刘春国; 高松峰; 卢晓峰
2012-01-01
The maximum autocorrelation factor is a statistical calculation method of multivariate image based on the principal component analysis and spatial correlation of remote sensing imagery.The maximum autocorrelation factor transformation of multivariate remotely sensing imagery will produce uncorrelated components among all bands,which are ordered according to the degree of spatial autocorrelation.The mathematic principles of this method are present in this paper.Its advantage ouer principal component analysis is exhibited through a case of hyperspectral imagery processing.The recent developments of its applications in remotely sensing imagery analysis are reviewed.And at last,an outlook of its application to other fields like multi-temporal radar images backscatter coefficient change detection is prospected.%最大自相关因子方法是一种基于遥感影像空间相关性和主成分分析的多元图像统计计算方法.对多元遥感影像进行最大自相关因子变换,可生成波段间互不相关的、按空间相关性大小排序的数据分量.介绍了最大自相关因子方法的数学原理,以高光谱影像数据处理为例展示了最大自相关因子相对于主成分分析的优势,综述了近年来最大自相关因子方法在遥感影像分析应用中的研究进展.并对该方法在多时相雷达影像后向散射系数变化检测等研究方向的应用前景进行了展望.
Positron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone. Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT. Experiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images. The most important
Sumi C
2011-08-01
Full Text Available Chikayoshi Sumi, Kunio ShimizuDepartment of Information and Communication Sciences, Faculty of Science and Technology, Sophia University, Chiyoda, Tokyo, JapanAbstract: Comparison of the measurement accuracy of elasticity was performed through agar phantom experiments, ie, two-dimensional (2D strain tensor components and 2D shear modulus reconstruction obtained by previously developed multidimensional displacement vector measurement methods on the basis of autocorrelation and Doppler methods (2D AM and 2D DM and the corresponding 1D methods. The multidimensional methods yield more accurate and stable results than the corresponding 1D methods. As is shown, however, such 1D methods can also be used when the echo signal-to-noise ratio is high, eg, obtainable by previously developed lateral modulation with parabolic apodizations.Keywords: ultrasound, lateral modulation, displacement vector measurement, accuracy, multidimensional methods, one-dimensional methods, tissue elasticity, strain tensor, shear modulus, agar phantom experiment
Matsuoka, T.; Umezawa, N. [Saitama Institute of Environmental Pollution, Saitama (Japan)
1996-05-01
To render the spatial autocorrelation (SAC) method easier to use, a system has been constructed that can be used with ease on the site for the calculation of phase velocities. This system can perform two observation methods of the same frequency characteristics, that is, the simultaneous multi-point observation and one-point independent observation. The pickup is a velocity type seismograph of a natural period of 1 second that has been so electrically adjusted as to work on an apparent natural period of 7 seconds. Among the frequency characteristics, those related to phase are regarded as important because the SAC method is based on the measurement of coherence between two points. The analysis software runs on a waveform processing software DADiSP/WIN designed for personal computers. To know the operability of this system on the site and to accumulate records using the SAC method, observations were made at the depth of 100-500m at 6 locations in Saitama Prefecture where the underground structure was known thanks to prior PS logging. As the result, a dispersion curve was obtained by use of an array of appropriate dimensions at every location agreeing with the underground structure. 9 refs., 10 figs.
卞鸿雁; 任志远
2011-01-01
应用1978~2008年关中—天水的农业经济数据,运用空间自相关模型对关中—天水经济区的LCCI进行分析.结果表现出：关中—天水经济区耕地面积迅速下降,人口迅速膨胀,LCCI的空间分布格局为＂城市高,农村低,西高东低＂;空间分布呈现出高度的正的全局空间自相关;局部空间自相关分布特征为城市辖区和天水地区是显著的高值集聚区,关中—天水地区的中部是显著的低值集聚区,并对各个区域检验其显著性.%The Economic Area LCCI of Guanzhong—Tianshui areas is analyzed by the related spatial autocorrelation model of the Guanzhong—Tianshui agricultural economic data from 1978 to 2008.The results showed：The area of cultivated land in the economic rapidly decli
José Carlos Pereira
2006-12-01
Full Text Available OBJECTIVE: To evaluate the maximum residual signal auto-correlation also known as pitch amplitude (PA values in patients with Parkinson’s disease (PD patients. METHOD: The signals of 21 Parkinson’s patients were compared with 15 healthy individuals, divided according age and gender. RESULTS: Statistical difference was seen between groups for PA, 0.39 for controls and 0.25 for PD. Normal value threshold was set as 0.3; (pOBJETIVO: Avaliar autocorrelação do sinal residual também denominado como amplitude do pitch (PA em pacientes com doença de Parkinson (PD. MÉTODO: Os valores de PA, estratificados de acordo com idade e sexo, em 21 pacientes com doença de Parkinson foram analisados e comparados aos dados obtidos em 15 indivíduos sadios. RESULTADOS: Foi determinada diferença estatística para a PA entre os dois grupos (p0,3. Nos pacientes com PD 80,77% dos pacientes tinham a PA <0,3, enquanto que entre os controles somente 12,28% apresentavam valores abaixo de 0,3. O diagrama de dispersão para idade e sexo para os doentes com PD mostraram um p=0,001 e r=0,54. Não houve diferença em relação a sexo e idade entre os grupos. CONCLUSÃO: A significativa diferença da PA entre pacientes com PD e controles demonstra a especificidade da análise. Os resultados apontam para a necessidade de estudos controlados, prospectivos, para implementar o uso e indicações da determinação da amplitude do pitch na avaliação da fala em pacientes com doença de Parkinson.
Decomposition of spectra using maximum autocorrelation factors
Larsen, Rasmus
2001-01-01
classification or regression type analyses. A featured method for low dimensional representation of multivariate datasets is Hotellings principal components transform. We will extend the use of principal components analysis incorporating new information into the algorithm. This new information consists of the...... fact that given a spectrum we have a natura ln order of the input \\$\\backslash\\$underline{variables}. This is similar to Switzers maximum au tocorrelation factors, where a natural order of \\$\\backslash\\$underline{observations} (pixels) in multispectral images is utilized. However, in order to utilize...
Autocorrelations in hybrid Monte Carlo simulations
Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)
Multivariate Process Control with Autocorrelated Data
Kulahci, Murat
2011-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control and monitoring. This new high dimensional data...... often exhibit not only cross-‐correlation among the quality characteristics of interest but also serial dependence as a consequence of high sampling frequency and system dynamics. In practice, the most common method of monitoring multivariate data is through what is called the Hotelling’s T2 statistic...
Highly Robust Estimation of the Autocorrelation Coefficient
Kalina, Jan; Vlčková, Katarína
Slaný : Melandrium, 2014, s. 588-597 ISBN 978-80-87990-02-5. [International Days of Statistics and Economics /8./. Prague (CZ), 11.09.2014-13.09.2014] Grant ostatní: Nadační fond na opdporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : time series * autoregressive process * linear regression * robust econometrics Subject RIV: BB - Applied Statistics, Operational Research
On the role of autocorrelations in texts
Lande, D V
2007-01-01
The task of finding a criterion allowing to distinguish a text from an arbitrary set of words is rather relevant in itself, for instance, in the aspect of development of means for internet-content indexing or separating signals and noise in communication channels. The Zipf law is currently considered to be the most reliable criterion of this kind [3]. At any rate, conventional stochastic word sets do not meet this law. The present paper deals with one of possible criteria based on the determination of the degree of data compression.
On the role of autocorrelations in texts
Lande, D. V.; Snarskii, A. A.
2007-01-01
The task of finding a criterion allowing to distinguish a text from an arbitrary set of words is rather relevant in itself, for instance, in the aspect of development of means for internet-content indexing or separating signals and noise in communication channels. The Zipf law is currently considered to be the most reliable criterion of this kind [3]. At any rate, conventional stochastic word sets do not meet this law. The present paper deals with one of possible criteria based on the determi...
贾莹莹; 杨霖; 王田; 胡武君
2013-01-01
This paper studies the time-domain autocorrelation matching method for reducing the Peak-to-Average Power Ratio (PAPR)of the Orthogonal Frequency Division Multiplexing (OFDM)system.The main idea of this method is to add a ran-dom sequence generator in time domain,in which the random sequences are overlapped to the original signals so as to reduce the PAPR of the system and perform blind detection at the receiving end.As the signal processing in this method takes place in time domain,the computational complexity can be reduced in j ust one IFFT operation.Simulation results indicate that similar PAPR and Bit Error Rate (BER)performances can be acquired in this method to those in traditional SeLecting Mapping (SLM) method but the computational complexity is much more mitigated,thus verifying the effectiveness of the proposed method.%对时域自相关匹配方法降低 OFDM (正交频分复用)系统的PAPR (峰均功率比)进行了研究。该方法的基本思想是在时域加入一个随机序列发生器，随机序列与原始信号在时域叠加，以达到降低 OFDM系统 PAPR的目的，并可以在接收端实现信号的盲检测。该方法的信号处理过程是在时域，故仅需要一个 IFFT (快速傅里叶逆变换)操作，就能降低计算复杂度。仿真结果表明，该方法可以获得与传统 SLM (选择性映射)方法相似的PAPR和BER (误码率)性能，但计算复杂度比传统的SLM方法降低了很多，从而验证了该方法的有效性。
王培震; 石培基; 魏伟; 张胜武
2012-01-01
以石羊河流域为例，运用GCAWI法、空间自相关指数以及考虑空间自相关性的多（单）中心指数模型等实现了乡镇单元向格网单元图层的转化、适宜格网大小的确定以及人口密度的空间模拟。结果表明：①石羊河流域人口密度的空间分布差异较大而又相对集中，具有“3点4线3区”的“点一线一区”状空间结构；②不同单元大小的格网图层提高了流域整体的空间自相关性，Mo-ran’sI指数表现出较大的差异性和偶然性；③石羊河流域人口密度空间分布存在明显的正空间自相关，8000-10000m是表现流域人口密度空间分布特征的最优选择范围；④空间自相关性影响下的人口密度空间化多（单）中心模型大大提高传统指数模型的精度，却改变了距离衰减系数的性质和大小，多中心和单中心模型模拟系数的差异主要是由金昌人口密度中心引起的。%Taking Shiyang River Basin as an example, the models of GCAWI, spatial autocorrelation index, multiple (single) centre exponential with the feature of spatial autocorrelation are applied to achieve three goals : the conversion from township unit to grid unit, the regulation of determining appropriate grid size and spatial distribu- tion patterns of population density. It turned out that:①The population density distribution is relatively scattered but concentrated in Shiyang River Basin ,having a spatial structure pattern of point( three points)-line(four lines)- region ( three regions) ; ②The level of global spatial autocorrelation is improved by applying different grid scale size. The index of Moran' s I Shows larger difference and contingency ; ③The spatial distribution of population density has positive spatial autocorrelation in Shiyang River Basin. And the range from 8 000 to 10 000 metres is the best choice to present the basin' s spatial distribution characteristics of population density ;
Ana Lúcia Puerro de Melo
2011-10-01
Full Text Available Objetivou-se com este trabalho apresentar uma metodologia de identificação e modelagem da autocorrelação residual considerando ajustes individuais do modelo de Wood às lactações de cabras leiteiras e também avaliar a influência de tal modelagem na qualidade do ajuste. O modelo de Wood foi ajustado individualmente às lactações, considerando três estruturas residuais. Na primeira, assumiu-se independência dos erros (EI para todas as lactações, na segunda, assumiu-se a estrutura de erros autoregressivos de primeira ordem (AR1 para todas as lactações e, na terceira, nomeada por EI-AR1, foi utilizada a estrutura de erros AR1 somente para as lactações que apresentaram autocorrelação residual, segundo o teste de Durbin-Watson, e de EI para as demais. As três situações de ajuste foram comparadas pelos percentuais de convergência e pelas médias dos quadrados médios dos erros (QME e dos coeficientes de determinação ajustados (R²aj. As médias dos QME e dos R²aj apresentaram valores semelhantes nas três situações de estrutura residual. No entanto, o modelo com estrutura EI-AR1 apresentou maior convergência, o que consiste em uma vantagem, já que permite que um maior número de animais seja avaliado quanto à sua curva de lactação. Portanto, em função da maior convergência obtida, o ajuste do modelo de Wood com a estrutura EI-AR1 consiste na opção mais indicada para grandes conjuntos de dados.The objective of this research was to present a methodology for identification and modeling of residual autocorrelation considering individual adjustments of the Wood's model to lactation dairy goats and evaluate the influence of such modeling in the quality of adjustment. The Wood's model was adjusted individually for lactations in three different ways, the first have assumed independence of errors (IE for all lactations, the second have assumed autoregressives first order errors (AR1 for all lactations and the third, named
焦璨; 吴换杰; 黄玥娜; 黄菲菲; 张敏强
2014-01-01
In general, social science data can be divided into attribute data and relational data. Focusing on individual properties, plus lagged statistical methods, the traditional social research, by simplifying relational data into attribute data, adopts traditional statistical analysis to deal with the former. This approach is not desirable, because traditional statistical analysis needs to meet the independence of cases. However, relational data mainly involves the relationships between interdependent actors, in which sense, it violates the assumption of independence, inapplicable to traditional statistical analysis. With the development of the statistical methods, a new approach—social network analysis (SNA) is proposed to deal with relational data. Social network analysis is a large and growing body of researches on the measurement and analysis of relational structure. It mainly evaluates relationships between actors, and the contexts of the social actors. Network autocorrelation models are common for social network analysis, which are used to study on the relationship between network effect and individual behavior. In order to explore the difference between social network analysis and traditional statistical analysis, we have compared the performance of network effect model and traditional linear model in dealing with relational data through simulation studies. The simulation studies were conducted in R statistical programming environment. This article also presents the application of network effect model in psychology, and the empirical study was to investigate the impact of peer effect and learning motivation on adolescents’ academic performance. Network effect model, a type of the network autocorrelation models that fully considers the interdependencies among sample units, was applied to delve into the data by using“sna”software package in R project. The simulation study suggests that parameter estimation and model fit of network effect model are
Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices
de Jong, R. M.; Davidson, J.
1996-01-01
Conditions are derived for the consistency of kernel estimators of the covariance matrix of a sum of vectors of dependent heterogeneous random variables, which match those of the currently best-known conditions for the central limit theorem, as required for a unified theory of asymptotic inference. These include finite moments of order no more than 2 + for > 0, trending variances, and variables which are near-epoch dependent on a mixing process, but not necessarily mixing. The results are als...
The autocorrelation function for spectral determinants of quantum graphs
This paper considers the spectral determinant of quantum graph families with chaotic classical limit. The secular coefficients of the spectral determinant are found to follow distributions with zero mean and variance approaching a constant in the limit of large network size for graphs without symmetries. This constant is, in general, different from the random matrix result and depends on the classical limit. A closed expression for this system-dependent constant is given here explicitly in terms of the spectrum of an underlying Markov process. Related results for graphs with time-reversal symmetry are given. (author)
Temporal autocorrelations simulated by the ALARO-Climate RCM
Pokorná, Lucie; Huth, Radan; Farda, Aleš; Metelka, L.
Göttingen: Copernicus, 2013. EGU2013-1419. [EGU General Assembly 2013. 07.04.2013-12.04.2013, Vienna] R&D Projects: GA ČR(CZ) GAP209/11/2405 Institutional support: RVO:68378289 Subject RIV: DG - Athmosphere Sciences, Meteorology http://meetingorganizer.copernicus.org/EGU2013/EGU2013-1419.pdf
ADJUSTMENT OF GEODETIC NETWORKS USING AUTO-CORRELATION TECHNIQUE
Yehia, Hassan
2007-01-01
Control surveys networks are used to establish the locations of arbitrary points. These points may be used as reference locations for performing additional survey work. Geodetic networks are generally performed to a higher standard of accuracy than other types of surveys. This is necessary because any follow-on survey work must be able to count on the accuracy of the control points. In hybrid geodetic networks, the combination of both angular and linear measurements increases the redundant ob...
Kernel maximum autocorrelation factor and minimum noise fraction transformations
Nielsen, Allan Aasbjerg
2010-01-01
quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA), kernel MAF and kernel MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite...... hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt to...
João Marcos Louzada
2006-04-01
Full Text Available O índice I de Moran é a ferramenta usual para se medir a intensidade da autocorrelação espacial em dados de marcadores genéticos. A estatística I é assintoticamente normalmente distribuída, podendo ser avaliada como desvios da normal padrão mediante o suposto-N (aproximação normal. Porém, para pequenos números de populações (m25}, deve-se aplicar o teste de Mantel em qualquer das situações simuladas.Moran's I index is the usual tool to measure the intensity of the spatial autocorrelation in genetic markers data. I statistics is asymptotically normally distributed and it may be evaluated as standard normal deviations (assumption-N, normality. However, for small numbers of populations (m<8, the Mantel' s randomness test (assumption-R developed by Mantel (1967 should be applied. Thus, this study was done to evaluate the performance of both tests accordding to type I error rate sand their power. They were evaluated via Monte Carlo simulation, in which, the situations of average allelic frequencies, {p=0,1, p=0,25 and p=0,5} were analyzed under H0. Number for populations varying from {m= 5, 10, 25 and 50}were taken into account and for each population, the number of individuals in {n=1, 2, 5, 10 and 30} was varied as well. As regards to the alternative hypothesis (with spatial pattern, in addition to these same situations simulated in H0, the behavior of these criteria of tests was evaluated according to the variation of the amplitude in the average local allelic frequency in {A=0,1; 0,2; 0,5; 0,8 e 1,0}. Therefore, the performance of the test studied could be analyzed as the degree of variability of the average frequencies generated on a linear surface, related to the geographic space and by means of it's different slopes. The normal approximation was considered better withpopulations as combined with the weighing systems inverse of the distance and inverse of the distance squared in both levels of significance 1% and 5%. The same
任平; 吴涛; 周介铭
2016-01-01
Cultivated lands are among the most fundamental resources for the existence and development of mankind. Scientific analysis of the spatial distribution patterns and evolutionary characteristics of cultivated lands is highly useful in the protection and resource optimization of cultivated lands. Working on such research project, this paper extracted cultivated land data from the 2005, 2009 and 2013 land use data of the Longquanyi District of Chengdu, China, and calculated the kernel density, concentration index of cultivated land and conducted spatial autocorrelation analysis by using GIS platform. The results suggested that: 1) the evolution of cultivated lands in 2005-2013 in the study area was driven by aggregation. Spatially, cultivated land densities in the northwestern and northern regions were higher than those in the southern and central regions. Regions with higher cultivated land density apparently expanded from northwest to southwest, while regions with lower cultivated land density sporadically expanded from urban to rural area. 2) For distribution of cultivated lands, feature land density in the north was generally higher than that in the south. The distribution of cultivated lands was relatively concentrated, with more concentrated years in terms of the time series, but with more significant variation in the spatial differentiations among the regions. 3) There was a significant spatial autocorrelation for global distribution, with strengthening heterogeneity for local distribution of cultivated lands in the study area. Spatial units with higher proportion of cultivated lands was concentrated in the northern and northwestern regions and reduced westwards from year to year. The units with lower proportions of cultivated lands were more distributed at built-up areas and suburbs surrounding the urban centers, with two stages of expansion and contraction. Because of urban expansion and rural land consolidation in 2005-2013, there were hot spots and cold
On the effect of the ionising background on the Ly{\\alpha} forest autocorrelation function
Gontcho, Satya Gontcho A; Busca, Nicolás G
2014-01-01
An analytical framework is presented to understand the effects of a fluctuating intensity of the cosmic ionising background on the correlations of the Ly{\\alpha} forest transmission fraction measured in quasar spectra. In the absence of intensity fluctuations, the Ly{\\alpha} power spectrum should have the expected cold dark matter power spectrum with redshift distortions in the linear regime, with a bias factor b_{\\delta} and a redshift distortion parameter {\\beta} that depend on redshift but are independent of scale. The intensity fluctuations introduce a scale dependence in both b_{\\delta} and {\\beta}, but keeping their product b_{\\delta}{\\beta} fixed. Observations of the Ly{\\alpha} correlations and cross-correlations with radiation sources like those being done at present in the BOSS survey of SDSS-III (Busca et al. 2013; Slosar et al. 2013; Font-Ribera et al. 2014) have the potential to measure this scale dependence, which reflects the biasing properties of the sources and absorbers of the ionising backgr...
On the effect of the ionising background on the Ly{\\alpha} forest autocorrelation function
Gontcho, Satya Gontcho A; Miralda-Escudé, Jordi; Busca, Nicolás G.
2014-01-01
An analytical framework is presented to understand the effects of a fluctuating intensity of the cosmic ionising background on the correlations of the Ly{\\alpha} forest transmission fraction measured in quasar spectra. In the absence of intensity fluctuations, the Ly{\\alpha} power spectrum should have the expected cold dark matter power spectrum with redshift distortions in the linear regime, with a bias factor b_{\\delta} and a redshift distortion parameter {\\beta} that depend on redshift but...
On the validity of the case-time-control design for autocorrelated exposure histories
Jensen, Aksel Karl Georg; Gerds, Thomas Alexander; Weeke, Peter; Torp-Pedersen, Christian; Andersen, Per Kragh
2014-01-01
review the mathematical assumptions underlying the case-time-control design and examine sensitivity to deviations from the assumed independence of within-individual exposure history. Results from simulating various scenarios suggest that the design is quite robust to deviations from this model assumption...
Trajectory length and autocorrelation times. Nf = 2 simulations in the Schroedinger functional
A status report is presented on the large-volume simulations in the Schroedinger functional with two flavours of O(a) improved Wilson quarks performed by the ALPHA collaboration. The physics goal is to set the scale for the computation of the fundamental parameters of QCD. In this talk the emphasis is on aspects of the Hybrid Monte-Carlo algorithm, which we use with (symmetric) even-odd and Hasenbusch preconditioning. We study the dependence of aucorrelation times on the trajectory length. The latter is found to be significant for fermionic correlators, the trajectories longer than unity performing better than the shorter ones. (orig.)
Hansen, Peter Reinhard; Lunde, Asger
2014-01-01
An economic time series can often be viewed as a noisy proxy for an underlying economic variable. Measurement errors will influence the dynamic properties of the observed process and may conceal the persistence of the underlying time series. In this paper we develop instrumental variable (IV...
Zhang, Hongjuan; Shi, Zhenwei; Guo, Chonghui; Feng, Enmin
2009-01-01
Blind source extraction (BSE) has become one of the promising methods in the field of signal processing and analysis, which only desires to extract "interesting" source signals with specific stochastic property or features so as to save lots of computing time and resources. This paper addresses BSE problem, in which desired source signals have some available reference signals. Based on this prior information, we develop an objective function for extraction of temporally correlated sources. Maximizing this objective function, a semi-blind source extraction fixed-point algorithm is proposed. Simulations on artificial electrocardiograph (ECG) signals and the real-world ECG data demonstrate the better performance of the new algorithm. Moreover, comparisons with existing algorithms further indicate the validity of our new algorithm, and also show its robustness to the estimated error of time delay.
Long-range autocorrelations of CpG islands in the human genome.
Benjamin Koester
Full Text Available In this paper, we use a statistical estimator developed in astrophysics to study the distribution and organization of features of the human genome. Using the human reference sequence we quantify the global distribution of CpG islands (CGI in each chromosome and demonstrate that the organization of the CGI across a chromosome is non-random, exhibits surprisingly long range correlations (10 Mb and varies significantly among chromosomes. These correlations of CGI summarize functional properties of the genome that are not captured when considering variation in any particular separate (and local feature. The demonstration of the proposed methods to quantify the organization of CGI in the human genome forms the basis of future studies. The most illuminating of these will assess the potential impact on phenotypic variation of inter-individual variation in the organization of the functional features of the genome within and among chromosomes, and among individuals for particular chromosomes.
A propagation-separation approach to estimate the autocorrelation in a time-series
D. V. Divine
2008-07-01
Full Text Available The paper presents an approach to estimate parameters of a local stationary AR(1 time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1 model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes.
Viceré, Andrea; Yvert, Michel
2016-08-01
Rotating, non-axisymmetric neutron stars are expected to emit continuous gravitational waves at a nearly stable frequency. Nowadays about 2500 pulsars have been detected, thanks to their beamed electromagnetic emission, and many more of these objects should exist, whose electromagnetic beam does not include Earth and cannot be detected. The gravitational emission is not beamed, and could be accessible to gravitational observatories, even though no detection as been claimed yet. About half of the pulsars predicted to possibly emit gravitational waves in the frequency range accessible to ground-based interferometers belongs to binary systems; this is an additional complication, because the frequencies of these pulsars are Doppler-shifted due to their orbital motion, and an optimal detection strategy would require a computing power far beyond the present capabilities. We present here an approach which allows searching all-sky for such sources, over a broad range of frequencies, orbital periods and binary system eccentricities, reaching sensitivities potentially good enough to provide candidates for more sophisticated hierarchical detection methods. We test this new technique using real data taken during the first science run of Virgo, and estimating the sensitivity to a set of simulated pulsar signals.
Shiue, Ren-Jye; Wang, Yifei; Peng, Cheng; Robertson, Alexander D; Efetov, Dimitri; Assefa, Solomon; Koppens, Frank H L; Hone, James; Englund, Dirk
2015-01-01
Graphene and other two-dimensional (2D) materials have emerged as promising materials for broadband and ultrafast photodetection and optical modulation. These optoelectronic capabilities can augment complementary metal-oxide-semiconductor (CMOS) devices for high-speed and low-power optical interconnects. Here, we demonstrate an on-chip ultrafast photodetector based on a two-dimensional heterostructure consisting of high-quality graphene encapsulated in hexagonal boron nitride. Coupled to the optical mode of a silicon waveguide, this 2D heterostructure-based photodetector exhibits a maximum responsivity of 0.36 A/W and high-speed operation with a 3 dB cut-off at 42 GHz. From photocurrent measurements as a function of the top-gate and source-drain voltages, we conclude that the photoresponse is consistent with hot electron mediated effects. At moderate peak powers above 50 mW, we observe a saturating photocurrent consistent with the mechanisms of electron-phonon supercollision cooling. This nonlinear photorespo...
Power spectra and autocorrelation functions for surface diffusion of lithium on tungsten
Gładyszewski, L.
1989-04-01
The surface ionization of lithium on polycrystalline tungsten and ionic thermal desorption are studied by a method based on the Li + ion current noise arising from the fluctuation of the work function as a result of random fluctuations of the Li adsorbate density. The activation energy for surface diffusion and energy of desorption for Li atoms have been determined by measuring the time correlation function of the local ion thermoemission current fluctuations.
van Beijeren, H.; Kehr, K. W.
1986-01-01
The correlation factor, defined as the ratio between the tracer diffusion coefficient in lattice gases and the diffusion coefficient for a corresponding uncorrelated random walk, is known to assume a very simple form under certain conditions. A simple derivation of this is given with the aid of the Green-Kubo formula for the tracer diffusion coefficient and it is generalised to a frequency-dependent correlation factor. The application to lattice gases with nearly vanishing vacancy concentrati...
The spin-autocorrelation function in spin glasses above the freezing temperature
The purpose of this work is to investigate spin glasses above the freezing temperature, where dynamics of magnetic correlations have been observed. In the temperature range well above two times the freezing temperature the Markovian Two Level Jump (MTJP) model was rather successful to describe the experimental findings in HFM measurements of the spin glasses AuFe, where Fe atoms are diluted in a diamagnetic matrix, and in the cubic Laves phase Y(Fe,Al)2, where magnetic spins are placed in a pauli paramagnetic matrix. This MTJP model proposes a two state system, where the 57-Fe probe atom is embedded in a correlated region - the life time of this state is ton - and a state, in which the atoms experiences no correlation. The temperature dependence of ton was found to follow a power law between two times Tf and 10 times Tf. Two different exponents were obtained: -1 for samples with low Fe content and -2 for spin glasses with high Fe content. A major goal of the present work is to test the power law findings in spin glasses with Fe concentrations different to the ones investigated and in other classes of spin glass types for temperatures above Tf with HFM and μSR measurements. For the current investigations additional AuFe and Y(Fe,Al)2 samples in the intermediate concentration range are investigated. To check if the findings are more generally valid the study is extended to spin glasses with competing exchange interactions. In the alloys CrFe and NiFeMn the spin glass phase occurs in the concentration regime between antiferromagnetic and ferromagnetic phase. The successful analysis of all recorded HFM spectra by means of the MTJP model is shown. For temperatures above two times Tf the proposed power law behavior for high Fe and low Fe content is confirmed for all spin glasses investigated. Below this temperature range a sharp increase in the life time of correlated states is observed. The life times derived from μSR experiments show a similar power law behavior in temperature dependence. However, the correlation times are a factor 10 - 100 shorter than those analyzed in the HFM measurements. (author)
de la Mata, Tamara; Llano, Carlos
2013-07-01
Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.
Mata López, Tamara de la; Llano Verduras , Carlos
2013-01-01
Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with touris...
A TR-UWB Downconversion Autocorrelation Receiver for Wireless Body Area Network
Islam SMRiazul
2009-01-01
Full Text Available Low power UWB receiver architecture is proposed for a Wireless Body Area Network (WBAN. This receiving technology is a synergy of existing downconversion-based narrowband rejection mechanism in RF front end and signal processing in frequency domain. Frequency components of converted and filtered UWB pulses are separated into real and imaginary parts, independently correlated and effectively combined to achieve an improved output Signal to noise ratio (SNR. An extensive mathematical analysis has been performed to formulate the close-form expressions for SNRs in order to compare system performances toward favorable BER under BPSK modulation scheme. Analysis shows that optimal rotation of coordination plays an important role for the enhancement of receiving SNR which is further confirmed by computer simulation. A wide range of link level simulation (LLS urges that the proposed system is more power efficient in higher-order modulation (HOM schemes. Transmitted Reference (TR scheme has been considered as the basis for wideband communication.
Investigation of gas discharge processes in PMTs by the autocorrelation method
The effect of the potential different at the focusing chamber electrodes of the FEU-85, FEU-87, and FEU-93 photomultipliers on the intensity of afterpulses resulting from gas discharge processes is investigated. With appropriately selected potentials, the number of recorded secondary pulses can be decreased. Charge distribution spectra are obtained for this sort of pulses, which gives a qualitative estimate of both the homogeneity of the charge and mass distribution of residual gases and the ion-electron emission coefficients
Application of the Autocorrelation Function and Fractal Geometry Methods for Analysis of MFM Images
Bramowicz M.
2014-06-01
Full Text Available Niniejsza praca dotyczy zastosowania metod korelacyjnych do numerycznej analizy obrazów rozkładu pola magnetycznego emitowanego z obszarów spontanicznego namagnesowania. W pracy przedstawiono kontynuację badań nad zastosowaniem funkcji autokorelacji oraz metod analizy fraktalnej w badaniach struktury domenowej oraz charakterystyki emitowanego z nich pola magnetycznego.
Hedonic Predicted House Price Indices Using Time-Varying Hedonic Models with Spatial Autocorrelation
Alicia Rambaldi; Prasada Rao
2011-01-01
Hedonic housing price indices are computed from estimated hedonic pricing models. The commonly used time dummy hedonic model and the rolling window hedonic model fail to account for changing consumer preferences over hedonic characteristics and typically these models do not account for the presence of spatial correlation in prices reflecting the role of locational characteristics. This paper develops a class of models with time-varying hedonic coefficients and spatially correlated errors, pro...
Passive-microwave derived observations of snow cover show potential to provide synoptically sensitive, and hydrologically and climatologically significant, information because of all-weather imaging capabilities, rapid scene revisit time and the ability to derive quantitative estimates of snow water equivalent (SWE). In this study, we seek to identify the dominant patterns of clustering in SWE imagery using the Getis statistic, a local indicator of spatial association. The SWE data were derived from five day-averaged Special Sensor Microwave/Imager (SSM/I) brightness temperatures using the Canadian Atmospheric Environment Service dual channel algorithm. The analysed data span one winter season (December–February 1988–1989) and are limited to a ground-validated prairie scene. National Center for Environmental Prediction (NCEP) gridded atmospheric data (500 mb geopotential height; 700 mb temperature) were incorporated into the study to investigate whether the spatial orientation of the Getis statistic clusters provides information on interaction between snow cover and the atmosphere. Results show that the direction of atmospheric airflow as expressed by the 500 mb geopotential height field corresponds strongly to the orientation of surface snow cover clusters with no time lag. The 700 mb temperature field is also a controlling influence on the snow cover clusters both through modifying cluster orientation and reinforcing cluster magnitude. (author)
Radiation-induced large-scale structure during the reionization epoch: the autocorrelation function
Croft, Rupert A C
2007-01-01
The structures produced during the epoch of reionization by the action of radiation on neutral hydrogen are in principle different to those that arise through gravitational growth of initially small perturbations. We explore the difference between the two mechanisms using high resolution cosmological radiative transfer. Our computations use a Monte Carlo code which raytraces directly through SPH kernels without a grid, preserving the high spatial resolution of the underlying hydrodynamic simulation. Because the properties of the first sources of radiation are uncertain, we simulate a range of models with different source properties and recombination physics. We examine the morphology of the neutral hydrogren distribution and the reionization history in these models. We find that at fixed mean neutral fraction, structures are visually most affected by the existence of a lower limit in source luminosity, then by galaxy mass to light ratio, and are minimally affected by changes in the recombination rate and ampl...
Jayaraman, K.; Zakrzewski, W.T.
1996-11-01
Describes a practical approach to handling the problem of correlated errors when calibrating linear and non-linear models used in forest growth and yield modelling. Details the parameter estimation method which is appropriate when there is a need to consider the effect of correlation among residuals (repeated measurements, longitudinal observations). The presented approach is not model-specific but the procedure and conclusions are based on practical experience with calibrating the stem-profile model derived by Zakrzewski (1995).
P. BAECKE; Van den Poel, D
2012-01-01
Traditional CRM models often ignore the correlation that could exist among the purchasing behavior of surrounding prospects. Hence, a generalized linear autologistic regression model can be used to capture this interdependence and improve the predictive performance of the model. In particular, customer acquisition models can benefit from this. These models often suffer from a lack of data quality due to the limited amount of information available about potential new customers. Based on a cust...
Fujiyama, Toshifumi; Matsui, Chihiro; Takemura, Akimichi
2016-01-01
We propose a power-law growth and decay model for posting data to social networking services before and after social events. We model the time series structure of deviations from the power-law growth and decay with a conditional Poisson autoregressive (AR) model. Online postings related to social events are described by five parameters in the power-law growth and decay model, each of which characterizes different aspects of interest in the event. We assess the validity of parameter estimates in terms of confidence intervals, and compare various submodels based on likelihoods and information criteria. PMID:27505155
Schröder, Winfried; Pesch, Roland; Harmens, Harry; Fagerli, Hilde; Ilyin, Ilia
2012-01-01
Background: Within the framework of the Convention on Long-range Transboundary Air Pollution atmospheric depositions of heavy metals and nitrogen as well as critical loads/levels exceedances are mapped yearly with a spatial resolution of 50 km by 50 km. The maps rely on emission data and are calculated by use of atmospheric modelling techniques. For validation, EMEP monitoring data collected at up to 70 sites across Europe are used. This spatially sparse coverage gave reason to te...