Energy-Based Wavelet De-Noising of Hydrologic Time Series
Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu
2014-01-01
De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533
Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M
2017-02-01
Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.
Permutation entropy of finite-length white-noise time series.
Little, Douglas J; Kane, Deb M
2016-08-01
Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a time series. While the PE of white noise is well understood in the long time-series limit, analysis in the general case is currently lacking. Here the expectation value and variance of white-noise PE are derived as functions of the number of ordinal pattern trials, N, and the embedding dimension, D. It is demonstrated that the probability distribution of the white-noise PE converges to a χ^{2} distribution with D!-1 degrees of freedom as N becomes large. It is further demonstrated that the PE variance for an arbitrary time series can be estimated as the variance of a related metric, the Kullback-Leibler entropy (KLE), allowing the qualitative N≫D! condition to be recast as a quantitative estimate of the N required to achieve a desired PE calculation precision. Application of this theory to statistical inference is demonstrated in the case of an experimentally obtained noise series, where the probability of obtaining the observed PE value was calculated assuming a white-noise time series. Standard statistical inference can be used to draw conclusions whether the white-noise null hypothesis can be accepted or rejected. This methodology can be applied to other null hypotheses, such as discriminating whether two time series are generated from different complex system states.
False-nearest-neighbors algorithm and noise-corrupted time series
International Nuclear Information System (INIS)
Rhodes, C.; Morari, M.
1997-01-01
The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented. copyright 1997 The American Physical Society
Spectral parameter power series representation for Hill's discriminant
International Nuclear Information System (INIS)
Khmelnytskaya, K.V.; Rosu, H.C.
2010-01-01
We establish a series representation of the Hill discriminant based on the spectral parameter power series (SPPS) recently introduced by Kravchenko. We also show the invariance of the Hill discriminant under a Darboux transformation and employing the Mathieu case the feasibility of this type of series for numerical calculations of the eigenspectrum.
Restriction of complementary series representations of O(1,N) to symmetric subgroups
DEFF Research Database (Denmark)
Möllers, Jan; Oshima, Yoshiki
by a direct integral of principal series representations whereas the discrete part consists of finitely many complementary series representations. The explicit Plancherel formula is computed on the Fourier transformed side of the non-compact realization of the complementary series by using the spectral...
Restriction of complementary series representations of $O(1,N)$ to symmetric subgroups
DEFF Research Database (Denmark)
Möllers, Jan; Oshima, Yoshiki
2012-01-01
is given by a direct integral of principal series representations whereas the discrete part consists of finitely many complementary series representations. The explicit Plancherel formula is computed on the Fourier transformed side of the non-compact realization of the complementary series by using...
Noise in attractor networks in the brain produced by graded firing rate representations.
Directory of Open Access Journals (Sweden)
Tristan J Webb
Full Text Available Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry.
Noise in attractor networks in the brain produced by graded firing rate representations
Webb, Tristan J.; Rolls, Edmund T; Deco, Gustavo; Feng, Jianfeng
2011-01-01
Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate\\ud probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as\\ud decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given\\ud mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribut...
Thresholding of auditory cortical representation by background noise
Liang, Feixue; Bai, Lin; Tao, Huizhong W.; Zhang, Li I.; Xiao, Zhongju
2014-01-01
It is generally thought that background noise can mask auditory information. However, how the noise specifically transforms neuronal auditory processing in a level-dependent manner remains to be carefully determined. Here, with in vivo loose-patch cell-attached recordings in layer 4 of the rat primary auditory cortex (A1), we systematically examined how continuous wideband noise of different levels affected receptive field properties of individual neurons. We found that the background noise, when above a certain critical/effective level, resulted in an elevation of intensity threshold for tone-evoked responses. This increase of threshold was linearly dependent on the noise intensity above the critical level. As such, the tonal receptive field (TRF) of individual neurons was translated upward as an entirety toward high intensities along the intensity domain. This resulted in preserved preferred characteristic frequency (CF) and the overall shape of TRF, but reduced frequency responding range and an enhanced frequency selectivity for the same stimulus intensity. Such translational effects on intensity threshold were observed in both excitatory and fast-spiking inhibitory neurons, as well as in both monotonic and nonmonotonic (intensity-tuned) A1 neurons. Our results suggest that in a noise background, fundamental auditory representations are modulated through a background level-dependent linear shifting along intensity domain, which is equivalent to reducing stimulus intensity. PMID:25426029
Thresholding of auditory cortical representation by background noise.
Liang, Feixue; Bai, Lin; Tao, Huizhong W; Zhang, Li I; Xiao, Zhongju
2014-01-01
It is generally thought that background noise can mask auditory information. However, how the noise specifically transforms neuronal auditory processing in a level-dependent manner remains to be carefully determined. Here, with in vivo loose-patch cell-attached recordings in layer 4 of the rat primary auditory cortex (A1), we systematically examined how continuous wideband noise of different levels affected receptive field properties of individual neurons. We found that the background noise, when above a certain critical/effective level, resulted in an elevation of intensity threshold for tone-evoked responses. This increase of threshold was linearly dependent on the noise intensity above the critical level. As such, the tonal receptive field (TRF) of individual neurons was translated upward as an entirety toward high intensities along the intensity domain. This resulted in preserved preferred characteristic frequency (CF) and the overall shape of TRF, but reduced frequency responding range and an enhanced frequency selectivity for the same stimulus intensity. Such translational effects on intensity threshold were observed in both excitatory and fast-spiking inhibitory neurons, as well as in both monotonic and nonmonotonic (intensity-tuned) A1 neurons. Our results suggest that in a noise background, fundamental auditory representations are modulated through a background level-dependent linear shifting along intensity domain, which is equivalent to reducing stimulus intensity.
Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise
West, Thomas K., IV; Bretl, Katherine N.; Walker, Eric L.; Pinier, Jeremy T.
2015-01-01
The objective of this study was to outline an approach for the quantification of uncertainty in sonic boom measurements and to investigate the effect of various near-field uncertainty representation approaches on ground noise predictions. These approaches included a symmetric versus asymmetric uncertainty band representation and a dispersion technique based on a partial sum Fourier series that allows for the inclusion of random error sources in the uncertainty. The near-field uncertainty was propagated to the ground level, along with additional uncertainty in the propagation modeling. Estimates of perceived loudness were obtained for the various types of uncertainty representation in the near-field. Analyses were performed on three configurations of interest to the sonic boom community: the SEEB-ALR, the 69o DeltaWing, and the LM 1021-01. Results showed that representation of the near-field uncertainty plays a key role in ground noise predictions. Using a Fourier series based dispersion approach can double the amount of uncertainty in the ground noise compared to a pure bias representation. Compared to previous computational fluid dynamics results, uncertainty in ground noise predictions were greater when considering the near-field experimental uncertainty.
Geometric noise reduction for multivariate time series.
Mera, M Eugenia; Morán, Manuel
2006-03-01
We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.
Riesz Representation Theorem on Bilinear Spaces of Truncated Laurent Series
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Sabarinsyah
2017-06-01
Full Text Available In this study a generalization of the Riesz representation theorem on non-degenerate bilinear spaces, particularly on spaces of truncated Laurent series, was developed. It was shown that any linear functional on a non-degenerate bilinear space is representable by a unique element of the space if and only if its kernel is closed. Moreover an explicit equivalent condition can be identiﬁed for the closedness property of the kernel when the bilinear space is a space of truncated Laurent series.
Estimating the level of dynamical noise in time series by using fractal dimensions
Energy Technology Data Exchange (ETDEWEB)
Sase, Takumi, E-mail: sase@sat.t.u-tokyo.ac.jp [Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 153-8505 (Japan); Ramírez, Jonatán Peña [CONACYT Research Fellow, Center for Scientific Research and Higher Education at Ensenada (CICESE), Carretera Ensenada-Tijuana No. 3918, Zona Playitas, C.P. 22860, Ensenada, Baja California (Mexico); Kitajo, Keiichi [BSI-Toyota Collaboration Center, RIKEN Brain Science Institute, Wako, Saitama 351-0198 (Japan); Aihara, Kazuyuki; Hirata, Yoshito [Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 153-8505 (Japan); Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505 (Japan)
2016-03-11
We present a method for estimating the dynamical noise level of a ‘short’ time series even if the dynamical system is unknown. The proposed method estimates the level of dynamical noise by calculating the fractal dimensions of the time series. Additionally, the method is applied to EEG data to demonstrate its possible effectiveness as an indicator of temporal changes in the level of dynamical noise. - Highlights: • A dynamical noise level estimator for time series is proposed. • The estimator does not need any information about the dynamics generating the time series. • The estimator is based on a novel definition of time series dimension (TSD). • It is demonstrated that there exists a monotonic relationship between the • TSD and the level of dynamical noise. • We apply the proposed method to human electroencephalographic data.
Estimating the level of dynamical noise in time series by using fractal dimensions
International Nuclear Information System (INIS)
Sase, Takumi; Ramírez, Jonatán Peña; Kitajo, Keiichi; Aihara, Kazuyuki; Hirata, Yoshito
2016-01-01
We present a method for estimating the dynamical noise level of a ‘short’ time series even if the dynamical system is unknown. The proposed method estimates the level of dynamical noise by calculating the fractal dimensions of the time series. Additionally, the method is applied to EEG data to demonstrate its possible effectiveness as an indicator of temporal changes in the level of dynamical noise. - Highlights: • A dynamical noise level estimator for time series is proposed. • The estimator does not need any information about the dynamics generating the time series. • The estimator is based on a novel definition of time series dimension (TSD). • It is demonstrated that there exists a monotonic relationship between the • TSD and the level of dynamical noise. • We apply the proposed method to human electroencephalographic data.
On-line analysis of reactor noise using time-series analysis
International Nuclear Information System (INIS)
McGevna, V.G.
1981-10-01
A method to allow use of time series analysis for on-line noise analysis has been developed. On-line analysis of noise in nuclear power reactors has been limited primarily to spectral analysis and related frequency domain techniques. Time series analysis has many distinct advantages over spectral analysis in the automated processing of reactor noise. However, fitting an autoregressive-moving average (ARMA) model to time series data involves non-linear least squares estimation. Unless a high speed, general purpose computer is available, the calculations become too time consuming for on-line applications. To eliminate this problem, a special purpose algorithm was developed for fitting ARMA models. While it is based on a combination of steepest descent and Taylor series linearization, properties of the ARMA model are used so that the auto- and cross-correlation functions can be used to eliminate the need for estimating derivatives. The number of calculations, per iteration varies lineegardless of the mee 0.2% yield strength displayed anisotropy, with axial and circumferential values being greater than radial. For CF8-CPF8 and CF8M-CPF8M castings to meet current ASME Code S acid fuel cells
Complex noise suppression using a sparse representation and 3D filtering of images
Kravchenko, V. F.; Ponomaryov, V. I.; Pustovoit, V. I.; Palacios-Enriquez, A.
2017-08-01
A novel method for the filtering of images corrupted by complex noise composed of randomly distributed impulses and additive Gaussian noise has been substantiated for the first time. The method consists of three main stages: the detection and filtering of pixels corrupted by impulsive noise, the subsequent image processing to suppress the additive noise based on 3D filtering and a sparse representation of signals in a basis of wavelets, and the concluding image processing procedure to clean the final image of the errors emerged at the previous stages. A physical interpretation of the filtering method under complex noise conditions is given. A filtering block diagram has been developed in accordance with the novel approach. Simulations of the novel image filtering method have shown an advantage of the proposed filtering scheme in terms of generally recognized criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, and when visually comparing the filtered images.
Flicker Noise in GNSS Station Position Time Series: How much is due to Crustal Loading Deformations?
Rebischung, P.; Chanard, K.; Metivier, L.; Altamimi, Z.
2017-12-01
The presence of colored noise in GNSS station position time series was detected 20 years ago. It has been shown since then that the background spectrum of non-linear GNSS station position residuals closely follows a power-law process (known as flicker noise, 1/f noise or pink noise), with some white noise taking over at the highest frequencies. However, the origin of the flicker noise present in GNSS station position time series is still unclear. Flicker noise is often described as intrinsic to the GNSS system, i.e. due to errors in the GNSS observations or in their modeling, but no such error source has been identified so far that could explain the level of observed flicker noise, nor its spatial correlation.We investigate another possible contributor to the observed flicker noise, namely real crustal displacements driven by surface mass transports, i.e. non-tidal loading deformations. This study is motivated by the presence of power-law noise in the time series of low-degree (≤ 40) and low-order (≤ 12) Stokes coefficients observed by GRACE - power-law noise might also exist at higher degrees and orders, but obscured by GRACE observational noise. By comparing GNSS station position time series with loading deformation time series derived from GRACE gravity fields, both with their periodic components removed, we therefore assess whether GNSS and GRACE both plausibly observe the same flicker behavior of surface mass transports / loading deformations. Taking into account GRACE observability limitations, we also quantify the amount of flicker noise in GNSS station position time series that could be explained by such flicker loading deformations.
Formal degrees of unipotent discrete series representations and the exotic Fourier transform
Ciubotaru, D.; Opdam, E.
2015-01-01
We introduce a notion of elliptic fake degrees for unipotent elliptic representations of a semisimple p-adic group. We conjecture, and verify in some cases, that the relation between the formal degrees of unipotent discrete series representations of a semisimple p-adic group and the elliptic fake
Nestor, Adrian; Vettel, Jean M; Tarr, Michael J
2013-11-01
What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.
Noise propagation in two-step series MAPK cascade.
Directory of Open Access Journals (Sweden)
Venkata Dhananjaneyulu
Full Text Available Series MAPK enzymatic cascades, ubiquitously found in signaling networks, act as signal amplifiers and play a key role in processing information during signal transduction in cells. In activated cascades, cell-to-cell variability or noise is bound to occur and thereby strongly affects the cellular response. Commonly used linearization method (LM applied to Langevin type stochastic model of the MAPK cascade fails to accurately predict intrinsic noise propagation in the cascade. We prove this by using extensive stochastic simulations for various ranges of biochemical parameters. This failure is due to the fact that the LM ignores the nonlinear effects on the noise. However, LM provides a good estimate of the extrinsic noise propagation. We show that the correct estimate of intrinsic noise propagation in signaling networks that contain at least one enzymatic step can be obtained only through stochastic simulations. Noise propagation in the cascade depends on the underlying biochemical parameters which are often unavailable. Based on a combination of global sensitivity analysis (GSA and stochastic simulations, we developed a systematic methodology to characterize noise propagation in the cascade. GSA predicts that noise propagation in MAPK cascade is sensitive to the total number of upstream enzyme molecules and the total number of molecules of the two substrates involved in the cascade. We argue that the general systematic approach proposed and demonstrated on MAPK cascade must accompany noise propagation studies in biological networks.
Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions
Klos, Anna; Bogusz, Janusz; Figurski, Mariusz; Kosek, Wieslaw; Gruszczynski, Maciej
2014-05-01
The noises in GPS time series are stated to be described the best by the combination of white (Gaussian) and power-law processes. They are mainly the effect of mismodelled satellite orbits, Earth orientation parameters, atmospheric effects, antennae phase centre effects, or of monument instability. Due to the fact, that velocities of permanent stations define the kinematic reference frame, they have to fulfil the requirement of being stable at 0.1 mm/yr. The previously performed researches showed, that the wrong assumption of noise model leads to the underestimation of velocities and their uncertainties from 2 up to even 11, especially in the Up direction. This presentation focuses on more than 200 EPN (EUREF Permanent Network) stations from the area of Europe with various monument types (concrete pillars, buildings, metal masts, with or without domes, placed on the ground or on the rock) and coordinates of weekly changes (GPS weeks 0834-1459). The topocentric components (North, East, Up) in ITRF2005 which come from the EPN Re-Processing made by the Military University of Technology Local Analysis Centre (MUT LAC) were processed with Maximum Likelihood Estimation (MLE) using CATS software. We have assumed the existence of few combinations of noise models (these are: white, flicker and random walk noise with integer spectral indices and power-law noise models with fractional spectral indices) and investigated which of them EPN weekly time series are likely to follow. The results show, that noises in GPS time series are described the best by the combination of white and flicker noise model. It is strictly related to the so-called common mode error (CME) that is spatially correlated error being one of the dominant error source in GPS solutions. We have assumed CME as spatially uniform, what was a good approximation for stations located hundreds of kilometres one to another. Its removal with spatial filtering reduces the amplitudes of white and flicker noise by a
Self-dual continuous series of representations for and
Hadasz, Leszek; Pawelkiewicz, Michal; Schomerus, Volker
2014-10-01
We determine the Clebsch-Gordan and Racah-Wigner coefficients for continuous series of representations of the quantum deformed algebras and . While our results for the former algebra reproduce formulas by Ponsot and Teschner, the expressions for the orthosymplectic algebra are new. Up to some normalization factors, the associated Racah-Wigner coefficients are shown to agree with the fusing matrix in the Neveu-Schwarz sector of N =1 supersymmetric Liouville field theory.
Uncorrelated Noise in Turbulence Measurements
DEFF Research Database (Denmark)
Kristensen, Leif; Lenschow, D. H.
1985-01-01
of atmospheric variability. The authors assume that the measured signal is a representation of a variable that is continuous on the scale of interest in the atmosphere. Uncorrelated noise affects the autovariance function (or, equivalently, the structure function) only between zero and the first lag, while its...... effect is smeared across the entire power spectrum. For this reason, quantities such as variance dissipation may be more conveniently estimated from the structure function than from the spectrum. The modeling results are confirmed by artificially modifying a test time series with Poisson noise...
Asymptotic behaviour of a non-commutative rational series with a nonnegative linear representation
Directory of Open Access Journals (Sweden)
Philippe Dumas
2007-01-01
Full Text Available We analyse the asymptotic behaviour in the mean of a non-commutative rational series, which originates from differential cryptanalysis, using tools from probability theory, and from analytic number theory. We derive a Fourier representation of a first-order summation function obtained by interpreting this rational series as a non-classical rational sequence via the octal numeration system. The method is applicable to a wide class of sequences rational with respect to a numeration system essentially under the condition that they admit a linear representation with nonnegative coefficients.
Swartz, R. Andrew
2013-01-01
This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136
Directory of Open Access Journals (Sweden)
Wenjia Liu
2013-01-01
Full Text Available This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.
Mehdizadeh, Sina; Sanjari, Mohammad Ali
2017-11-07
This study aimed to determine the effect of added noise, filtering and time series length on the largest Lyapunov exponent (LyE) value calculated for time series obtained from a passive dynamic walker. The simplest passive dynamic walker model comprising of two massless legs connected by a frictionless hinge joint at the hip was adopted to generate walking time series. The generated time series was used to construct a state space with the embedding dimension of 3 and time delay of 100 samples. The LyE was calculated as the exponential rate of divergence of neighboring trajectories of the state space using Rosenstein's algorithm. To determine the effect of noise on LyE values, seven levels of Gaussian white noise (SNR=55-25dB with 5dB steps) were added to the time series. In addition, the filtering was performed using a range of cutoff frequencies from 3Hz to 19Hz with 2Hz steps. The LyE was calculated for both noise-free and noisy time series with different lengths of 6, 50, 100 and 150 strides. Results demonstrated a high percent error in the presence of noise for LyE. Therefore, these observations suggest that Rosenstein's algorithm might not perform well in the presence of added experimental noise. Furthermore, findings indicated that at least 50 walking strides are required to calculate LyE to account for the effect of noise. Finally, observations support that a conservative filtering of the time series with a high cutoff frequency might be more appropriate prior to calculating LyE. Copyright © 2017 Elsevier Ltd. All rights reserved.
Orović, Irena; Stanković, Srdjan; Amin, Moeness
2013-05-01
A modified robust two-dimensional compressive sensing algorithm for reconstruction of sparse time-frequency representation (TFR) is proposed. The ambiguity function domain is assumed to be the domain of observations. The two-dimensional Fourier bases are used to linearly relate the observations to the sparse TFR, in lieu of the Wigner distribution. We assume that a set of available samples in the ambiguity domain is heavily corrupted by an impulsive type of noise. Consequently, the problem of sparse TFR reconstruction cannot be tackled using standard compressive sensing optimization algorithms. We introduce a two-dimensional L-statistics based modification into the transform domain representation. It provides suitable initial conditions that will produce efficient convergence of the reconstruction algorithm. This approach applies sorting and weighting operations to discard an expected amount of samples corrupted by noise. The remaining samples serve as observations used in sparse reconstruction of the time-frequency signal representation. The efficiency of the proposed approach is demonstrated on numerical examples that comprise both cases of monocomponent and multicomponent signals.
Data Series Subtraction with Unknown and Unmodeled Background Noise
Vitale, Stefano; Congedo, Giuseppe; Dolesi, Rita; Ferroni, Valerio; Hueller, Mauro; Vetrugno, Daniele; Weber, William Joseph; Audley, Heather; Danzmann, Karsten; Diepholz, Ingo;
2014-01-01
LISA Pathfinder (LPF), the precursor mission to a gravitational wave observatory of the European Space Agency, will measure the degree to which two test masses can be put into free fall, aiming to demonstrate a suppression of disturbance forces corresponding to a residual relative acceleration with a power spectral density (PSD) below (30 fm/sq s/Hz)(sup 2) around 1 mHz. In LPF data analysis, the disturbance forces are obtained as the difference between the acceleration data and a linear combination of other measured data series. In many circumstances, the coefficients for this linear combination are obtained by fitting these data series to the acceleration, and the disturbance forces appear then as the data series of the residuals of the fit. Thus the background noise or, more precisely, its PSD, whose knowledge is needed to build up the likelihood function in ordinary maximum likelihood fitting, is here unknown, and its estimate constitutes instead one of the goals of the fit. In this paper we present a fitting method that does not require the knowledge of the PSD of the background noise. The method is based on the analytical marginalization of the posterior parameter probability density with respect to the background noise PSD, and returns an estimate both for the fitting parameters and for the PSD. We show that both these estimates are unbiased, and that, when using averaged Welchs periodograms for the residuals, the estimate of the PSD is consistent, as its error tends to zero with the inverse square root of the number of averaged periodograms. Additionally, we find that the method is equivalent to some implementations of iteratively reweighted least-squares fitting. We have tested the method both on simulated data of known PSD and on data from several experiments performed with the LISA Pathfinder end-to-end mission simulator.
An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition
Mousavi, S. M.; Langston, C. A.
2016-12-01
Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http
The influence of noise on nonlinear time series detection based on Volterra-Wiener-Korenberg model
Energy Technology Data Exchange (ETDEWEB)
Lei Min [State Key Laboratory of Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai 200030 (China)], E-mail: leimin@sjtu.edu.cn; Meng Guang [State Key Laboratory of Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai 200030 (China)
2008-04-15
This paper studies the influence of noises on Volterra-Wiener-Korenberg (VWK) nonlinear test model. Our numerical results reveal that different types of noises lead to different behavior of VWK model detection. For dynamic noise, it is difficult to distinguish chaos from nonchaotic but nonlinear determinism. For time series, measure noise has no impact on chaos determinism detection. This paper also discusses various behavior of VWK model detection with surrogate data for different noises.
Effects on noise properties of GPS time series caused by higher-order ionospheric corrections
Jiang, Weiping; Deng, Liansheng; Li, Zhao; Zhou, Xiaohui; Liu, Hongfei
2014-04-01
Higher-order ionospheric (HOI) effects are one of the principal technique-specific error sources in precise global positioning system (GPS) analysis. These effects also influence the non-linear characteristics of GPS coordinate time series. In this paper, we investigate these effects on coordinate time series in terms of seasonal variations and noise amplitudes. Both power spectral techniques and maximum likelihood estimators (MLE) are used to evaluate these effects quantitatively and qualitatively. Our results show an overall improvement for the analysis of global sites if HOI effects are considered. We note that the noise spectral index that is used for the determination of the optimal noise models in our analysis ranged between -1 and 0 both with and without HOI corrections, implying that the coloured noise cannot be removed by these corrections. However, the corrections were found to have improved noise properties for global sites. After the corrections were applied, the noise amplitudes at most sites decreased, among which the white noise amplitudes decreased remarkably. The white noise amplitudes of up to 81.8% of the selected sites decreased in the up component, and the flicker noise of 67.5% of the sites decreased in the north component. Stacked periodogram results show that, no matter whether the HOI effects are considered or not, a common fundamental period of 1.04 cycles per year (cpy), together with the expected annual and semi-annual signals, can explain all peaks of the north and up components well. For the east component, however, reasonable results can be obtained only based on HOI corrections. HOI corrections are useful for better detecting the periodic signals in GPS coordinate time series. Moreover, the corrections contributed partly to the seasonal variations of the selected sites, especially for the up component. Statistically, HOI corrections reduced more than 50% and more than 65% of the annual and semi-annual amplitudes respectively at the
Ma, Liya; Skoblenick, Kevin; Seamans, Jeremy K; Everling, Stefan
2015-08-19
Working memory dysfunction is an especially debilitating symptom in schizophrenia. The NMDA antagonist ketamine has been successfully used to model working memory deficits in both rodents and nonhuman primates, but how it affects the strength and the consistency of working memory representations remains unclear. Here we recorded single-neuron activity in the lateral prefrontal cortex of macaque monkeys before and after the administration of subanesthetic doses of ketamine in a rule-based working memory task. The rule was instructed with a color cue before each delay period and dictated the correct prosaccadic or antisaccadic response to a peripheral stimulus appearing after the delay. We found that acute ketamine injections both weakened the rule signal across all delay periods and amplified the trial-to-trial variance in neural activities (i.e., noise), both within individual neurons and at the ensemble level, resulting in impaired performance. In the minority of postinjection trials when the animals responded correctly, the preservation of the signal strength during the delay periods was predictive of their subsequent success. Our findings suggest that NMDA receptor function may be critical for establishing the optimal signal-to-noise ratio in information representation by ensembles of prefrontal cortex neurons. In schizophrenia patients, working memory deficit is highly debilitating and currently without any efficacious treatment. An improved understanding of the pathophysiology of this symptom may provide critical information to treatment development. The NMDA antagonist ketamine, when injected at a subanesthetic dose, produces working memory deficit and other schizophrenia-like symptoms in humans and other animals. Here we investigated the effects of ketamine on the representation of abstract rules by prefrontal neurons, while macaque monkeys held the rules in working memory before responding accordingly. We found that ketamine weakened the signal-to-noise
Directory of Open Access Journals (Sweden)
L.F.P. Franca
2003-01-01
Full Text Available This contribution presents an investigation on noise sensitivity of some of the most disseminated techniques employed to estimate Lyapunov exponents from time series. Since noise contamination is unavoidable in cases of data acquisition, it is important to recognize techniques that could be employed for a correct identification of chaos. State space reconstruction and the determination of Lyapunov exponents are carried out to investigate the response of a nonlinear pendulum. Signals are generated by numerical integration of the mathematical model, selecting a single variable of the system as a time series. In order to simulate experimental data sets, a random noise is introduced in the signal. Basically, the analyses of periodic and chaotic motions are carried out. Results obtained from mathematical model are compared with the one obtained from time series analysis, evaluating noise sensitivity. This procedure allows the identification of the best techniques to be employed in the analysis of experimental data.
Noise Reduction for Nonlinear Nonstationary Time Series Data using Averaging Intrinsic Mode Function
Directory of Open Access Journals (Sweden)
Christofer Toumazou
2013-07-01
Full Text Available A novel noise filtering algorithm based on averaging Intrinsic Mode Function (aIMF, which is a derivation of Empirical Mode Decomposition (EMD, is proposed to remove white-Gaussian noise of foreign currency exchange rates that are nonlinear nonstationary times series signals. Noise patterns with different amplitudes and frequencies were randomly mixed into the five exchange rates. A number of filters, namely; Extended Kalman Filter (EKF, Wavelet Transform (WT, Particle Filter (PF and the averaging Intrinsic Mode Function (aIMF algorithm were used to compare filtering and smoothing performance. The aIMF algorithm demonstrated high noise reduction among the performance of these filters.
Characterizing and estimating noise in InSAR and InSAR time series with MODIS
Barnhart, William D.; Lohman, Rowena B.
2013-01-01
InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.
Spatio-temporal chaos and thermal noise in Josephson junction series arrays
International Nuclear Information System (INIS)
Dominguez, D.; Cerdeira, H.A.
1995-01-01
We study underdamped Josephson junction series arrays that are globally coupled through a resistive shunting load and driven by an rf bias current. We find that they can be an experimental realization of many phenomena currently studied in globally coupled logistic map. Depending on the bias current the array can show Shapiro steps but also spatio-temporal chaos or ''turbulence'' in the IV characteristics. In the turbulent phase there is a saturation of the broad band noise for a large number of junctions. This corresponds to a break down of the law of large numbers as seen in globally coupled maps. We study this phenomenon as a function of thermal noise. We find that when increasing the temperature the broad band noise decreases. (author). 8 refs, 1 fig
Schwager, Monika; Johst, Karin; Jeltsch, Florian
2006-06-01
Recent theoretical studies have shown contrasting effects of temporal correlation of environmental fluctuations (red noise) on the risk of population extinction. It is still debated whether and under which conditions red noise increases or decreases extinction risk compared with uncorrelated (white) noise. Here, we explain the opposing effects by introducing two features of red noise time series. On the one hand, positive autocorrelation increases the probability of series of poor environmental conditions, implying increasing extinction risk. On the other hand, for a given time period, the probability of at least one extremely bad year ("catastrophe") is reduced compared with white noise, implying decreasing extinction risk. Which of these two features determines extinction risk depends on the strength of environmental fluctuations and the sensitivity of population dynamics to these fluctuations. If extreme (catastrophic) events can occur (strong noise) or sensitivity is high (overcompensatory density dependence), then temporal correlation decreases extinction risk; otherwise, it increases it. Thus, our results provide a simple explanation for the contrasting previous findings and are a crucial step toward a general understanding of the effect of noise color on extinction risk.
6j-symbols for symmetric representations of SO(n) as the double series
International Nuclear Information System (INIS)
Alisauskas, Sigitas
2002-01-01
The corrected triple sum expression of Alisauskas (1987 J. Phys. A: Math. Gen. 20 35) for the recoupling (Racah) coefficients (6j-symbols) of the symmetric (most degenerate) representations of the orthogonal groups SO(n) (previously derived from the fourfold sum expression of Alisauskas also related to the result of Hormess and Junker (1999 J. Phys. A: Math. Gen. 32 4249) is rearranged into three new different double sum expressions (related to the hypergeometric Kampe de Feriet type series) and a new triple sum expression with preferable summation condition. The Regge type symmetry of special 6j-symbols of the orthogonal groups SO(n) in terms of special Kampe de Feriet F 1:4 1:3 series is revealed. The recoupling coefficients for antisymmetric representations of symplectic group Sp(2n) are derived using their relation with the recoupling coefficients of the formal orthogonal group SO(-2n)
A simple and fast representation space for classifying complex time series
International Nuclear Information System (INIS)
Zunino, Luciano; Olivares, Felipe; Bariviera, Aurelio F.; Rosso, Osvaldo A.
2017-01-01
In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease. - Highlights: • A bidimensional scheme has been tested for classification purposes. • A multiscale generalization is introduced. • Several practical applications confirm its usefulness. • Different sets of financial and physiological data are efficiently distinguished. • This multiscale bidimensional approach has high potential as discriminative tool.
A simple and fast representation space for classifying complex time series
Energy Technology Data Exchange (ETDEWEB)
Zunino, Luciano, E-mail: lucianoz@ciop.unlp.edu.ar [Centro de Investigaciones Ópticas (CONICET La Plata – CIC), C.C. 3, 1897 Gonnet (Argentina); Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), 1900 La Plata (Argentina); Olivares, Felipe, E-mail: olivaresfe@gmail.com [Instituto de Física, Pontificia Universidad Católica de Valparaíso (PUCV), 23-40025 Valparaíso (Chile); Bariviera, Aurelio F., E-mail: aurelio.fernandez@urv.cat [Department of Business, Universitat Rovira i Virgili, Av. Universitat 1, 43204 Reus (Spain); Rosso, Osvaldo A., E-mail: oarosso@gmail.com [Instituto de Física, Universidade Federal de Alagoas (UFAL), BR 104 Norte km 97, 57072-970, Maceió, Alagoas (Brazil); Instituto Tecnológico de Buenos Aires (ITBA) and CONICET, C1106ACD, Av. Eduardo Madero 399, Ciudad Autónoma de Buenos Aires (Argentina); Complex Systems Group, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Av. Mons. Álvaro del Portillo 12.455, Las Condes, Santiago (Chile)
2017-03-18
In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease. - Highlights: • A bidimensional scheme has been tested for classification purposes. • A multiscale generalization is introduced. • Several practical applications confirm its usefulness. • Different sets of financial and physiological data are efficiently distinguished. • This multiscale bidimensional approach has high potential as discriminative tool.
Directory of Open Access Journals (Sweden)
Snezhana Georgieva Gocheva-Ilieva
2013-01-01
Full Text Available There are obtained integral form and recurrence representations for some Fourier series and connected with them Favard constants. The method is based on preliminary integration of Fourier series which permits to establish general recursion formulas for Favard constants. This gives the opportunity for effective summation of infinite series and calculation of some classes of multiple singular integrals by the Favard constants.
Discrete series representations for sl(2|1), Meixner polynomials and oscillator models
International Nuclear Information System (INIS)
Jafarov, E I; Van der Jeugt, J
2012-01-01
We explore a model for a one-dimensional quantum oscillator based on the Lie superalgebra sl(2|1). For this purpose, a class of discrete series representations of sl(2|1) is constructed, each representation characterized by a real number β > 0. In this model, the position and momentum operators of the oscillator are odd elements of sl(2|1) and their expressions involve an arbitrary parameter γ. In each representation, the spectrum of the Hamiltonian is the same as that of a canonical oscillator. The spectrum of a position operator can be continuous or infinite discrete, depending on the value of γ. We determine the position wavefunctions both in the continuous and the discrete case and discuss their properties. In the discrete case, these wavefunctions are given in terms of Meixner polynomials. From the embedding osp(1|2) subset of sl(2|1), it can be seen why the case γ = 1 corresponds to a paraboson oscillator. Consequently, taking the values (β, γ) = (1/2, 1) in the sl(2|1) model yields a canonical oscillator. (paper)
Discrete Data Qualification System and Method Comprising Noise Series Fault Detection
Fulton, Christopher; Wong, Edmond; Melcher, Kevin; Bickford, Randall
2013-01-01
A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.
Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition
Directory of Open Access Journals (Sweden)
Md. Rabiul Islam
2012-01-01
Full Text Available This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition (MEMD is employed here for multiband representation of multichannel financial time series together. Autoregressive moving average (ARMA model is used in prediction of individual subband of any time series data. Then all the predicted subband signals are summed up to obtain the overall prediction. The ARMA model works better for stationary signal. With multiband representation, each subband becomes a band-limited (narrow band signal and hence better prediction is achieved. The performance of the proposed MEMD-ARMA model is compared with classical EMD, discrete wavelet transform (DWT, and with full band ARMA model in terms of signal-to-noise ratio (SNR and mean square error (MSE between the original and predicted time series. The simulation results show that the MEMD-ARMA-based method performs better than the other methods.
Berendrecht, W.L.; Heemink, A.W.; Geer, F.C. van; Gehrels, J.C.
2003-01-01
A state-space representation of the transfer function-noise (TFN) model allows the choice of a modeling (input) interval that is smaller than the measuring interval of the output variable. Since in geohydrological applications the interval of the available input series (precipitation excess) is
Distinguishing deterministic and noise components in ELM time series
International Nuclear Information System (INIS)
Zvejnieks, G.; Kuzovkov, V.N
2004-01-01
Full text: One of the main problems in the preliminary data analysis is distinguishing the deterministic and noise components in the experimental signals. For example, in plasma physics the question arises analyzing edge localized modes (ELMs): is observed ELM behavior governed by a complicate deterministic chaos or just by random processes. We have developed methodology based on financial engineering principles, which allows us to distinguish deterministic and noise components. We extended the linear auto regression method (AR) by including the non-linearity (NAR method). As a starting point we have chosen the nonlinearity in the polynomial form, however, the NAR method can be extended to any other type of non-linear functions. The best polynomial model describing the experimental ELM time series was selected using Bayesian Information Criterion (BIC). With this method we have analyzed type I ELM behavior in a subset of ASDEX Upgrade shots. Obtained results indicate that a linear AR model can describe the ELM behavior. In turn, it means that type I ELM behavior is of a relaxation or random type
Wu, Yue; Shang, Pengjian; Li, Yilong
2018-03-01
A modified multiscale sample entropy measure based on symbolic representation and similarity (MSEBSS) is proposed in this paper to research the complexity of stock markets. The modified algorithm reduces the probability of inducing undefined entropies and is confirmed to be robust to strong noise. Considering the validity and accuracy, MSEBSS is more reliable than Multiscale entropy (MSE) for time series mingled with much noise like financial time series. We apply MSEBSS to financial markets and results show American stock markets have the lowest complexity compared with European and Asian markets. There are exceptions to the regularity that stock markets show a decreasing complexity over the time scale, indicating a periodicity at certain scales. Based on MSEBSS, we introduce the modified multiscale cross-sample entropy measure based on symbolic representation and similarity (MCSEBSS) to consider the degree of the asynchrony between distinct time series. Stock markets from the same area have higher synchrony than those from different areas. And for stock markets having relative high synchrony, the entropy values will decrease with the increasing scale factor. While for stock markets having high asynchrony, the entropy values will not decrease with the increasing scale factor sometimes they tend to increase. So both MSEBSS and MCSEBSS are able to distinguish stock markets of different areas, and they are more helpful if used together for studying other features of financial time series.
SimpleTimeseries: Towards a Standard Representation of Astronomical Time-Series
Brewer, John Michael; Bloom, J. S.; Starr, D.
2010-01-01
Centuries of astrophysical data will soon be eclipsed by the unprecedented number of novel events regularly captured by large scale synoptic surveys. In the past, a stately accumulation of data could await inclusion in catalogs. More recently, digital catalogs have been placed on websites, or forwarded in e-mails. Fully exploiting the science opportunities of this new era will require much more rapid and standardized data exchange. With abundant novel sources to choose from, the limited followup resources available will need regularized data formats to help in decision making, whether the ultimate decisions lie with a human or a machine. The Berkeley Transients Classification Pipeline (TCP) has developed an XML based time-series format to exchange data within the context of the Palomar Transients Factory (PTF). The benefit of a standard time-series representation lies in promulgating it beyond just one collaboration and so we are publicly releasing the format, SimpleTimeseries. It is also slated to describe time-series within the the Virtual Observatory's upcoming VOEvent 2.0 specification. An XML based format allows easy processing by both machines and humans. We have put together examples and documentation which show the flexibilty of SimpleTimeseries on dotastro.org, where you can also find the XML schema, and public light curves in the new format.
GEKF, GUKF and GGPF based prediction of chaotic time-series with additive and multiplicative noises
International Nuclear Information System (INIS)
Wu Xuedong; Song Zhihuan
2008-01-01
On the assumption that random interruptions in the observation process are modelled by a sequence of independent Bernoulli random variables, this paper generalize the extended Kalman filtering (EKF), the unscented Kalman filtering (UKF) and the Gaussian particle filtering (GPF) to the case in which there is a positive probability that the observation in each time consists of noise alone and does not contain the chaotic signal (These generalized novel algorithms are referred to as GEKF, GUKF and GGPF correspondingly in this paper). Using weights and network output of neural networks to constitute state equation and observation equation for chaotic time-series prediction to obtain the linear system state transition equation with continuous update scheme in an online fashion, and the prediction results of chaotic time series represented by the predicted observation value, these proposed novel algorithms are applied to the prediction of Mackey–Glass time-series with additive and multiplicative noises. Simulation results prove that the GGPF provides a relatively better prediction performance in comparison with GEKF and GUKF. (general)
International Nuclear Information System (INIS)
Accardi, Luigi; Boukas, Andreas
2008-01-01
The identification of the *-Lie algebra of the renormalized higher powers of White noise (RHPWN) and the analytic continuation of the second quantized centreless Virasoro (or Witt)-Zamolodchikov-w ∞ *-Lie algebra of conformal field theory and high-energy physics, was recently established on results obtained. In the present paper, we show how the RHPWN Fock kernels must be truncated in order to be positive semi-definite and we obtain a Fock representation of the two algebras. We show that the truncated renormalized higher powers of White noise (TRHPWN) Fock spaces of order ≥2 host the continuous binomial and beta processes
WANG, D.; Wang, Y.; Zeng, X.
2017-12-01
Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.
An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
Directory of Open Access Journals (Sweden)
Stavros-Richard G. Christopoulos
2017-01-01
Full Text Available Recently, the study of the coherent noise model has led to a simple (binary prediction algorithm for the forthcoming earthquake magnitude in aftershock sequences. This algorithm is based on the concept of natural time and exploits the complexity exhibited by the coherent noise model. Here, using the relocated catalogue from Southern California Seismic Network for 1981 to June 2011, we evaluate the application of this algorithm for the aftershocks of strong earthquakes of magnitude M≥6. The study is also extended by using the Global Centroid Moment Tensor Project catalogue to the case of the six strongest earthquakes in the Earth during the last almost forty years. The predictor time series exhibits the ubiquitous 1/f noise behavior.
Representation of neutron noise data using neural networks
International Nuclear Information System (INIS)
Korsah, K.; Damiano, B.; Wood, R.T.
1992-01-01
This paper describes a neural network-based method of representing neutron noise spectra using a model developed at the Oak Ridge National Laboratory (ORNL). The backpropagation neural network learned to represent neutron noise data in terms of four descriptors, and the network response matched calculated values to within 3.5 percent. These preliminary results are encouraging, and further research is directed towards the application of neural networks in a diagnostics system for the identification of the causes of changes in structural spectral resonances. This work is part of our current investigation of advanced technologies such as expert systems and neural networks for neutron noise data reduction, analysis, and interpretation. The objective is to improve the state-of-the-art of noise analysis as a diagnostic tool for nuclear power plants and other mechanical systems
Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations
Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James
2013-01-01
This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks [Scargle 1998]-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piece- wise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by [Arias-Castro, Donoho and Huo 2003]. In the spirit of Reproducible Research [Donoho et al. (2008)] all of the code and data necessary to reproduce all of the figures in this paper are included as auxiliary material.
STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS
Energy Technology Data Exchange (ETDEWEB)
Scargle, Jeffrey D. [Space Science and Astrobiology Division, MS 245-3, NASA Ames Research Center, Moffett Field, CA 94035-1000 (United States); Norris, Jay P. [Physics Department, Boise State University, 2110 University Drive, Boise, ID 83725-1570 (United States); Jackson, Brad [The Center for Applied Mathematics and Computer Science, Department of Mathematics, San Jose State University, One Washington Square, MH 308, San Jose, CA 95192-0103 (United States); Chiang, James, E-mail: jeffrey.d.scargle@nasa.gov [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States)
2013-02-20
This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.
STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS
International Nuclear Information System (INIS)
Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James
2013-01-01
This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it—an improved and generalized version of Bayesian Blocks—that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.
Detecting nonlinearity in time series driven by non-Gaussian noise: the case of river flows
Directory of Open Access Journals (Sweden)
F. Laio
2004-01-01
Full Text Available Several methods exist for the detection of nonlinearity in univariate time series. In the present work we consider riverflow time series to infer the dynamical characteristics of the rainfall-runoff transformation. It is shown that the non-Gaussian nature of the driving force (rainfall can distort the results of such methods, in particular when surrogate data techniques are used. Deterministic versus stochastic (DVS plots, conditionally applied to the decay phases of the time series, are instead proved to be a suitable tool to detect nonlinearity in processes driven by non-Gaussian (Poissonian noise. An application to daily discharges from three Italian rivers provides important clues to the presence of nonlinearity in the rainfall-runoff transformation.
Indian Academy of Sciences (India)
2016-08-26
Aug 26, 2016 ... http://www.ias.ac.in/article/fulltext/pmsc/115/04/0371-0381. Keywords. Inverse binomial series; hypergeometric series; polylogarithms; integral representations. Abstract. In this paper we investigate the series ∑ k = 1 ∞ ( 3 k k ) − 1 k − n x k . Obtaining some integral representations of them, we evaluated the ...
Weighted Discriminative Dictionary Learning based on Low-rank Representation
International Nuclear Information System (INIS)
Chang, Heyou; Zheng, Hao
2017-01-01
Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)
The representations of Lie groups and geometric quantizations
International Nuclear Information System (INIS)
Zhao Qiang
1998-01-01
In this paper we discuss the relation between representations of Lie groups and geometric quantizations. A series of representations of Lie groups are constructed by geometric quantization of coadjoint orbits. Particularly, all representations of compact Lie groups, holomorphic discrete series of representations and spherical representations of reductive Lie groups are constructed by geometric quantizations of elliptic and hyperbolic coadjoint orbits. (orig.)
Rached, Nadhir B.
2016-12-24
In this paper, we develop a generalized momentbased approach for the evaluation of the outage probability (OP) in the presence of co-channel interference and additive white Gaussian noise. The proposed method allows the evaluation of the OP of the signal-to-interference-plus-noise ratio by a power series expansion in the threshold value. Its main advantage is that it does not require a particular distribution for the interference channels. The only necessary ingredients are a power series expansion for the cumulative distribution function of the desired user power and the cross-moments of the interferers\\' powers. These requirements are easily met in many practical fading models, for which the OP might not be obtained in closed-form expression. For a sake of illustration, we consider the application of our method to the Rician fading environment. Under this setting, we carry out a convergence study of the proposed power series and corroborate the validity of our method for different values of fading parameters and various numbers of co-channel interferers.
Stabilizing simulations of complex stochastic representations for quantum dynamical systems
Energy Technology Data Exchange (ETDEWEB)
Perret, C; Petersen, W P, E-mail: wpp@math.ethz.ch [Seminar for Applied Mathematics, ETH, Zurich (Switzerland)
2011-03-04
Path integral representations of quantum dynamics can often be formulated as stochastic differential equations (SDEs). In a series of papers, Corney and Drummond (2004 Phys. Rev. Lett. 93 260401), Deuar and Drummond (2001 Comput. Phys. Commun. 142 442-5), Drummond and Gardnier (1980 J. Phys. A: Math. Gen. 13 2353-68), Gardiner and Zoller (2004 Quantum Noise: A Handbook of Markovian and Non-Markovian Quantum Stochastic Methods with Applications to Quantum Optics (Springer Series in Synergetics) 3rd edn (Berlin: Springer)) and Gilchrist et al (1997 Phys. Rev. A 55 3014-32) and their collaborators have derived SDEs from coherent states representations for density matrices. Computationally, these SDEs are attractive because they seem simple to simulate. They can be quite unstable, however. In this paper, we consider some of the instabilities and propose a few remedies. Particularly, because the variances of the simulated paths typically grow exponentially, the processes become de-localized in relatively short times. Hence, the issues of boundary conditions and stable integration methods become important. We use the Bose-Einstein Hamiltonian as an example. Our results reveal that it is possible to significantly extend integration times and show the periodic structure of certain functionals.
Sams-Dodd, F; Capranica, R R
1996-10-01
Acoustic signals are generally encoded in the peripheral auditory system of vertebrates by a duality scheme. For frequency components that fall within the excitatory tuning curve, individual eighth nerve fibers can encode the effective spectral energy by a spike-rate code, while simultaneously preserving the signal waveform periodicity of lower frequency components by phase-locked spike-train discharges. To explore how robust this duality of representation may be in the presence of noise, we recorded the responses of auditory fibers in the eighth nerve of the Tokay gecko to tonal stimuli when masking noise was added simultaneously. We found that their spike-rate functions reached plateau levels fairly rapidly in the presence of noise, so the ability to signal the presence of a tone by a concomitant change in firing rate was quickly lost. On the other hand, their synchronization functions maintained a high degree of phase-locked firings to the tone even in the presence of high-intensity masking noise, thus enabling a robust detection of the tonal signal. Critical ratios (CR) and critical bandwidths showed that in the frequency range where units are able to phaselock to the tonal periodicity, the CR bands were relatively narrow and the bandwidths were independent of noise level. However, to higher frequency tones where phaselocking fails and only spike-rate codes apply, the CR bands were much wider and depended upon noise level, so that their ability to filter tones out of a noisy background degraded with increasing noise levels. The greater robustness of phase-locked temporal encoding contrasted with spike-rate coding verifies a important advantage in using lower frequency signals for communication in noisy environments.
A high signal-to-noise ratio composite quasar spectrum
International Nuclear Information System (INIS)
Francis, P.J.; Hewett, P.C.; Foltz, C.B.; Chaffee, F.H.; Weymann, R.J.
1991-01-01
A very high signal-to-noise ratio (S/N of about 400) composite spectrum of the rest-frame ultraviolet and optical region of high luminosity quasars is presented. The spectrum is derived from 718 individual spectra obtained as part of the Large Bright Quasar Survey. The moderate resolution, 4A or less, and high signal-to-noise ratio allow numerous weak emission features to be identified. Of particular note is the large equivalent-width of the Fe II emission in the rest-frame ultraviolet and the blue continuum slope of the composite. The primary aim of this paper is to provide a reference spectrum for use in line identifications, and a series of large-scale representations of the composite spectrum are shown. A measure of the standard deviation of the individual quasar spectra from the composite spectrum is also presented. 12 refs
Guarnaccia, Claudio; Quartieri, Joseph; Tepedino, Carmine
2017-06-01
One of the most hazardous physical polluting agents, considering their effects on human health, is acoustical noise. Airports are a strong source of acoustical noise, due to the airplanes turbines, to the aero-dynamical noise of transits, to the acceleration or the breaking during the take-off and landing phases of aircrafts, to the road traffic around the airport, etc.. The monitoring and the prediction of the acoustical level emitted by airports can be very useful to assess the impact on human health and activities. In the airports noise scenario, thanks to flights scheduling, the predominant sources may have a periodic behaviour. Thus, a Time Series Analysis approach can be adopted, considering that a general trend and a seasonal behaviour can be highlighted and used to build a predictive model. In this paper, two different approaches are adopted, thus two predictive models are constructed and tested. The first model is based on deterministic decomposition and is built composing the trend, that is the long term behaviour, the seasonality, that is the periodic component, and the random variations. The second model is based on seasonal autoregressive moving average, and it belongs to the stochastic class of models. The two different models are fitted on an acoustical level dataset collected close to the Nice (France) international airport. Results will be encouraging and will show good prediction performances of both the adopted strategies. A residual analysis is performed, in order to quantify the forecasting error features.
International Nuclear Information System (INIS)
Litak, Grzegorz; Taccani, Rodolfo; Radu, Robert; Urbanowicz, Krzysztof; HoIyst, Janusz A.; Wendeker, MirosIaw; Giadrossi, Alessandro
2005-01-01
We report our results on non-periodic experimental time series of pressure in a single cylinder spark ignition engine. The experiments were performed for different levels of loading. We estimate the noise level in internal pressure calculating the coarse-grained entropy from variations of maximal pressures in successive cycles. The results show that the dynamics of the combustion is a non-linear multidimensional process mediated by noise. Our results show that so defined level of noise in internal pressure is not monotonous function of loading
Bahaz, Mohamed; Benzid, Redha
2018-03-01
Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.
Restoration for Noise Removal in Quantum Images
Liu, Kai; Zhang, Yi; Lu, Kai; Wang, Xiaoping
2017-09-01
Quantum computation has become increasingly attractive in the past few decades due to its extraordinary performance. As a result, some studies focusing on image representation and processing via quantum mechanics have been done. However, few of them have considered the quantum operations for images restoration. To address this problem, three noise removal algorithms are proposed in this paper based on the novel enhanced quantum representation model, oriented to two kinds of noise pollution (Salt-and-Pepper noise and Gaussian noise). For the first algorithm Q-Mean, it is designed to remove the Salt-and-Pepper noise. The noise points are extracted through comparisons with the adjacent pixel values, after which the restoration operation is finished by mean filtering. As for the second method Q-Gauss, a special mask is applied to weaken the Gaussian noise pollution. The third algorithm Q-Adapt is effective for the source image containing unknown noise. The type of noise can be judged through the quantum statistic operations for the color value of the whole image, and then different noise removal algorithms are used to conduct image restoration respectively. Performance analysis reveals that our methods can offer high restoration quality and achieve significant speedup through inherent parallelism of quantum computation.
Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin
2018-01-01
Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Huo, W.M.
1977-01-01
The convergence and range of applicability of the Bonham series representation of the Born--Oppenheimer exchange amplitude is investigated. Numerical calculations on 1 1 S→2 3 S and 1 1 S→2 3 P of He by electron impact demonstrate that the first three terms of the Bonham series can provide an adequate representation of the Born--Oppenheimer amplitude from high energies down to near threshold. The three-term Bonham series is then used to represent the Hartree--Fock exchange kernel in momentum space, which has been shown by Lassettre to be proportional to the Born--Oppenheimer amplitude. Inverse Fourier transform, plus an additional approximation of replacing the momentum which appears as an expansion parameter in the Bonham series by its averge value, gives us a local exchange potential. If the averge momentum in the Thomas--Fermi model is used, the first term of the local exchange potential is just the electron gas exchange potential. A second term corresponding to a correction for the inhomogeneity in the electron gas density, is also obtained. No adjustable parameter is involved. Exchange energies of He, Be, and Ne calculated using the local exchange potential agree much better with the Hartree--Fock results than the electron gas model
Background noise exerts diverse effects on the cortical encoding of foreground sounds.
Malone, B J; Heiser, Marc A; Beitel, Ralph E; Schreiner, Christoph E
2017-08-01
In natural listening conditions, many sounds must be detected and identified in the context of competing sound sources, which function as background noise. Traditionally, noise is thought to degrade the cortical representation of sounds by suppressing responses and increasing response variability. However, recent studies of neural network models and brain slices have shown that background synaptic noise can improve the detection of signals. Because acoustic noise affects the synaptic background activity of cortical networks, it may improve the cortical responses to signals. We used spike train decoding techniques to determine the functional effects of a continuous white noise background on the responses of clusters of neurons in auditory cortex to foreground signals, specifically frequency-modulated sweeps (FMs) of different velocities, directions, and amplitudes. Whereas the addition of noise progressively suppressed the FM responses of some cortical sites in the core fields with decreasing signal-to-noise ratios (SNRs), the stimulus representation remained robust or was even significantly enhanced at specific SNRs in many others. Even though the background noise level was typically not explicitly encoded in cortical responses, significant information about noise context could be decoded from cortical responses on the basis of how the neural representation of the foreground sweeps was affected. These findings demonstrate significant diversity in signal in noise processing even within the core auditory fields that could support noise-robust hearing across a wide range of listening conditions. NEW & NOTEWORTHY The ability to detect and discriminate sounds in background noise is critical for our ability to communicate. The neural basis of robust perceptual performance in noise is not well understood. We identified neuronal populations in core auditory cortex of squirrel monkeys that differ in how they process foreground signals in background noise and that may
Effect of noise on fractal structure
Energy Technology Data Exchange (ETDEWEB)
Serletis, Demitre [Division of Neurosurgery, Hospital for Sick Children, 1504-555 University Avenue, Toronto, Ont., M5G 1X8 (Canada)], E-mail: demitre.serletis@utoronto.ca
2008-11-15
In this paper, I investigate the effect of dynamical noise on the estimation of the Hurst exponent and the fractal dimension of time series. Recently, Serletis et al. [Serletis, Apostolos, Asghar Shahmoradi, Demitre Serletis. Effect of noise on estimation of Lyapunov exponents from a time series. Chaos, Solitons and Fractals, forthcoming] have shown that dynamical noise can make the detection of chaotic dynamics very difficult, and Serletis et al. [Serletis, Apostolos, Asghar Shahmoradi, Demitre Serletis. Effect of noise on the bifurcation behavior of dynamical systems. Chaos, Solitons and Fractals, forthcoming] have shown that dynamical noise can also shift bifurcation points and produce noise-induced transitions, making the determination of bifurcation boundaries difficult. Here I apply the detrending moving average (DMA) method, recently developed by Alessio et al. [Alessio E, Carbone A, Castelli G, Frappietro V. Second-order moving average and scaling of stochastic time series. The Eur Phys J B 2002;27:197-200] and Carbone et al. [Carbone A, Castelli G, Stanley HE. Time-dependent Hurst exponent in financial time series. Physica A 2004;344:267-71; Carbone A, Castelli G, Stanley HE. Analysis of clusters formed by the moving average of a long-range correlated time series. Phys Rev E 2004;69:026105], to estimate the Hurst exponent of a Brownian walk with a Hurst exponent of 0.5, coupled with low and high intensity noise, and show that dynamical noise has no effect on fractal structure.
Sparse Representation Denoising for Radar High Resolution Range Profiling
Directory of Open Access Journals (Sweden)
Min Li
2014-01-01
Full Text Available Radar high resolution range profile has attracted considerable attention in radar automatic target recognition. In practice, radar return is usually contaminated by noise, which results in profile distortion and recognition performance degradation. To deal with this problem, in this paper, a novel denoising method based on sparse representation is proposed to remove the Gaussian white additive noise. The return is sparsely described in the Fourier redundant dictionary and the denoising problem is described as a sparse representation model. Noise level of the return, which is crucial to the denoising performance but often unknown, is estimated by performing subspace method on the sliding subsequence correlation matrix. Sliding window process enables noise level estimation using only one observation sequence, not only guaranteeing estimation efficiency but also avoiding the influence of profile time-shift sensitivity. Experimental results show that the proposed method can effectively improve the signal-to-noise ratio of the return, leading to a high-quality profile.
Energy Technology Data Exchange (ETDEWEB)
Wang, Ruofan; Wang, Jiang; Deng, Bin, E-mail: dengbin@tju.edu.cn; Liu, Chen; Wei, Xile [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China); Tsang, K. M.; Chan, W. L. [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)
2014-03-15
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.
International Nuclear Information System (INIS)
Wang, Ruofan; Wang, Jiang; Deng, Bin; Liu, Chen; Wei, Xile; Tsang, K. M.; Chan, W. L.
2014-01-01
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease
Wang, Ruofan; Wang, Jiang; Deng, Bin; Liu, Chen; Wei, Xile; Tsang, K. M.; Chan, W. L.
2014-03-01
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.
Learning Document Semantic Representation with Hybrid Deep Belief Network
Directory of Open Access Journals (Sweden)
Yan Yan
2015-01-01
it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.
Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter
Directory of Open Access Journals (Sweden)
Álvaro Moreno
2014-08-01
Full Text Available Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted local regression filter (LOESS and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG, smoothing spline (SSP, Interpolation for Data Reconstruction (IDR and adaptive Savitzky-Golay (ASG. This paper evaluates the main advantages and drawbacks of the considered techniques. The results have shown that ASG and the adapted LOESS perform better in recovering fAPAR time series over multiple controlled noisy scenarios. Both methods can robustly reconstruct the fAPAR trajectories, reducing the noise up to 80% in the worst simulation scenario, which might be attributed to the quality control (QC MODIS information incorporated into these filtering algorithms, their flexibility and adaptation to the upper envelope. The adapted LOESS is particularly resistant to outliers. This method clearly outperforms the other considered methods to deal with the high presence of gaps and noise in satellite data records. The low RMSE and biases obtained with the LOESS method (|rMBE| < 8%; rRMSE < 20% reveals an optimal reconstruction even in most extreme situations with long seasonal gaps. An example of application of the LOESS method to fill in invalid values in real MODIS images presenting persistent cloud and snow coverage is also shown. The LOESS approach is recommended in most remote sensing applications, such as gap-filling, cloud-replacement, and observing temporal
Hahn, Andrew D; Rowe, Daniel B
2012-02-01
As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for dynamic main field fluctuations and motion regression. Our findings suggest that including physiologic regressors provides some benefit in terms of reduction in phase noise power, but it is small compared to the benefit of dynamic field corrections and use of estimated motion parameters as nuisance regressors. Additionally, we show that the use of all three techniques reduces phase variance substantially, removes undesirable spatial phase correlations and improves detection of the functional response in magnitude and phase. Copyright © 2011 Elsevier Inc. All rights reserved.
Phase Noise Compensation for OFDM Systems
Leshem, Amir; Yemini, Michal
2017-11-01
We describe a low complexity method for time domain compensation of phase noise in OFDM systems. We extend existing methods in several respects. First we suggest using the Karhunen-Lo\\'{e}ve representation of the phase noise process to estimate the phase noise. We then derive an improved datadirected choice of basis elements for LS phase noise estimation and present its total least square counterpart problem. The proposed method helps overcome one of the major weaknesses of OFDM systems. We also generalize the time domain phase noise compensation to the multiuser MIMO context. Finally we present simulation results using both simulated and measured phased noise. We quantify the tracking performance in the presence of residual carrier offset.
Satellite Image Time Series Decomposition Based on EEMD
Directory of Open Access Journals (Sweden)
Yun-long Kong
2015-11-01
Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.
Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J
2013-01-01
Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.
Understanding representations in design
DEFF Research Database (Denmark)
Bødker, Susanne
1998-01-01
Representing computer applications and their use is an important aspect of design. In various ways, designers need to externalize design proposals and present them to other designers, users, or managers. This article deals with understanding design representations and the work they do in design....... The article is based on a series of theoretical concepts coming out of studies of scientific and other work practices and on practical experiences from design of computer applications. The article presents alternatives to the ideas that design representations are mappings of present or future work situations...... and computer applications. It suggests that representations are primarily containers of ideas and that representation is situated at the same time as representations are crossing boundaries between various design and use activities. As such, representations should be carriers of their own contexts regarding...
International Nuclear Information System (INIS)
Decanini, Yves; Folacci, Antoine
2006-01-01
Having in mind applications to gravitational wave theory (in connection with the radiation reaction problem), stochastic semiclassical gravity (in connection with the regularization of the noise kernel) and quantum field theory in higher-dimensional curved spacetime (in connection with the Hadamard regularization of the stress-energy tensor), we improve the DeWitt-Schwinger and Hadamard representations of the Feynman propagator of a massive scalar field theory defined on an arbitrary gravitational background by deriving higher-order terms for the covariant Taylor series expansions of the geometrical coefficients--i.e., the DeWitt and Hadamard coefficients--that define them
Precomputing Process Noise Covariance for Onboard Sequential Filters
Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell
2017-01-01
Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.
Directory of Open Access Journals (Sweden)
Nasser Rashidi
2015-03-01
Full Text Available The current study aims at identifying particular ways through which social actors are represented in Summit Series ELT textbooks. It examines cultural load in the textbooks within critical discourse analysis framework, in this case van Leeuwen’s framework. Particularly, the study attempts to explore if values, norms, and roles are culture/context-bound. Results of the analyses showed that among discursive features, Inclusion, Genericization, and Indetermination were used more than Exclusion, Specification, and Determination. Activation was more observed than Passivation, and Categorization had an important function in the representation of some of the social actors along with Assimilation and Impersonalization. The analysis also indicated the impartiality toward the representation of social actors. Moral, social, and personal values were the most disseminated values, while social morality and traditions had the highest occurrence. However, a few discriminative cases were found regarding gender roles. The researchers proposed that Summit Series were less grounded in cultural assumptions/biases. This impartiality eases language learning by keeping learners away from misunderstanding and incomprehensibility.
Hubbard, Harvey H. (Editor)
1993-01-01
In the conference over 100 papers were presented in eight sessions: (1) Emission: Noise Sources; (2) Physical Phenomena; (3) Noise ControlElements; (4) Vibration and Shock: Generation, Transmission, Isolation, and Reduction; (5) Immission: Physical Aspects of Environmental Noise; (6) Immission: Effects of Noise; (7) Analysis; and (8) Requirements. In addition, the distinguished lecture series included presentations on the High Speed Civil Transport and on research from the United Kingdom on aircraft noise effects.
Self-dual continuous series of representations for Uq(sl(2)) and Uq(osp(1 vertical stroke 2))
International Nuclear Information System (INIS)
Hadasz, Leszek; Pawelkiewicz, Michal; Schomerus, Volker
2013-05-01
We determine the Clebsch-Gordan and Racah-Wigner coefficients for continuous series of representations of the quantum deformed algebras U q (sl(2)) and U q (osp(1 vertical stroke 2)). While our results for the former algebra reproduce formulas by Ponsot and Teschner, the expressions for the orthosymplectic algebra are new. Up to some normalization factors, the associated Racah-Wigner coefficients are shown to agree with the fusing matrix in the Neveu-Schwarz sector of N=1 supersymmetric Liouville field theory.
Optimizing the De-Noise Neural Network Model for GPS Time-Series Monitoring of Structures
Directory of Open Access Journals (Sweden)
Mosbeh R. Kaloop
2015-09-01
Full Text Available The Global Positioning System (GPS is recently used widely in structures and other applications. Notwithstanding, the GPS accuracy still suffers from the errors afflicting the measurements, particularly the short-period displacement of structural components. Previously, the multi filter method is utilized to remove the displacement errors. This paper aims at using a novel application for the neural network prediction models to improve the GPS monitoring time series data. Four prediction models for the learning algorithms are applied and used with neural network solutions: back-propagation, Cascade-forward back-propagation, adaptive filter and extended Kalman filter, to estimate which model can be recommended. The noise simulation and bridge’s short-period GPS of the monitoring displacement component of one Hz sampling frequency are used to validate the four models and the previous method. The results show that the Adaptive neural networks filter is suggested for de-noising the observations, specifically for the GPS displacement components of structures. Also, this model is expected to have significant influence on the design of structures in the low frequency responses and measurements’ contents.
Afshinpour, Babak; Hossein-Zadeh, Gholam-Ali; Soltanian-Zadeh, Hamid
2008-06-30
Unknown low frequency fluctuations called "trend" are observed in noisy time-series measured for different applications. In some disciplines, they carry primary information while in other fields such as functional magnetic resonance imaging (fMRI) they carry nuisance effects. In all cases, however, it is necessary to estimate them accurately. In this paper, a method for estimating trend in the presence of fractal noise is proposed and applied to fMRI time-series. To this end, a partly linear model (PLM) is fitted to each time-series. The parametric and nonparametric parts of PLM are considered as contributions of hemodynamic response and trend, respectively. Using the whitening property of wavelet transform, the unknown components of the model are estimated in the wavelet domain. The results of the proposed method are compared to those of other parametric trend-removal approaches such as spline and polynomial models. It is shown that the proposed method improves activation detection and decreases variance of the estimated parameters relative to the other methods.
The ART of representation: Memory reduction and noise tolerance in a neural network vision system
Langley, Christopher S.
The Feature Cerebellar Model Arithmetic Computer (FCMAC) is a multiple-input-single-output neural network that can provide three-degree-of-freedom (3-DOF) pose estimation for a robotic vision system. The FCMAC provides sufficient accuracy to enable a manipulator to grasp an object from an arbitrary pose within its workspace. The network learns an appearance-based representation of an object by storing coarsely quantized feature patterns. As all unique patterns are encoded, the network size grows uncontrollably. A new architecture is introduced herein, which combines the FCMAC with an Adaptive Resonance Theory (ART) network. The ART module categorizes patterns observed during training into a set of prototypes that are used to build the FCMAC. As a result, the network no longer grows without bound, but constrains itself to a user-specified size. Pose estimates remain accurate since the ART layer tends to discard the least relevant information first. The smaller network performs recall faster, and in some cases is better for generalization, resulting in a reduction of error at recall time. The ART-Under-Constraint (ART-C) algorithm is extended to include initial filling with randomly selected patterns (referred to as ART-F). In experiments using a real-world data set, the new network performed equally well using less than one tenth the number of coarse patterns as a regular FCMAC. The FCMAC is also extended to include real-valued input activations. As a result, the network can be tuned to reject a variety of types of noise in the image feature detection. A quantitative analysis of noise tolerance was performed using four synthetic noise algorithms, and a qualitative investigation was made using noisy real-world image data. In validation experiments, the FCMAC system outperformed Radial Basis Function (RBF) networks for the 3-DOF problem, and had accuracy comparable to that of Principal Component Analysis (PCA) and superior to that of Shape Context Matching (SCM), both
A Noise Robust Statistical Texture Model
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus
2002-01-01
Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise......This paper presents a novel approach to the problem of obtaining a low dimensional representation of texture (pixel intensity) variation present in a training set after alignment using a Generalised Procrustes analysis.We extend the conventional analysis of training textures in the Active...
Entanglement dynamics of two-qubit systems in different quantum noises
International Nuclear Information System (INIS)
Pan Chang-Ning; Fang Jian-Shu; Li-Fei; Fang Mao-Fa
2011-01-01
The entanglement dynamics of two-qubit systems in different quantum noises are investigated by means of the operator-sum representation method. We find that, except for the amplitude damping and phase damping quantum noise, the sudden death of entanglement is always observed in different two-qubit systems with generalized amplitude damping and depolarizing quantum noise. (general)
Electronic noise of superconducting tunnel junction detectors
International Nuclear Information System (INIS)
Jochum, J.; Kraus, H.; Gutsche, M.; Kemmather, B.; Feilitzsch, F. v.; Moessbauer, R.L.
1994-01-01
The optimal signal to noise ratio for detectors based on superconducting tunnel junctions is calculated and compared for the cases of a detector consisting of one single tunnel junction, as well as of series and of parallel connections of such tunnel junctions. The influence of 1 / f noise and its dependence on the dynamical resistance of tunnel junctions is discussed quantitatively. A single tunnel junction yields the minimum equivalent noise charge. Such a tunnel junction exhibits the best signal to noise ratio if the signal charge is independent of detector size. In case, signal charge increases with detector size, a parallel or a series connection of tunnel junctions would provide the optimum signal to noise ratio. The equivalent noise charge and the respective signal to noise ratio are deduced as functions of tunnel junction parameters such as tunneling time, quasiparticle lifetime, etc. (orig.)
International Nuclear Information System (INIS)
Moon, Byung Soo; Hwang, In Koo; Chung, Chong Eun; Kwon, Kee Choon; David, E. H.; Kisner, R.A.
2004-06-01
In this report, we first proved that a random signal obtained by taking the sum of a set of signal frequency signals generates a continuous Markov process. We used this random signal to simulate the Johnson noise and verified that the Johnson noise thermometry can be used to improve the measurements of the reactor coolant temperature within an accuracy of below 0.14%. Secondly, by using this random signal we determined the optimal sampling rate when the frequency band of the Johnson noise signal is given. Also the results of our examination on how good the linearity of the Johnson noise is and how large the relative error of the temperature could become when the temperature increases are described. Thirdly, the results of our analysis on a set of the Johnson noise signal blocks taken from a simple electric circuit are described. We showed that the properties of the continuous Markov process are satisfied even when some channel noises are present. Finally, we describe the algorithm we devised to handle the problem of the time lag in the long-term average or the moving average in a transient state. The algorithm is based on the Haar wavelet and is to estimate the transient temperature that has much smaller time delay. We have shown that the algorithm can track the transient temperature successfully
Aerodynamical noise from wind turbine generators
International Nuclear Information System (INIS)
Jakobsen, J.; Andersen, B.
1993-06-01
Two extensive measurement series of noise from wind turbines have been made during different modifications of their rotors. One series focused on the influence from the tip shape on the noise, while the other series dealt with the influence from the trailing edge. The experimental layout for the two investigations was identical. The total A-weighted noise from the wind turbine was measured in 1/3 octave bands from 50 Hz to 10 kHz in 1-minute periods simultaneously with wind speed measurements. The microphone was mounted on a hard board on the ground about 40 m directly downwind of the wind turbine, and the wind speed meter was placed at the same distance upwind of the wind turbine 10 m above ground. Regression analysis was made between noise and wind speed in each 1/3 octave band to determine the spectrum at 8 m/s. During the measurements care was taken to avoid influence from background noise, and the influence from machinery noise was minimized and corrected for. Thus the results display the aerodynamic rotor noise from the wind turbines. By use of this measurement technique, the uncertainty has been reduced to 1.5 - 2 dB per 1/3 octave band in the relevant frequency range and to about 1 dB on the total A-weighted levels. (au) (10 refs.)
International Nuclear Information System (INIS)
Sadeghi, Y.
2006-01-01
Computer Programs are important tools in physics. Analysis of the experimental data and the control of complex handle physical phenomenon and the solution of numerical problem in physics help scientist to the behavior and simulate the process. In this paper, calculation of several Fourier series gives us a visual and analytic impression of data analyses from Fourier series. One of important aspect in data analyses is to find optimum method for de-noising. Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution corresponding to its scale. They have advantages over usual traditional methods in analyzing physical situations where the signal contains discontinuities and sharp spikes. Transformed data by wavelets in frequency space has time information and can clearly show the exact location in time of the discontinuity. This aspect makes wavelets an excellent tool in the field of data analysis. In this paper, we show how Fourier series and wavelets can analyses data in Damavand tokamak. ?
Neutron noise analysis of BWR using time series analysis
International Nuclear Information System (INIS)
Fukunishi, Kohyu
1976-01-01
The main purpose of this paper is to give more quantitative understanding of noise source in neutron flux and to provide a useful tool for the detection and diagnosis of reactor. The space dependent effects of distributed neutron flux signals at the axial direction of two different strings are investigated by the power contribution ratio among neutron fluxes and the incoherent noise spectra of neutron fluxes derived from autoregressive spectra. The signals are measured on the medium sized commercial BWR of 460 MWe in Japan. From the obtained results, local and global noise sources in neutron flux are discussed. This method is indicated to be a useful tool for detection and diagnosis of anomalous phenomena in BWR. (orig./RW) [de
International Nuclear Information System (INIS)
Jóźwiak, Grzegorz
2017-01-01
Scanning probe microscopy (SPM) is a well known tool used for the investigation of phenomena in objects in the nanometer size range. However, quantitative results are limited by the size and the shape of the nanoprobe used in experiments. Blind tip reconstruction (BTR) is a very popular method used to reconstruct the upper boundary on the shape of the probe. This method is known to be very sensitive to all kinds of interference in the atomic force microscopy (AFM) image. Due to mathematical morphology calculus, the interference makes the BTR results biased rather than randomly disrupted. For this reason, the careful choice of methods used for image enhancement and denoising, as well as the shape of a calibration sample are very important. In the paper, the results of thorough investigations on the shape of a calibration standard are shown. A novel shape is proposed and a tool for the simulation of AFM images of this calibration standard was designed. It was shown that careful choice of the initial tip allows us to use images of hole structures to blindly reconstruct the shape of a probe. The simulator was used to test the impact of modern filtration algorithms on the BTR process. These techniques are based on sparse approximation with function dictionaries learned on the basis of an image itself. Various learning algorithms and parameters were tested to determine the optimal combination for sparse representation. It was observed that the strong reduction of noise does not guarantee strong reduction in reconstruction errors. It seems that further improvements will be possible by the combination of BTR and a noise reduction procedure. (paper)
Integral Representations of the Catalan Numbers and Their Applications
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Feng Qi
2017-08-01
Full Text Available In the paper, the authors survey integral representations of the Catalan numbers and the Catalan–Qi function, discuss equivalent relations between these integral representations, supply alternative and new proofs of several integral representations, collect applications of some integral representations, and present sums of several power series whose coefficients involve the Catalan numbers.
Whalen, Anthony D; Declaris, Nicholas
1971-01-01
Detection of Signals in Noise serves as an introduction to the principles and applications of the statistical theory of signal detection. The book discusses probability and random processes; narrowband signals, their complex representation, and their properties described with the aid of the Hilbert transform; and Gaussian-derived processes. The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise. Problem exercises, references, and a supplementary bibliography are included after each c
International Nuclear Information System (INIS)
Panigrahi, Swapnesh; Fade, Julien; Alouini, Mehdi
2015-01-01
We present a contrast-maximizing optimal linear representation of polarimetric images obtained from a snapshot polarimetric camera for enhanced vision of a polarized light source in obscured weather conditions (fog, haze, cloud) over long distances (above 1 km). We quantitatively compare the gain in contrast obtained by different linear representations of the experimental polarimetric images taken during rapidly varying foggy conditions. It is shown that the adaptive image representation that depends on the correlation in background noise fluctuations in the two polarimetric images provides an optimal contrast enhancement over all weather conditions as opposed to a simple difference image which underperforms during low visibility conditions. Finally, we derive the analytic expression of the gain in contrast obtained with this optimal representation and show that the experimental results are in agreement with the assumed correlated Gaussian noise model. (paper)
Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh
2015-09-01
We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs.
Anti-impulse-noise Edge Detection via Anisotropic Morphological Directional Derivatives.
Shui, Peng-Lang; Wang, Fu-Ping
2017-07-13
Traditional differential-based edge detection suffers from abrupt degradation in performance when images are corrupted by impulse noises. The morphological operators such as the median filters and weighted median filters possess the intrinsic ability to counteract impulse noise. In this paper, by combining the biwindow configuration with weighted median filters, anisotropic morphological directional derivatives (AMDD) robust to impulse noise are proposed to measure the local grayscale variation around a pixel. For ideal step edges, the AMDD spatial response and directional representation are derived. The characteristics and edge resolution of two kinds of typical biwindows are analyzed thoroughly. In terms of the AMDD spatial response and directional representation of ideal step edges, the spatial matched filter is used to extract the edge strength map (ESM) from the AMDDs of an image. The spatial and directional matched filters are used to extract the edge direction map (EDM). Embedding the extracted ESM and EDM into the standard route of the differential-based edge detection, an anti-impulse-noise AMDD-based edge detector is constructed. It is compared with the existing state-of-the-art detectors on a recognized image dataset for edge detection evaluation. The results show that it attains competitive performance in noise-free and Gaussian noise cases and the best performance in impulse noise cases.
Directory of Open Access Journals (Sweden)
Derek Attridge
2009-10-01
Full Text Available James Joyce uses both lexical and nonlexical onomatopoeia extensively in _Ulysses_; this essay examines some of the ways in which he employs the latter in order to convey noises of many kinds. Nonlexical onomatopoeia is particularly suited to the evocation of noise, though it can only do so in conjunction with shared literary and linguistic conventions. Several of the characters in _Ulysses_ show an interest in the representation of noise in language, but there are many more examples where there is no evidence of mental processes at work. The reader’s pleasure in Joyce’s nonlexical onomatopoeia is very seldom the result of vivid imitation; it is, as these examples testify, Joyce’s play with the workings of the device (and frequently its failure to imitate the nonlinguistic world that provides enjoyment and some insight into the relation between language and sound.
Uniformly bounded representations of the Lorentz groups
International Nuclear Information System (INIS)
Brega, A.O.
1982-01-01
For the Lorentz group G = SO/sub e/(n + 1, 1)(ngreater than or equal to 2) the author constructs a family of uniformly bounded representations by means of analytically continuing a certain normalization of the unitary principal series. The method the author uses relies on an analysis of various operators under a Mellin transform and extends earlier work of E.N. Wilson. In a series of papers Kunze and Stein initiated the theory of uniformly bounded representations of semisimple Lie groups; the starting point is the unitary principal series T(sigma,s) obtained in a certain subgroup M of G and a purely imaginary number s. From there Kunze and Stein constructed families of representations R(sigma,s) depending analytically on a parameter s in a domain D of C containing the imaginary axis which are unitarily equilvalent to T(sigma,s) for s contained in the set of imaginary numbers and whose operator norms are uniformly bounded for each s in D. In the case of the Lorentz groups SO/sub e/(n + 1, 1)(ngreater than or equal to2) and the trivial representation 1 of M, E.N. Wilson obtained such a family R(1,s) for the domain D = [s contained in the set of C: absolute value Re(s) Vertical Bar2]. For this domain D and for any representation sigma of M the author provides a family R(sigma,s) of uniformly bounded representations analytically continuing T(sigma,s), thereby generalizing Wilson's work. The author has also investigated certain symmetry properties of the representations R(sigma,s) under the action of the Weyl group. The trivial representation is Weyl group invariant and the family R(1,s) obtained by Wilson satisfies R(1,s) = R(1,-s) reflecting this. Obtained was the analogous result R(sigma,s) = R(sigma,-s) for some well known representations sigma that are Weyl group invariant. This involves the explicit computation of certain constants arising in the Fourier transforms of intertwining operators
Energy Technology Data Exchange (ETDEWEB)
Noun, R. J.
1983-06-01
The SERI Wind Energy Program manages the areas or innovative research, wind systems analysis, and environmental compatibility for the U.S. Department of Energy. Since 1978, SERI wind program staff have conducted in-house aerodynamic and engineering analyses of novel concepts for wind energy conversion and have managed over 20 subcontracts to determine technical feasibility; the most promising of these concepts is the passive blade cyclic pitch control project. In the area of systems analysis, the SERI program has analyzed the impact of intermittent generation on the reliability of electric utility systems using standard utility planning models. SERI has also conducted methodology assessments. Environmental issues related to television interference and acoustic noise from large wind turbines have been addressed. SERI has identified the causes, effects, and potential control of acoustic noise emissions from large wind turbines.
Beyond Fractals and 1/f Noise: Multifractal Analysis of Complex Physiological Time Series
Ivanov, Plamen Ch.; Amaral, Luis A. N.; Ashkenazy, Yosef; Stanley, H. Eugene; Goldberger, Ary L.; Hausdorff, Jeffrey M.; Yoneyama, Mitsuru; Arai, Kuniharu
2001-03-01
We investigate time series with 1/f-like spectra generated by two physiologic control systems --- the human heartbeat and human gait. We show that physiological fluctuations exhibit unexpected ``hidden'' structures often described by scaling laws. In particular, our studies indicate that when analyzed on different time scales the heartbeat fluctuations exhibit cascades of branching patterns with self-similar (fractal) properties, characterized by long-range power-law anticorrelations. We find that these scaling features change during sleep and wake phases, and with pathological perturbations. Further, by means of a new wavelet-based technique, we find evidence of multifractality in the healthy human heartbeat even under resting conditions, and show that the multifractal character and nonlinear properties of the healthy heart are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure. In contrast to the heartbeat, we find that the interstride interval time series of healthy human gait, a voluntary process under neural regulation, is described by a single fractal dimension (such as classical 1/f noise) indicating monofractal behavior. Thus our approach can help distinguish physiological and physical signals with comparable frequency spectra and two-point correlations, and guide modeling of their control mechanisms.
Time series modeling for analysis and control advanced autopilot and monitoring systems
Ohtsu, Kohei; Kitagawa, Genshiro
2015-01-01
This book presents multivariate time series methods for the analysis and optimal control of feedback systems. Although ships’ autopilot systems are considered through the entire book, the methods set forth in this book can be applied to many other complicated, large, or noisy feedback control systems for which it is difficult to derive a model of the entire system based on theory in that subject area. The basic models used in this method are the multivariate autoregressive model with exogenous variables (ARX) model and the radial bases function net-type coefficients ARX model. The noise contribution analysis can then be performed through the estimated autoregressive (AR) model and various types of autopilot systems can be designed through the state–space representation of the models. The marine autopilot systems addressed in this book include optimal controllers for course-keeping motion, rolling reduction controllers with rudder motion, engine governor controllers, noise adaptive autopilots, route-tracki...
A practical exposure-equivalent metric for instrumentation noise in x-ray imaging systems
International Nuclear Information System (INIS)
Yadava, G K; Kuhls-Gilcrist, A T; Rudin, S; Patel, V K; Hoffmann, K R; Bednarek, D R
2008-01-01
The performance of high-sensitivity x-ray imagers may be limited by additive instrumentation noise rather than by quantum noise when operated at the low exposure rates used in fluoroscopic procedures. The equipment-invasive instrumentation noise measures (in terms of electrons) are generally difficult to make and are potentially not as helpful in clinical practice as would be a direct radiological representation of such noise that may be determined in the field. In this work, we define a clinically relevant representation for instrumentation noise in terms of noise-equivalent detector entrance exposure, termed the instrumentation noise-equivalent exposure (INEE), which can be determined through experimental measurements of noise-variance or signal-to-noise ratio (SNR). The INEE was measured for various detectors, thus demonstrating its usefulness in terms of providing information about the effective operating range of the various detectors. A simulation study is presented to demonstrate the robustness of this metric against post-processing, and its dependence on inherent detector blur. These studies suggest that the INEE may be a practical gauge to determine and compare the range of quantum-limited performance for clinical x-ray detectors of different design, with the implication that detector performance at exposures below the INEE will be instrumentation-noise limited rather than quantum-noise limited
Realistic Noise Assessment and Strain Analysis of Iranian Permanent GPS Stations
Razeghi, S. M.; Amiri Simkooei, A. A.; Sharifi, M. A.
2012-04-01
To assess noise characteristics of Iranian Permanent GPS Stations (IPGS), northwestern part of this network namely Azerbaijan Continuous GPS Station (ACGS), was selected. For a realistic noise assessment it is required to model all deterministic signals of the GPS time series by means of least squares harmonic estimation (LS-HE) and derive all periodic behavior of the series. After taking all deterministic signals into account, the least squares variance component estimation (LS-VCE) is used to obtain a realistic noise model (white noise plus flicker noise) of the ACGS. For this purpose, one needs simultaneous GPS time series for which a multivariate noise assessment is applied. Having determined realistic noise model, a realistic strain analysis of the network is obtained for which one relies on the finite element methods. Finite element is now considered to be a new functional model and the new stochastic model is given based on the multivariate noise assessment using LS-VCE. The deformation rates of the components along with their full covariance matries are input to the strain analysis. Further, the results are also provided using a pure white noise model. The normalized strains for these two models show that the strain parameters derived from a realistic noise model are less significant than those derived from the white model. This could be either due to the short time span of the time series used or due to the intrinsic behavior of the strain parameters in the ACGS. Longer time series are required to further elaborate this issue.
Noise Pollution, Teachers' Edition.
O'Donnell, Patrick A.; Lavaroni, Charles W.
One of three in a series about pollution, this teacher's guide for a unit on noise pollution is designed for use in junior high school grades. It offers suggestions for extending the information and activities contained in the textual material for students. Chapter 1 discusses the problem of noise pollution and involves students in processes of…
Brownian motion with multiplicative noises revisited
International Nuclear Information System (INIS)
Kuroiwa, T; Miyazaki, K
2014-01-01
The Langevin equation with multiplicative noise and a state-dependent transport coefficient should always complemented with the proper interpretation rule of the noise, such as the Itô and Stratonovich conventions. Although the mathematical relationship between the different rules and how to translate from one rule to another are well established, the subject of which is a more physically natural rule still remains controversial. In this communication, we derive the overdamped Langevin equation with multiplicative noise for Brownian particles, by systematically eliminating the fast degrees of freedom of the underdamped Langevin equation. The Langevin equations obtained here vary depending on the choice of the noise conventions but they are different representations for an identical phenomenon. The results apply to multi-variable, nonequilibrium, non-stationary systems, and other general settings. (fast track communication)
Effect of noise on estimation of Lyapunov exponents from a time series
Energy Technology Data Exchange (ETDEWEB)
Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alta., T2N 1N4 (Canada)]. E-mail: http://econ.ucalgary.ca/serletis.htm; Shahmoradi, Asghar [Department of Economics, University of Calgary, Calgary, Alta., T2N 1N4 (Canada); Serletis, Demitre [Division of Neurosurgery, University of Toronto, Toronto, ON, M5G 1L5 (Canada)
2007-04-15
We argue that dynamical noise can dramatically change the dynamics of low-dimensional chaotic systems. Moreover, we show that chaos tests are highly sensitive to dynamical noise and this becomes worse when the intensity of the noise increases.
On signal design by the R sub 0 criterion for non-white Gaussian noise channels
Bordelon, D. L.
1976-01-01
The use of the R sub 0 criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate R sub 0 for vector channels with additive nonwhite Gaussian noise and unquantized demodulation is derived. When the signal unput to the channel is a continuous random vector, maximization of R sub 0 with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize R sub 0 with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. A necessary condition on a constrained energy, finite signal set is found which maximizes a Taylor series approximation of R sub 0. This signal set is compared with the finite signal set which has the water-filling average energy distribution.
Magnified Neural Envelope Coding Predicts Deficits in Speech Perception in Noise.
Millman, Rebecca E; Mattys, Sven L; Gouws, André D; Prendergast, Garreth
2017-08-09
anatomically distinct cortical representations of modulated noise in normal-hearing and hearing-impaired listeners. This work provides the first link among hearing thresholds, the amplitude of cortical representations of modulated sounds, and the ability to understand speech in modulated background noise. In light of previous work, we propose that magnified cortical representations of modulated sounds disrupt the separation of speech from modulated background noise in auditory cortex. Copyright © 2017 Millman et al.
Stochastic Analysis of Gaussian Processes via Fredholm Representation
Directory of Open Access Journals (Sweden)
Tommi Sottinen
2016-01-01
Full Text Available We show that every separable Gaussian process with integrable variance function admits a Fredholm representation with respect to a Brownian motion. We extend the Fredholm representation to a transfer principle and develop stochastic analysis by using it. We show the convenience of the Fredholm representation by giving applications to equivalence in law, bridges, series expansions, stochastic differential equations, and maximum likelihood estimations.
Representations of some quantum tori Lie subalgebras
International Nuclear Information System (INIS)
Jiang, Jingjing; Wang, Song
2013-01-01
In this paper, we define the q-analog Virasoro-like Lie subalgebras in x ∞ =a ∞ (b ∞ , c ∞ , d ∞ ). The embedding formulas into x ∞ are introduced. Irreducible highest weight representations of A(tilde sign) q , B(tilde sign) q , and C(tilde sign) q -series of the q-analog Virasoro-like Lie algebras in terms of vertex operators are constructed. We also construct the polynomial representations of the A(tilde sign) q , B(tilde sign) q , C(tilde sign) q , and D(tilde sign) q -series of the q-analog Virasoro-like Lie algebras.
The Powers of Noise-Fitting: Reply to Barth and Paladino
Opfer, John E.; Siegler, Robert S.; Young, Christopher J.
2011-01-01
Barth and Paladino (2011) argue that changes in numerical representations are better modeled by a power function whose exponent gradually rises to 1 than as a shift from a logarithmic to a linear representation of numerical magnitude. However, the fit of the power function to number line estimation data may simply stem from fitting noise generated…
Directory of Open Access Journals (Sweden)
Martin Gugat
2012-05-01
Full Text Available Compressible squeeze film damping is a phenomenon of great importance for micromachines. For example, for the optimal design of an electrostatically actuated micro-cantilever mass sensor that operates in air, it is essential to have a model for the system behavior that can be evaluated efficiently. An analytical model that is based upon a solution of the linearized Reynolds equation has been given by R.B. Darling. In this paper we explain how some infinite sums that appear in Darling’s model can be evaluated analytically. As an example of applications of these closed form representations, we compute an approximation for the critical frequency where the spring component of the reaction force on the microplate, due to the motion through the air, is equal to a certain given multiple of the damping component. We also show how some double series that appear in the model can be reduced to a single infinite series that can be approximated efficiently.
International Nuclear Information System (INIS)
Thie, J.A.
1981-01-01
This book concentrates on the different types of noise present in power reactors and how the analysis of this noise can be used as a tool for reactor monitoring and diagnostics. Noise analysis is a growing field that offers advantages such as simplicity, low cost, and natural multivariable interactions. A major advantage, continuous and undisturbed monitoring, supplies a means of obtaining early warnings of possible reactor malfunctions thus preventing further complications by alerting operators to a problem - and aiding in the diagnosis of that problem - before it demands major repairs. Following an introductory chapter, the theoretical basis for the various methods of noise analysis is explained, and full chapters are devoted to the fundamentals of statistics for time-domain analysis and Fourier series and related topics for frequency-domain analysis. General experimental techniques and associated theoretical considerations are reviewed, leading to discussion of practical applications in the latter half of the book. Besides chapters giving examples of neutron noise and acoustical noise, chapters are also devoted to extensive examples from pressurized water reactor and boiling water reactor power plants
A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering
Directory of Open Access Journals (Sweden)
Yubao Sun
2015-01-01
Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.
Gender Representations: Reaching Beyond the Limits We Make.
Enciso, Patricia; Rogers, Theresa; Marshall, Elizabeth; Tyson, Cynthia; Jenkins, Christine; Brown, Jacqueline; Core, Elizabeth; Cordova, Carmen; Youngsteadt-Parish, Denise; Robinson, Dwan
1999-01-01
Describes 15 children's books (published in 1998 or 1999) that offer diverse representations of gender. Discusses them in tandem with landmark children's books in categories of picture books (from traditional tales to contemporary and historical representations), series books (fitting into and breaking the mold), and chapter books (navigating…
Wilson, Scott; Bowyer, Andrea; Harrap, Stephen B
2015-01-01
The clinical characterization of cardiovascular dynamics during hemodialysis (HD) has important pathophysiological implications in terms of diagnostic, cardiovascular risk assessment, and treatment efficacy perspectives. Currently the diagnosis of significant intradialytic systolic blood pressure (SBP) changes among HD patients is imprecise and opportunistic, reliant upon the presence of hypotensive symptoms in conjunction with coincident but isolated noninvasive brachial cuff blood pressure (NIBP) readings. Considering hemodynamic variables as a time series makes a continuous recording approach more desirable than intermittent measures; however, in the clinical environment, the data signal is susceptible to corruption due to both impulsive and Gaussian-type noise. Signal preprocessing is an attractive solution to this problem. Prospectively collected continuous noninvasive SBP data over the short-break intradialytic period in ten patients was preprocessed using a novel median hybrid filter (MHF) algorithm and compared with 50 time-coincident pairs of intradialytic NIBP measures from routine HD practice. The median hybrid preprocessing technique for continuously acquired cardiovascular data yielded a dynamic regression without significant noise and artifact, suitable for high-level profiling of time-dependent SBP behavior. Signal accuracy is highly comparable with standard NIBP measurement, with the added clinical benefit of dynamic real-time hemodynamic information.
The quantum Rabi model and Lie algebra representations of sl2
International Nuclear Information System (INIS)
Wakayama, Masato; Yamasaki, Taishi
2014-01-01
The aim of the present paper is to understand the spectral problem of the quantum Rabi model in terms of Lie algebra representations of sl 2 (R). We define a second order element of the universal enveloping algebra U(sl 2 ) of sl 2 (R), which, through the image of a principal series representation of sl 2 (R), provides a picture equivalent to the quantum Rabi model drawn by confluent Heun differential equations. By this description, in particular, we give a representation theoretic interpretation of the degenerate part of the spectrum (i.e., Judd's eigenstates) of the Rabi Hamiltonian due to Kuś in 1985, which is a part of the exceptional spectrum parameterized by integers. We also discuss the non-degenerate part of the exceptional spectrum of the model, in addition to the Judd eigenstates, from a viewpoint of infinite dimensional irreducible submodules (or subquotients) of the non-unitary principal series such as holomorphic discrete series representations of sl 2 (R). (paper)
Updating working memory in aircraft noise and speech noise causes different fMRI activations.
Saetrevik, Bjørn; Sörqvist, Patrik
2015-02-01
The present study used fMRI/BOLD neuroimaging to investigate how visual-verbal working memory is updated when exposed to three different background-noise conditions: speech noise, aircraft noise and silence. The number-updating task that was used can distinguish between "substitution processes," which involve adding new items to the working memory representation and suppressing old items, and "exclusion processes," which involve rejecting new items and maintaining an intact memory set. The current findings supported the findings of a previous study by showing that substitution activated the dorsolateral prefrontal cortex, the posterior medial frontal cortex and the parietal lobes, whereas exclusion activated the anterior medial frontal cortex. Moreover, the prefrontal cortex was activated more by substitution processes when exposed to background speech than when exposed to aircraft noise. These results indicate that (a) the prefrontal cortex plays a special role when task-irrelevant materials should be denied access to working memory and (b) that, when compensating for different types of noise, either different cognitive mechanisms are involved or those cognitive mechanisms that are involved are involved to different degrees. © 2014 The Authors. Scandinavian Journal of Psychology published by Scandinavian Psychological Associations and John Wiley & Sons Ltd.
Visualizing the Geometric Series.
Bennett, Albert B., Jr.
1989-01-01
Mathematical proofs often leave students unconvinced or without understanding of what has been proved, because they provide no visual-geometric representation. Presented are geometric models for the finite geometric series when r is a whole number, and the infinite geometric series when r is the reciprocal of a whole number. (MNS)
Davis Canyon noise analysis: Revision 2
International Nuclear Information System (INIS)
1985-11-01
A study was performed as part of the Civilian Radioactive Waste Management Program to quantify the level and effect of noise from the various major phases of development of the proposed potentially acceptable nuclear waste repository site at Davis Canyon, Utah. This report contains the results of a predictive noise level study for the site characterization, repository construction, and repository operational phases. Included herein are graphic representations of energy averaged sound levels, and of audibility levels representing impact zones expected during each phase. Sound levels from onsite and offsite activity including traffic on highways and railroad routes are presented in isopleth maps. A description of the Environmental Noise Prediction Model used for the study, the study basis and methodologies, and actual modeling data are provided. Noise and vibration levels from blasting are also predicted and evaluated. Protective noise criteria containing a margin of safety are used in relation to residences, schools, churches, noise-sensitive recreation areas, and noise-sensitive biological resources. Protective ground motion criteria for ruins and delicate rock formation in Canyonlands National Park and for human annoyance are used in the evaluation of blasting. The evaluations provide the basis for assessing the noise impacts from the related activities at the proposed repository. 45 refs., 21 figs., 15 tabs
Anharmonic potential in the oscillator representation
International Nuclear Information System (INIS)
Dineykhan, M.; Efimov, G.V.
1994-01-01
In the non relativistic and relativized Schroedinger equation the Wick ordering method called the oscillator representation is proposed to calculate the energy spectrum for a wide class of potentials allowing the existence of a bound state. The oscillator representation method gives a unique regular way to describe and calculate the energy levels of ground as well as orbital and radial excitation states for a wide class of potentials. The results of the zeroth approximation oscillator representation are in good agreement with the exact values for the anharmonic potentials. The oscillator representation method was applied to the relativized Schroedinger equation too. The perturbation series converges fairly fast, i.e., the highest perturbation corrections over the interaction Hamiltonian are small enough. 29 refs.; 4 tabs. (author)
Properties of autoregressive model in reactor noise analysis, 1
International Nuclear Information System (INIS)
Yamada, Sumasu; Kishida, Kuniharu; Bekki, Keisuke.
1987-01-01
Under appropriate conditions, stochastic processes are described by the ARMA model, however, the AR model is popularly used in reactor noise analysis. Hence, the properties of AR model as an approximate representation of the ARMA model should be made clear. Here, convergence of AR-parameters and PSD of AR model were studied through numerical analysis on specific examples such as the neutron noise in subcritical reactors, and it was found that : (1) The convergence of AR-parameters and AR model PSD is governed by the ''zero nearest to the unit circle in the complex plane'' (μ -1 ,|μ| M . (3) The AR model of the neutron noise of subcritical reactors needs a large model order because of an ARMA-zero very close to unity corresponding to the decay constant of the 6-th group of delayed neutron precursors. (4) In applying AR model for system identification, much attention has to be paid to a priori unknown error as an approximate representation of the ARMA model in addition to the statistical errors. (author)
Directory of Open Access Journals (Sweden)
M. A. Porta-Garcia
2018-01-01
Full Text Available Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationships between multivariate neural time series is presented, applied either in a single epoch or over an intertrial assessment, relying on a proposed clustering algorithm, termed Multivariate Time Series Clustering by Phase Synchrony, which generates fuzzy clusters for each multivalued time sample and thereupon obtains hard clusters according to a circular variance threshold; such cluster modes are then depicted in Time-Frequency-Topography representations of synchrony state beyond mere global indices. EEG signals from P300 Speller sessions of four subjects were analyzed, obtaining useful insights of synchrony patterns related to the ERP and even revealing steady-state artifacts at 7.6 Hz. Further, contrast maps of Levenshtein Distance highlight synchrony differences between ERP and no-ERP epochs, mainly at delta and theta bands. The framework, which is not limited to one synchrony measure, allows observing dynamics of phase changes and interactions among channels and can be applied to analyze other cognitive states rather than ERP versus no ERP.
Richton Dome noise analysis: Revision 2
International Nuclear Information System (INIS)
1985-11-01
A study was performed as part of the Civilian Radioactive Waste Management Program to quantify the level and effect of noise from the various major phases of development of the proposed potentially acceptable nuclear waste repository site at Richton Dome, Mississippi. This report contains the results of a predictive noise level study for the site characterization, repository construction, and repository operational phases. Included herein are graphic representations of energy averaged day/night sound levels representing impact zones expected during each phase. Sound levels from onsite and offsite activity including traffic on highways and railroad routes are presented in isopleth maps. A description of the Environmental Noise Prediction Model used for the study, the study basis and methodologies, and actual modeling data are provided. Noise and vibration levels from blasting are also predicted and evaluated. Protective noise criteria containing a margin of safety are used for persons in relation to residences, schools, churches, and agricultural areas. Protective ground motion criteria for residential dwelling and for human annoyance are used in the evaluation. The evaluation provides the bases for assessing the noise impacts from the related activities at the proposed repository. 24 refs., 8 figs., 8 tabs
Wu, Kan; Shum, Ping
2010-01-01
The phase noise and intensity noise of a pulse train are theoretically analyzed in the demodulation measurement. The effect of pulse asymmetry is discussed for the first time using Fourier series. Experimentally, photodetectors with different bandwidth and incident power levels are compared to achieve minimum pulse distortion.
Distinguishing Representations as Origin and Representations as Input: Roles for Individual Cells
Directory of Open Access Journals (Sweden)
Jonathan C.W. Edwards
2016-09-01
input interaction between signals and consumer. The acceptance of this necessity provides a basis for resolving the problem that representations appear both as distributed (representation-as-origin and local (representation-as-input. The key implications are that representations in brain are massively multiple both in series and in parallel, and that individual cells play specific semantic roles. These roles are discussed in relation to traditional concepts of ‘gnostic’ cell types.
Diatomic molecule vibrational potentials: Accuracy of representations
International Nuclear Information System (INIS)
Engelke, R.
1978-01-01
A method is presented for increasing the radius of convergence of certain representations of diatomic molecule vibrational potentials. The method relies on using knowledge of the analytic structure of such potentials to the maximum when attempting to approximate them. The known singular point (due to the centrifugal and/or Coulomb potentials) at zero internuclear separation should be included in its exact form in an approximate representation. The efficacy of this idea is tested [using Peek's ''exact'' numerical Born-Oppenheimer potential for the (1ssigma/sub g/) 2 Σ + /sub g/ state of H + 2 as a test problem] when the representational form is the series of (1) Dunham, (2) Simons, Parr, and Finlan, (3) Thakkar, and (4) Ogilvie-Tipping, and also (5) when the form is a [2, 2] or a [3, 3] Pade approximant. Significant improvements in accuracy are obtained in some of these cases, particularly on the inner wall of the potential. A comparison of the effectiveness of the five methods is made both with and without the origin behavior being included exactly. This is useful in itself as no comprehensive accuracy comparison of the standard representations seems to have appeared in the literature. The Ogilvie-Tipping series, corrected at the origin for singular behavior, is the best representation presently available for states analogous to the (1ssigma/sub g/) 2 Σ + /sub g/ state of H + 2
International Nuclear Information System (INIS)
Thie, J.A.
1981-01-01
Noise analysis is a growing field that offers advantages such as simplicity, low cost, and natural multivariable interactions. A major advantage, continuous and undisturbed monitoring, supplies a means of obtaining early warnings of possible reactor malfunctions, thus preventing further complications by alerting opeators to a problem - and aiding in the diagnosis of that problem - before it demands major repairs. Dr. Thie hopes to further, through detailed explanations and over 70 illustrations, the acceptance of the use of noise analysis by the nuclear utility industry. Following an introductory chapter, the theoretical basis for the various methods of noise analysis is explained, and full chapters are devoted to the fundamentals of statistics for time-domain analysis and Fourier series and related topics for frequency-domain analysis. General experimental techniques and associated theoretical considerations are reviewed, leading to discussions of practical applications in the latter half of the book. Besides chapters giving examples of neutron noise and acoustical noise, chapters are also devoted to extensive examples from pressurized water reactor and boiling water reactor power plants
Series of Bessel and Kummer-type functions
Baricz, Arpad; Pogány, Tibor K
2017-01-01
This book is devoted to the study of certain integral representations for Neumann, Kapteyn, Schlömilch, Dini and Fourier series of Bessel and other special functions, such as Struve and von Lommel functions. The aim is also to find the coefficients of the Neumann and Kapteyn series, as well as closed-form expressions and summation formulas for the series of Bessel functions considered. Some integral representations are deduced using techniques from the theory of differential equations. The text is aimed at a mathematical audience, including graduate students and those in the scientific community who are interested in a new perspective on Fourier–Bessel series, and their manifold and polyvalent applications, mainly in general classical analysis, applied mathematics and mathematical physics.
Experimental testing of the noise-canceling processor.
Collins, Michael D; Baer, Ralph N; Simpson, Harry J
2011-09-01
Signal-processing techniques for localizing an acoustic source buried in noise are tested in a tank experiment. Noise is generated using a discrete source, a bubble generator, and a sprinkler. The experiment has essential elements of a realistic scenario in matched-field processing, including complex source and noise time series in a waveguide with water, sediment, and multipath propagation. The noise-canceling processor is found to outperform the Bartlett processor and provide the correct source range for signal-to-noise ratios below -10 dB. The multivalued Bartlett processor is found to outperform the Bartlett processor but not the noise-canceling processor. © 2011 Acoustical Society of America
Energy Technology Data Exchange (ETDEWEB)
Hadasz, Leszek [Krakow Univ. (Poland). Inst. of Physics; Pawelkiewicz, Michal; Schomerus, Volker [DESY Hamburg (Germany). Theory Group
2013-05-15
We determine the Clebsch-Gordan and Racah-Wigner coefficients for continuous series of representations of the quantum deformed algebras U{sub q}(sl(2)) and U{sub q}(osp(1 vertical stroke 2)). While our results for the former algebra reproduce formulas by Ponsot and Teschner, the expressions for the orthosymplectic algebra are new. Up to some normalization factors, the associated Racah-Wigner coefficients are shown to agree with the fusing matrix in the Neveu-Schwarz sector of N=1 supersymmetric Liouville field theory.
The equivalent internal orientation and position noise for contour integration.
Baldwin, Alex S; Fu, Minnie; Farivar, Reza; Hess, Robert F
2017-10-12
Contour integration is the joining-up of local responses to parts of a contour into a continuous percept. In typical studies observers detect contours formed of discrete wavelets, presented against a background of random wavelets. This measures performance for detecting contours in the limiting external noise that background provides. Our novel task measures contour integration without requiring any background noise. This allowed us to perform noise-masking experiments using orientation and position noise. From these we measure the equivalent internal noise for contour integration. We found an orientation noise of 6° and position noise of 3 arcmin. Orientation noise was 2.6x higher in contour integration compared to an orientation discrimination control task. Comparing against a position discrimination task found position noise in contours to be 2.4x lower. This suggests contour integration involves intermediate processing that enhances the quality of element position representation at the expense of element orientation. Efficiency relative to the ideal observer was lower for the contour tasks (36% in orientation noise, 21% in position noise) compared to the controls (54% and 57%).
Geometry of the Borel - de Siebenthal discrete series
DEFF Research Database (Denmark)
Ørsted, Bent; Wolf, Joseph A
Let G0 be a connected, simply connected real simple Lie group. Suppose that G0 has a compact Cartan subgroup T0, so it has discrete series representations. Relative to T0 there is a distinguished positive root system + for which there is a unique noncompact simple root , the “Borel – de Siebenthal...... system”. There is a lot of fascinating geometry associated to the corresponding “Borel – de Siebenthal discrete series” representations of G0. In this paper we explore some of those geometric aspects and we work out the K0–spectra of the Borel – de Siebenthal discrete series representations. This has...
A network of spiking neurons for computing sparse representations in an energy-efficient way.
Hu, Tao; Genkin, Alexander; Chklovskii, Dmitri B
2012-11-01
Computing sparse redundant representations is an important problem in both applied mathematics and neuroscience. In many applications, this problem must be solved in an energy-efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating by low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, the operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We show that the numerical performance of HDA is on par with existing algorithms. In the asymptotic regime, the representation error of HDA decays with time, t, as 1/t. HDA is stable against time-varying noise; specifically, the representation error decays as 1/√t for gaussian white noise.
Updating working memory in aircraft noise and speech causes different fMRI activations
Sætrevik, Bjørn; Sörqvist, Patrik
2014-01-01
The present study used fMRI/BOLD neuroimaging to investigate how visual-verbal working memory is updated when exposed to three different background-noise conditions: speech noise, aircraft noise and silence. The number-updating task that was used can distinguish between ?substitution processes,? which involve adding new items to the working memory representation and suppressing old items, and ?exclusion processes,? which involve rejecting new items and maintaining an intact memory set. The cu...
Quantum control with noisy fields: computational complexity versus sensitivity to noise
International Nuclear Information System (INIS)
Kallush, S; Khasin, M; Kosloff, R
2014-01-01
A closed quantum system is defined as completely controllable if an arbitrary unitary transformation can be executed using the available controls. In practice, control fields are a source of unavoidable noise, which has to be suppressed to retain controllability. Can one design control fields such that the effect of noise is negligible on the time-scale of the transformation? This question is intimately related to the fundamental problem of a connection between the computational complexity of the control problem and the sensitivity of the controlled system to noise. The present study considers a paradigm of control, where the Lie-algebraic structure of the control Hamiltonian is fixed, while the size of the system increases with the dimension of the Hilbert space representation of the algebra. We find two types of control tasks, easy and hard. Easy tasks are characterized by a small variance of the evolving state with respect to the operators of the control operators. They are relatively immune to noise and the control field is easy to find. Hard tasks have a large variance, are sensitive to noise and the control field is hard to find. The influence of noise increases with the size of the system, which is measured by the scaling factor N of the largest weight of the representation. For fixed time and control field the ability to control degrades as O(N) for easy tasks and as O(N 2 ) for hard tasks. As a consequence, even in the most favorable estimate, for large quantum systems, generic noise in the controls dominates for a typical class of target transformations, i.e. complete controllability is destroyed by noise. (paper)
Educating "The Simpsons": Teaching Queer Representations in Contemporary Visual Media
Padva, Gilad
2008-01-01
This article analyzes queer representation in contemporary visual media and examines how the episode "Homer's Phobia" from Matt Groening's animation series "The Simpsons" can be used to deconstruct hetero- and homo-sexual codes of behavior, socialization, articulation, representation and visibility. The analysis is contextualized in the…
Calibration of an audio frequency noise generator
DEFF Research Database (Denmark)
Diamond, Joseph M.
1966-01-01
a noise bandwidth Bn = π/2 × (3dB bandwidth). To apply this method to low audio frequencies, the noise bandwidth of the low Q parallel resonant circuit has been found, including the effects of both series and parallel damping. The method has been used to calibrate a General Radio 1390-B noise generator...... it is used for measurement purposes. The spectral density of a noise source may be found by measuring its rms output over a known noise bandwidth. Such a bandwidth may be provided by a passive filter using accurately known elements. For example, the parallel resonant circuit with purely parallel damping has...
On the prediction of impact noise, V: The noise from drop hammers
Richards, E. J.; Carr, I.; Westcott, M.
1983-06-01
In earlier papers in this series, the concepts of "acceleration" and "ringing" noise have been studied in relation to impact machines, and values of radiation efficiency have been obtained for the various types of structural components. In the work reported in this paper the predicted and measured noise radiation from a drop hammer, both in full-scale and in {1}/{3}- scale model form, were examined. It is found that overall noise levels ( Leq per event) can be predicted from vibration measurements to within ± 1·5 dB, and to within ±2·5 dB in one-third octave bands. In turn this has permitted noise reduction techniques to be examined by studies of local component vibration levels rather than overall noise, a method which provides considerable enlightenment at the design stage. It is shown that on one particular drop hammer, the noise energy is shared surprisingly uniformly over four or five sources, and that when these have been reduced, the overall noise reduction is severely limited by the "acceleration" noise from the "tup" or "hammer" itself. As this is difficult to eliminate without a basic change in forging technology, it follows that "tup" enclosure or modification of the sharpness of the final "hard" impact are the only means available for any serious noise reduction. Also indicated is the reliability of using model techniques, suitably scaled in frequency and impulse magnitude, in developing machinery with impact characteristics.
Chicago transit authority train noise exposure.
Phan, Linh T; Jones, Rachael M
2017-06-01
To characterize noise exposure of riders on Chicago Transit Authority (CTA) trains, we measured noise levels twice on each segment of 7 of the 8 CTA train lines, which are named after colors, yielding 48 time-series measurements. We found the Blue Line has the highest noise levels compared to other train lines, with mean 76.9 dBA; and that the maximum noise level, 88.9 dBA occurred in the tunnel between the Chicago and Grand stations. Train segments involving travel through a tunnel had significantly higher noise levels than segments with travel on elevated and ground level tracks. While 8-hr doses inside the passenger cars were not estimated to exceed occupational exposure limits, train operators ride in a separate cab with operational windows and may therefore have higher noise exposures than riders. Despite the low risk of hearing loss for riders on CTA trains, in part because transit noise accounts for a small part of total daily noise exposure, 1-min average noise levels exceeded 85 dBA at times. This confirms anecdotal observations of discomfort due to noise levels, and indicates a need for noise management, particularly in tunnels.
Theoretical and experimental notes on noise phenomena of KUR
International Nuclear Information System (INIS)
Kishida, Kuniharu
1980-01-01
The classification of global or local noise is important in reactor noise analysis. The term of ''global'' or ''local'' corresponds to that of ''system size'' or ''cell size'' in statistical physics. On the other hand, point model or phase space description is used in time series analysis. If a time series model describing spatial behavior is established, it will serve to reactor diagnosis. The noise phenomena of KUR are discussed from these points of view. In other words, from experimental results, the point reactor picture is reasonable to neutronic aspect but quantitative problem remains in coolant temperature fluctuations. By taking into account a diffusion type model, the spatial dependence is discussed for the problem remaining in coolant temperature fluctuations. It is pointed out that the time-space picture is a crucial idea of reactor noise phenomena. (author)
Classification of time-series images using deep convolutional neural networks
Hatami, Nima; Gavet, Yann; Debayle, Johan
2018-04-01
Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.
Bourbakis, Nikolaos G.
2001-04-01
A fusion technique is presented for 3D representation. The fusion involves laser range data and segmented image data, using human expertise related to the environment. In particular, the range data may contain noise due to reflections on sloped surfaces or long open corridors; the proposed approach removes the noise by using human expertise from 3D environments. This method could be utilized either by an autonomous robot in an unknown environment, or by an inspection machine in a complex manufacturing environment, or by a visual navigation device used by blind people. Additional applications for this technique are to correct measurement deficiencies in a laser scan and to provide a true color and 3D perceived-shape representation for a given object in a modeling environment.
Slow cortical evoked potentials after noise exposure
Energy Technology Data Exchange (ETDEWEB)
von Wedel, H; Opitz, H J
1979-07-01
Human cortical evoked potentials under conditions of stimuation are registrated in the post-stimulatory phase of a five minutes lasting equally masking white noise (90 dB HL). Changes of the evoked potentials during adaptation, possible analogy with high tone losses after noise representation and the origin of tinnitus are examined. Stimulation was started 3 sec after the off-effect of the noise. For five minutes periodically tone bursts were represented. Each train of stimulation consists of tone bursts of three frequencies: 2 kcs, 4 kcs, 8 kcs. The 0.5 sec lasting tones were separated by pauses of 2 sec. During the experiment stimulation and analysis were controlled by a computer. Changes in latency and amplitudes of the cortical evoked potentials were registered. Changes of the adaptation patterns as a function of the poststimulatory time are discussed.
Applications of the representation of the Heisenberg-Euler Lagrangian by means of special functions
International Nuclear Information System (INIS)
Valluri, S.R.; Lamm, D.R.; Mielniczuk, W.J.
1993-01-01
A convenient series representation for the real part of the Heisenberg-Euler Lagrangian density of quantum electrodynamics for arbitrary nonvanishing electric fields, E, and magnetic fields, B, has been previously provided by Mielniczuk. Using this representation, numerical information for the Lagrangian is presented for the range 0 cr ≤ 5 and 0 cr ≤ 10 (subscript cr stands for critical) with the electric and magnetic fields parallel and E cr ∼ 1.7 X 10 16 V cm -1 and B cr ∼ 4.4 X 10 13 G. It was found that for a fixed electric field, the Lagrangian is monotonically increasing with increasing magnetic field strength. However, for a fixed magnetic field, the Lagrangian exhibits a positively valued maximum before turning monotonically decreasing with increasing electric field strength. Further, the series representation is extended to the case of vanishing electric or magnetic field. Numerical results for these special cases are in very close agreement with previous results, which indicated a maximum value for the Lagrangian density for B = 0 at E/E cr ∼ 3. Also, the techniques developed for deriving the real part of the Heisenberg-Euler Lagrangian are applied to the imaginary part to deduce a similar, convenient series representation that agrees with the previous results derived by others for the special case of a vanishing magnetic field. Possible applications of this Lagrangian to quantum chromodynamics are discussed. This series representation will be of use in calculations of a quantum-electrodynamical field energy density in the absence of real charges, and for calculations of polarization and magnetization of the vacuum. More accurate calculations of the cross-section scattering of light by light in the presence of a constant, homogeneous magnetic and (or) electric field are possible with the aid of this series representation. (author)
Image de-noising based on mathematical morphology and multi-objective particle swarm optimization
Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng
2017-07-01
To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.
Exploring Noise: Sound Pollution.
Rillo, Thomas J.
1979-01-01
Part one of a three-part series about noise pollution and its effects on humans. This section presents the background information for teachers who are preparing a unit on sound. The next issues will offer learning activities for measuring the effects of sound and some references. (SA)
Ocean Ambient Noise Measurement and Theory
Carey, William M
2011-01-01
This book develops the theory of ocean ambient noise mechanisms and measurements, and also describes general noise characteristics and computational methods. It concisely summarizes the vast ambient noise literature using theory combined with key representative results. The air-sea boundary interaction zone is described in terms of non-dimensional variables requisite for future experiments. Noise field coherency, rare directional measurements, and unique basin scale computations and methods are presented. The use of satellite measurements in these basin scale models is demonstrated. Finally, this book provides a series of appendices giving in-depth mathematical treatments. With its complete and careful discussions of both theory and experimental results, this book will be of the greatest interest to graduate students and active researchers working in fields related to ambient noise in the ocean.
Complexity in White Noise Analysis
Hida, Takeyuki
We restrict our attention to random complex systems and discuss degree their degree of complexity based on a white noise. The white noise is realized as the time derivative of a Brownian motion B(t), and denoted by Ḃ(t). The collection {Ḃ(t)}, is a system of idealized elementary variables and at the same time the system is a stochastic representation of the time t, in other words it is time-oriented. Having expressed the given evolutional random phenomena in question in terms of the Ḃ(t), we introduce the notion of spectral multiplicity, which describes how much the phenomena are complex. The multiplicity is the number of cyclic subspaces that are spanned by the given random phenomena. Each cyclic subspace has further structure. Typical property is multiple Markov property, although this property appears only particular cases. As a related property, in fact as a characteristic of a complex system, one can speak of the time reversibility and irreversibility of certain random phenomena in terms of the white noise. We expect an irreversible random complex system may be decomposed into reversible systems.
Entropy-Based Method of Choosing the Decomposition Level in Wavelet Threshold De-noising
Directory of Open Access Journals (Sweden)
Yan-Fang Sang
2010-06-01
Full Text Available In this paper, the energy distributions of various noises following normal, log-normal and Pearson-III distributions are first described quantitatively using the wavelet energy entropy (WEE, and the results are compared and discussed. Then, on the basis of these analytic results, a method for use in choosing the decomposition level (DL in wavelet threshold de-noising (WTD is put forward. Finally, the performance of the proposed method is verified by analysis of both synthetic and observed series. Analytic results indicate that the proposed method is easy to operate and suitable for various signals. Moreover, contrary to traditional white noise testing which depends on “autocorrelations”, the proposed method uses energy distributions to distinguish real signals and noise in noisy series, therefore the chosen DL is reliable, and the WTD results of time series can be improved.
Chesca, Boris; John, Daniel; Mellor, Christopher J.
2015-10-01
A very promising direction to improve the sensitivity of magnetometers based on superconducting quantum interference devices (SQUIDs) is to build a series-array of N non-interacting SQUIDs operating flux-coherently, because in this case their voltage modulation depth, ΔV, linearly scales with N whereas the white flux noise SΦ1/2 decreases as 1/N1/2. Here, we report the realization of both these improvements in an advanced layout of very large SQUID arrays made of YBa2Cu3O7. Specially designed with large area narrow flux focusers for increased field sensitivity and improved flux-coherency, our arrays have extremely low values for SΦ1/2 between (0.25 and 0.44) μΦ0/Hz1/2 for temperatures in the range (77-83) K. In this respect, they outperform niobium/aluminium trilayer technology-based single-SQUIDs operating at 4.2 K. Moreover, with values for ΔV and transimpedance in the range of (10-17) mV and (0.3-2.5) kΩ, respectively, a direct connection to a low-noise room temperature amplifier is allowed, while matching for such readout is simplified and the available bandwidth is greatly increased. These landmark performances suggest such series SQUID arrays are ideal candidates to replace single-SQUIDs operating at 4.2 K in many applications.
Directory of Open Access Journals (Sweden)
Wilson S
2015-01-01
Full Text Available Scott Wilson,1,2 Andrea Bowyer,3 Stephen B Harrap4 1Department of Renal Medicine, The Alfred Hospital, 2Baker IDI, Melbourne, 3Department of Anaesthesia, Royal Melbourne Hospital, 4University of Melbourne, Parkville, VIC, Australia Abstract: The clinical characterization of cardiovascular dynamics during hemodialysis (HD has important pathophysiological implications in terms of diagnostic, cardiovascular risk assessment, and treatment efficacy perspectives. Currently the diagnosis of significant intradialytic systolic blood pressure (SBP changes among HD patients is imprecise and opportunistic, reliant upon the presence of hypotensive symptoms in conjunction with coincident but isolated noninvasive brachial cuff blood pressure (NIBP readings. Considering hemodynamic variables as a time series makes a continuous recording approach more desirable than intermittent measures; however, in the clinical environment, the data signal is susceptible to corruption due to both impulsive and Gaussian-type noise. Signal preprocessing is an attractive solution to this problem. Prospectively collected continuous noninvasive SBP data over the short-break intradialytic period in ten patients was preprocessed using a novel median hybrid filter (MHF algorithm and compared with 50 time-coincident pairs of intradialytic NIBP measures from routine HD practice. The median hybrid preprocessing technique for continuously acquired cardiovascular data yielded a dynamic regression without significant noise and artifact, suitable for high-level profiling of time-dependent SBP behavior. Signal accuracy is highly comparable with standard NIBP measurement, with the added clinical benefit of dynamic real-time hemodynamic information. Keywords: continuous monitoring, blood pressure
Wavelets for Sparse Representation of Music
DEFF Research Database (Denmark)
Endelt, Line Ørtoft; Harbo, Anders La-Cour
2004-01-01
We are interested in obtaining a sparse representation of music signals by means of a discrete wavelet transform (DWT). That means we want the energy in the representation to be concentrated in few DWT coefficients. It is well-known that the decay of the DWT coefficients is strongly related...... to the number of vanishing moments of the mother wavelet, and to the smoothness of the signal. In this paper we present the result of applying two classical families of wavelets to a series of musical signals. The purpose is to determine a general relation between the number of vanishing moments of the wavelet...
Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation
Directory of Open Access Journals (Sweden)
Wei Jin
2016-12-01
Full Text Available Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC, atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.
Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation
Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi
2016-01-01
Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261
Directory of Open Access Journals (Sweden)
Qaisar Javaid
2018-01-01
Full Text Available De-noising of the medical images is very difficult task. To improve the overall visual representation we need to apply a contrast enhancement techniques, this representation provide the physicians and clinicians a good and recovered diagnosis results. Various de-noising and contrast enhancements methods are develops. However, some of the methods are not good in providing the better results with accuracy and efficiency. In our paper we de-noise and enhance the medical images without any loss of information. We uses the curvelet transform in combination with ridglet transform along with CS (Cuckoo Search algorithm. The curvlet transform adapt and represents the sparse pixel informations with all edges. The edges play very important role in understanding of the images. Curvlet transform computes the edges very efficiently where the wavelets are failed. We used the CS to optimize the de-noising coefficients without loss of structural and morphological information. Our designed method would be accurate and efficient in de-noising the medical images. Our method attempts to remove the multiplicative and additive noises. Our proposed method is proved to be an efficient and reliable in removing all kind of noises from the medical images. Result indicates that our proposed approach is better than other approaches in removing impulse, Gaussian, and speckle noises.
Correlation in stimulated respiratory neural noise
Hoop, Bernard; Burton, Melvin D.; Kazemi, Homayoun; Liebovitch, Larry S.
1995-09-01
Noise in spontaneous respiratory neural activity of the neonatal rat isolated brainstem-spinal cord preparation stimulated with acetylcholine (ACh) exhibits positive correlation. Neural activity from the C4 (phrenic) ventral spinal rootlet, integrated and corrected for slowly changing trend, is interpreted as a fractal record in time by rescaled range, relative dispersional, and power spectral analyses. The Hurst exponent H measured from time series of 64 consecutive signal levels recorded at 2 s intervals during perfusion of the preparation with artificial cerebrospinal fluid containing ACh at concentrations 62.5 to 1000 μM increases to a maximum of 0.875±0.087 (SD) at 250 μM ACh and decreases with higher ACh concentration. Corrections for bias in measurement of H were made using two different kinds of simulated fractional Gaussian noise. Within limits of experimental procedure and short data series, we conclude that in the presence of added ACh of concentration 250 to 500 μM, noise which occurs in spontaneous respiratory-related neural activity in the isolated brainstem-spinal cord preparation observed at uniform time intervals exhibits positive correlation.
Annoyance of Low Frequency Noise (LFN) in the laboratory assessed by LFN-sufferers and non-sufferers
DEFF Research Database (Denmark)
Poulsen, Torben
2003-01-01
In a series of listening tests, test subjects listened to eight different environmental low frequency noises to evaluate their loudness and annoyance. The noises were continuous noise with and without tones, intermittent noise, music, traffic noise and low frequency noises with an impulsive...
Environmental noise forecasting based on support vector machine
Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan
2018-01-01
As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.
Time response measurements of pressure sensors using pink noise technique
International Nuclear Information System (INIS)
Pereira, Iraci Martinez; Santos, Roberto Carlos dos
2009-01-01
This work presents an experimental setup for Pink Noise method application on pressure transmitters' response times. The Pink Noise method consists on injecting artificial pressure noise into the pressure transmitter. The artificial pressure noise is generated using a current-to-pressure (I-to-P) converter, which is driven by a random noise signal generator. The output pressure transmitter noise is then analyzed using conventional Noise Analysis Technique. Noise signals may be interpreted using spectral techniques or empirical time series models. The frequency domain method consists of evaluating the Power Spectral Density (PSD) function. The information needed for time constant estimation can be obtained by fitting an all-pole transfer function to this power spectral density. (author)
Euler Polynomials, Fourier Series and Zeta Numbers
DEFF Research Database (Denmark)
Scheufens, Ernst E
2012-01-01
Fourier series for Euler polynomials is used to obtain information about values of the Riemann zeta function for integer arguments greater than one. If the argument is even we recover the well-known exact values, if the argument is odd we find integral representations and rapidly convergent series....
RB reactor noise analysis; Analiza sumova reaktora RB
Energy Technology Data Exchange (ETDEWEB)
Petrovic, M; Velickovic, Lj; Markovic, V; Jovanovic, S [Institut za nuklearne nauke Boris Kidric, Vinca, Beograd (Yugoslavia)
1964-07-01
Statistical fluctuations of reactivity represent reactor noise. Analysis of reactor noise enables determining a series of reactor kinetic parameters. Fluctuations of power was measured by ionization chamber placed next to the tank of the RB reactor. The signal was digitized by an analog-digital converter. After calculation of the mean power, 3000 data obtained by sampling were analysed.
Reconstructing latent dynamical noise for better forecasting observables
Hirata, Yoshito
2018-03-01
I propose a method for reconstructing multi-dimensional dynamical noise inspired by the embedding theorem of Muldoon et al. [Dyn. Stab. Syst. 13, 175 (1998)] by regarding multiple predictions as different observables. Then, applying the embedding theorem by Stark et al. [J. Nonlinear Sci. 13, 519 (2003)] for a forced system, I produce time series forecast by supplying the reconstructed past dynamical noise as auxiliary information. I demonstrate the proposed method on toy models driven by auto-regressive models or independent Gaussian noise.
Linear phase formation by noise simulator
International Nuclear Information System (INIS)
Hazi, G.; Por, G.
1998-01-01
A new simulation technique is introduced to study noise propagation in nuclear power plants. Noise processes are considered as time functions, and the dynamic behaviour of the reactor core is modelled by ordinary and partial differential equations. The equations are solved by numerical methods and the results (time series) are considered as virtual measurements. The auto power spectral density and the cross power spectral density of these time series are calculated by traditional techniques. The spectrum obtained is compared with the analytical solution to validate the new simulation approach. After validation, the simulator is expanded to investigate some physical phenomena which are unmanageable by analytical calculations. Propagating disturbances are studied, and the effect of non-flat flux shape on phase curves is demonstrated. Numerical problems also are briefly discussed. (author)
Multifractal analysis of visibility graph-based Ito-related connectivity time series.
Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano
2016-02-01
In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.
Noise in a-Si:H p-i-n detector diodes
International Nuclear Information System (INIS)
Cho, G.; Qureshi, S.; Drewery, J.S.; Jing, T.; Kaplan, S.N.; Lee, H.; Mireshghi, A.; Perez-Mendez, V.; Wildermuth, D.
1991-10-01
Noise of a-Si:H p-i-n diodes (5 ∼ 50 μm thick) under reverse bias was investigated. The current dependent 1/f type noise was found to be the main noise component at high bias. At low bias the thermal noise from a series resistance of the p-layer and of the metallic contacts is the dominant noise source which is unrelated to the reverse current through the diode. The noise associated with the p-layer resistance decreased significantly on annealing under reverse bias, reducing the total zero bias noise by a factor 2 approximately. The noise recovered to the original value on subsequent annealing without bias. In addition to the resistive noise there seems to be a shaping time independent noise component at zero biased diodes
Directory of Open Access Journals (Sweden)
David Afolabi
2017-11-01
Full Text Available The importance of an interference-less machine learning scheme in time series prediction is crucial, as an oversight can have a negative cumulative effect, especially when predicting many steps ahead of the currently available data. The on-going research on noise elimination in time series forecasting has led to a successful approach of decomposing the data sequence into component trends to identify noise-inducing information. The empirical mode decomposition method separates the time series/signal into a set of intrinsic mode functions ranging from high to low frequencies, which can be summed up to reconstruct the original data. The usual assumption that random noises are only contained in the high-frequency component has been shown not to be the case, as observed in our previous findings. The results from that experiment reveal that noise can be present in a low frequency component, and this motivates the newly-proposed algorithm. Additionally, to prevent the erosion of periodic trends and patterns within the series, we perform the learning of local and global trends separately in a hierarchical manner which succeeds in detecting and eliminating short/long term noise. The algorithm is tested on four datasets from financial market data and physical science data. The simulation results are compared with the conventional and state-of-the-art approaches for time series machine learning, such as the non-linear autoregressive neural network and the long short-term memory recurrent neural network, respectively. Statistically significant performance gains are recorded when the meta-learning algorithm for noise reduction is used in combination with these artificial neural networks. For time series data which cannot be decomposed into meaningful trends, applying the moving average method to create meta-information for guiding the learning process is still better than the traditional approach. Therefore, this new approach is applicable to the forecasting
Sanz López, Josep Maria
2017-10-09
A growing academic discussion has focused on how, in a globalized world, LGBTQ identities are shaped and influenced by different and international actors, such as the media. This article analyzes how LGBTQ people from a rural region of a Western country-Spain-feel toward their representations on TV series from English-speaking countries. Employing a qualitative approach, this research aims to depict whether the academic conceptualizations to analyze these identity conformation processes are accurate. In addition, it explores how dominating media representations are being adapted in a region that, although within the West, can serve a context of a very different nature. The results found that a major rejection of the TV series representations among participants can suggest both an inaccuracy of the conceptualizations used by some scholars to understand LGBTQ flows and a problematic LGBTQ representation in media products that goes beyond regions and spaces.
Hertrich, Ingo; Mathiak, Klaus; Lutzenberger, Werner; Ackermann, Hermann
2004-01-01
To delineate the time course and processing stages of pitch encoding at the level of the supratemporal plane, the present study recorded evoked magnetic fields in response to rippled noise (RN) stimuli. RN largely masks simple tonotopic representations and addresses pitch processing within the temporal domain (periodicity encoding). Four dichotic stimulus types (111 or 133 Hz RN at one ear, white noise to the other one) were applied in randomized order during either visual distraction or selective auditory attention. Strictly periodic signals, noise-like events, and mixtures of both signals served as control conditions. (1) Attention-dependent ear x hemisphere interactions were observed within the time domain of the M50 field, indicating early streaming of auditory information. (2) M100 responses to strictly periodic stimuli were found lateralized to the right hemisphere. Furthermore, the higher-pitched stimuli yielded enhanced activation as compared to the lower-pitch signals (pitch scaling), conceivably reflecting sensory memory operations. (3) Besides right-hemisphere pitch scaling, the relatively late M100 component in association with the RN condition (latency = 136 ms) showed significantly stronger field strengths over the left hemisphere. Control experiments revealed this lateralization effect to be related to noise rather than pitch processing. Furthermore, subtle noise variations interacted with signal periodicity. Obviously, thus, complex task demands such as RN encoding give rise to functional segregation of auditory processing across the two hemispheres (left hemisphere: noise, right hemisphere: periodicity representation). The observed noise/periodicity interactions, furthermore, might reflect pitch-synchronous spectral evaluation at the level of the left supratemporal plane, triggered by right-hemisphere representation of signal periodicity. Copyright 2004 Elsevier Ltd.
Jiang, Weiping; Ma, Jun; Li, Zhao; Zhou, Xiaohui; Zhou, Boye
2018-05-01
The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126 GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.
Klos, Anna; Pottiaux, Eric; Van Malderen, Roeland; Bock, Olivier; Bogusz, Janusz
2017-04-01
A synthetic benchmark dataset of Integrated Water Vapour (IWV) was created within the activity of "Data homogenisation" of sub-working group WG3 of COST ES1206 Action. The benchmark dataset was created basing on the analysis of IWV differences retrieved by Global Positioning System (GPS) International GNSS Service (IGS) stations using European Centre for Medium-Range Weather Forecats (ECMWF) reanalysis data (ERA-Interim). Having analysed a set of 120 series of IWV differences (ERAI-GPS) derived for IGS stations, we delivered parameters of a number of gaps and breaks for every certain station. Moreover, we estimated values of trends, significant seasonalities and character of residuals when deterministic model was removed. We tested five different noise models and found that a combination of white and autoregressive processes of first order describes the stochastic part with a good accuracy. Basing on this analysis, we performed Monte Carlo simulations of 25 years long data with two different types of noise: white as well as combination of white and autoregressive processes. We also added few strictly defined offsets, creating three variants of synthetic dataset: easy, less-complicated and fully-complicated. The 'Easy' dataset included seasonal signals (annual, semi-annual, 3 and 4 months if present for a particular station), offsets and white noise. The 'Less-complicated' dataset included above-mentioned, as well as the combination of white and first order autoregressive processes (AR(1)+WH). The 'Fully-complicated' dataset included, beyond above, a trend and gaps. In this research, we show the impact of manual homogenisation on the estimates of trend and its error. We also cross-compare the results for three above-mentioned datasets, as the synthetized noise type might have a significant influence on manual homogenisation. Therefore, it might mostly affect the values of trend and their uncertainties when inappropriately handled. In a future, the synthetic dataset
Evaluation of recent GRACE monthly solution series with an ice sheet perspective
Horwath, Martin; Groh, Andreas
2016-04-01
GRACE monthly global gravity field solutions have undergone a remarkable evolution, leading to the latest (Release 5) series by CSR, GFZ, and JPL, to new series by other processing centers, such as ITSG and AIUB, as well as to efforts to derive combined solutions, particularly by the EGSIEM (European Gravity Service for Improved Emergency Management) project. For applications, such as GRACE inferences on ice sheet mass balance, the obvious question is on what GRACE solution series to base the assessment. Here we evaluate different GRACE solution series (including the ones listed above) in a unified framework. We concentrate on solutions expanded up to degree 90 or higher, since this is most appropriate for polar applications. We empirically assess the error levels in the spectral as well as in the spatial domain based on the month-to-month scatter in the high spherical harmonic degrees. We include empirical assessment of error correlations. We then apply all series to infer Antarctic and Greenland mass change time series and compare the results in terms of apparent signal content and noise level. We find that the ITSG solutions show lowest noise level in the high degrees (above 60). A preliminary combined solution from the EGSIEM project shows lowest noise in the degrees below 60. This virtue maps into the derived ice mass time series, where the EGSIEM-based results show the lowest noise in most cases. Meanwhile, there is no indication that any of the considered series systematically dampens actual geophysical signals.
Absorption of cosmic radio noise at different frequencies at Sanae
International Nuclear Information System (INIS)
Steyn, T.F.J.
1983-12-01
Electron density profiles are simulated as a function of altitude for the D- and E-regions during disturbed ionospheric conditions using auroral absorption data from riometers recording cosmic radio noise at 20, 30 and 51 MHz at Sanae, Antarctica. An elliptical function was used to simulate, as a function of height, the electron density profiles. Using these profiles the measured absorption was calculated by utilizing the Appleton-Hartree treatment for radio waves crossing the ionosphere. The frequency dependence of the riometer absorption is represented by a power law of the frequency: A(f) = C.f -n , and values of n were determined from calculations of the absorptions from the simulated electron density profiles. This power law is a fairly accurate representation in the frequency range 20 to 51 MHz. It appears that the exponent of the power law and the height of maximum absorption are effective parameters to determine the hardness of the energy spectra of precipitating electrons. A method is discussed whereby interferences on the riometer recordings are filtered from the data. Quiet day curves are obtained by the superposition of successive riometer recordings with a period of one sidereal day. A Fourier series is fitted to the points of maximum density to represent the quiet day recordings. Absorption events on day 175 and day 178 (1982) are analized for each riometer frequency, and the hardness of the precipitating electrons is inferred from the n-values of power law presentation. It is shown that the absorption of cosmic radio noise increases by increasing the depth of ionization without increasing the ionization rate (number of electrons /m 3 ) in the upper D-region. This may mean that a hardening of a precipitation spectrum will increase the absorption of cosmic radio noise
Data mining in time series databases
Kandel, Abraham; Bunke, Horst
2004-01-01
Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.
Multiscale Poincaré plots for visualizing the structure of heartbeat time series.
Henriques, Teresa S; Mariani, Sara; Burykin, Anton; Rodrigues, Filipa; Silva, Tiago F; Goldberger, Ary L
2016-02-09
Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.
Noise as a Probe of Ising Spin Glass Transitions
Chen, Zhi; Yu, Clare
2009-03-01
Noise is ubiquitous and and is often viewed as a nuisance. However, we propose that noise can be used as a probe of the fluctuations of microscopic entities, especially in the vicinity of a phase transition. In recent work we have used simulations to show that the noise increases in the vicinity of phase transitions of ordered systems. We have recently turned our attention to noise near the phase transitions of disordered systems. In particular, we are studying the noise near Ising spin glass transitions using Monte Carlo simulations. We monitor the system as a function of temperature. At each temperature, we obtain the time series of quantities characterizing the properties of the system, i.e., the energy and magnetization. We look at different quantities, such as the noise power spectrum and the second spectrum of the noise, to analyze the fluctuations.
Variations of Background Seismic Noise Before Strong Earthquakes, Kamchatka.
Kasimova, V.; Kopylova, G.; Lyubushin, A.
2017-12-01
The network of broadband seismic stations of Geophysical Service (Russian Academy of Science) works on the territory of Kamchatka peninsula in the Far East of Russia. We used continuous records on Z-channels at 21 stations for creation of background seismic noise time series in 2011-2017. Average daily parameters of multi-fractal spectra of singularity have been calculated at each station using 1-minute records. Maps and graphs of their spatial distribution and temporal changes were constructed at time scales from days to several years. The analysis of the coherent behavior of the time series of the statistics was considered. The technique included the splitting of seismic network into groups of stations, taking into account the coastal effect, the network configuration and the main tectonic elements of Kamchatka. Then the time series of median values of noise parameters from each group of stations were made and the frequency-time diagrams of the evolution of the spectral measure of the coherent behavior of four time series were analyzed. The time intervals and frequency bands of the maximum values showing the increase of coherence in the changes of all statistics were evaluated. The strong earthquakes with magnitudes M=6.9-8.3 occurred near the Kamchatka peninsula during the observations. The synchronous variations of the background noise parameters and increase in the coherent behavior of the median values of statistical parameters was shown before two earthquakes 2013 (February 28, Mw=6.9; May 24, Mw=8.3) within 3-9 months and before earthquake of January 30, 2016, Mw=7.2 within 3-6 months. The maximum effect of increased coherence in the range of periods 4-5.5 days corresponds to the time of preparation of two strong earthquakes in 2013 and their aftershock processes. Peculiarities in changes of statistical parameters at stages of preparation of strong earthquakes indicate the attenuation in high-amplitude outliers and the loss of multi-fractal properties in
Percolation model of excess electrical noise in transition-edge sensors
International Nuclear Information System (INIS)
Lindeman, M.A.; Anderson, M.B.; Bandler, S.R.; Bilgri, N.; Chervenak, J.; Gwynne Crowder, S.; Fallows, S.; Figueroa-Feliciano, E.; Finkbeiner, F.; Iyomoto, N.; Kelley, R.; Kilbourne, C.A.; Lai, T.; Man, J.; McCammon, D.; Nelms, K.L.; Porter, F.S.; Rocks, L.E.; Saab, T.; Sadleir, J.; Vidugiris, G.
2006-01-01
We present a geometrical model to describe excess electrical noise in transition-edge sensors (TESs). In this model, a network of fluctuating resistors represents the complex dynamics inside a TES. The fluctuations can cause several resistors in series to become superconducting. Such events short out part of the TES and generate noise because much of the current percolates through low resistance paths. The model predicts that excess white noise increases with decreasing TES bias resistance (R/R N ) and that perpendicular zebra stripes reduce noise and alpha of the TES by reducing percolation
Vector coherent state representations and their inner products
International Nuclear Information System (INIS)
Rowe, D J
2012-01-01
Several advances have extended the power and versatility of coherent state theory to the extent that it has become a vital tool in the representation theory of Lie groups and their Lie algebras. Representative applications are reviewed and some new developments are introduced. The examples given are chosen to illustrate special features of the scalar and vector coherent state constructions and how they work in practical situations. Comparisons are made with Mackey's theory of induced representations. For simplicity, we focus on square integrable (discrete series) unitary representations although many of the techniques apply more generally, with minor adjustment. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Coherent states: mathematical and physical aspects’. (review)
5. Data Types and their Representation in Memory
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 12. Algorithms Data Types and their Representation in Memory. R K Shyamasundar. Series Article Volume 1 Issue 12 December 1996 pp 26-38. Fulltext. Click here to view fulltext PDF. Permanent link:
Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition
Directory of Open Access Journals (Sweden)
Qi Jia
2015-03-01
Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.
Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.
2014-11-01
We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.
International Nuclear Information System (INIS)
Chesca, Boris; John, Daniel; Mellor, Christopher J.
2015-01-01
A very promising direction to improve the sensitivity of magnetometers based on superconducting quantum interference devices (SQUIDs) is to build a series-array of N non-interacting SQUIDs operating flux-coherently, because in this case their voltage modulation depth, ΔV, linearly scales with N whereas the white flux noise S Φ 1/2 decreases as 1/N 1/2 . Here, we report the realization of both these improvements in an advanced layout of very large SQUID arrays made of YBa 2 Cu 3 O 7 . Specially designed with large area narrow flux focusers for increased field sensitivity and improved flux-coherency, our arrays have extremely low values for S Φ 1/2 between (0.25 and 0.44) μΦ 0 /Hz 1/2 for temperatures in the range (77–83) K. In this respect, they outperform niobium/aluminium trilayer technology-based single-SQUIDs operating at 4.2 K. Moreover, with values for ΔV and transimpedance in the range of (10–17) mV and (0.3–2.5) kΩ, respectively, a direct connection to a low-noise room temperature amplifier is allowed, while matching for such readout is simplified and the available bandwidth is greatly increased. These landmark performances suggest such series SQUID arrays are ideal candidates to replace single-SQUIDs operating at 4.2 K in many applications
Inferring causality from noisy time series data
DEFF Research Database (Denmark)
Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian
2016-01-01
Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... and even causality direction in synchronized time-series and in the presence of intermediate coupling. We find that the presence of noise deterministically reduces the level of cross-mapping fidelity, while the convergence rate exhibits higher levels of robustness. Finally, we propose that controlled noise...
Fuzzy fractals, chaos, and noise
Energy Technology Data Exchange (ETDEWEB)
Zardecki, A.
1997-05-01
To distinguish between chaotic and noisy processes, the authors analyze one- and two-dimensional chaotic mappings, supplemented by the additive noise terms. The predictive power of a fuzzy rule-based system allows one to distinguish ergodic and chaotic time series: in an ergodic series the likelihood of finding large numbers is small compared to the likelihood of finding them in a chaotic series. In the case of two dimensions, they consider the fractal fuzzy sets whose {alpha}-cuts are fractals, arising in the context of a quadratic mapping in the extended complex plane. In an example provided by the Julia set, the concept of Hausdorff dimension enables one to decide in favor of chaotic or noisy evolution.
Conditional time series forecasting with convolutional neural networks
A. Borovykh (Anastasia); S.M. Bohte (Sander); C.W. Oosterlee (Cornelis)
2017-01-01
textabstractForecasting financial time series using past observations has been a significant topic of interest. While temporal relationships in the data exist, they are difficult to analyze and predict accurately due to the non-linear trends and noise present in the series. We propose to learn these
Training to Improve Hearing Speech in Noise: Biological Mechanisms
Song, Judy H.; Skoe, Erika; Banai, Karen
2012-01-01
We investigated training-related improvements in listening in noise and the biological mechanisms mediating these improvements. Training-related malleability was examined using a program that incorporates cognitively based listening exercises to improve speech-in-noise perception. Before and after training, auditory brainstem responses to a speech syllable were recorded in quiet and multitalker noise from adults who ranged in their speech-in-noise perceptual ability. Controls did not undergo training but were tested at intervals equivalent to the trained subjects. Trained subjects exhibited significant improvements in speech-in-noise perception that were retained 6 months later. Subcortical responses in noise demonstrated training-related enhancements in the encoding of pitch-related cues (the fundamental frequency and the second harmonic), particularly for the time-varying portion of the syllable that is most vulnerable to perceptual disruption (the formant transition region). Subjects with the largest strength of pitch encoding at pretest showed the greatest perceptual improvement. Controls exhibited neither neurophysiological nor perceptual changes. We provide the first demonstration that short-term training can improve the neural representation of cues important for speech-in-noise perception. These results implicate and delineate biological mechanisms contributing to learning success, and they provide a conceptual advance to our understanding of the kind of training experiences that can influence sensory processing in adulthood. PMID:21799207
Hauk, O; Keil, A; Elbert, T; Müller, M M
2002-01-30
We describe a methodology to apply current source density (CSD) and minimum norm (MN) estimation as pre-processing tools for time-series analysis of single trial EEG data. The performance of these methods is compared for the case of wavelet time-frequency analysis of simulated gamma-band activity. A reasonable comparison of CSD and MN on the single trial level requires regularization such that the corresponding transformed data sets have similar signal-to-noise ratios (SNRs). For region-of-interest approaches, it should be possible to optimize the SNR for single estimates rather than for the whole distributed solution. An effective implementation of the MN method is described. Simulated data sets were created by modulating the strengths of a radial and a tangential test dipole with wavelets in the frequency range of the gamma band, superimposed with simulated spatially uncorrelated noise. The MN and CSD transformed data sets as well as the average reference (AR) representation were subjected to wavelet frequency-domain analysis, and power spectra were mapped for relevant frequency bands. For both CSD and MN, the influence of noise can be sufficiently suppressed by regularization to yield meaningful information, but only MN represents both radial and tangential dipole sources appropriately as single peaks. Therefore, when relating wavelet power spectrum topographies to their neuronal generators, MN should be preferred.
Chaos game representation of the D st index and prediction of geomagnetic storm events
International Nuclear Information System (INIS)
Yu, Z.G.; Anh, V.V.; Wanliss, J.A.; Watson, S.M.
2007-01-01
This paper proposes a two-dimensional chaos game representation (CGR) for the D st index. The CGR provides an effective method to characterize the multifractality of the D st time series. The probability measure of this representation is then modeled as a recurrent iterated function system in fractal theory, which leads to an algorithm for prediction of a storm event. We present an analysis and modeling of the D st time series over the period 1963-2003. The numerical results obtained indicate that the method is useful in predicting storm events one day ahead
An Integral Representation of Standard Automorphic L Functions for Unitary Groups
Directory of Open Access Journals (Sweden)
Yujun Qin
2007-01-01
Full Text Available Let F be a number field, G a quasi-split unitary group of rank n. We show that given an irreducible cuspidal automorphic representation π of G(A, its (partial L function LS(s,π,σ can be represented by a Rankin-Selberg-type integral involving cusp forms of π, Eisenstein series, and theta series.
Noise-induced chaos in a quadratically nonlinear oscillator
International Nuclear Information System (INIS)
Gan Chunbiao
2006-01-01
The present paper focuses on the noise-induced chaos in a quadratically nonlinear oscillator. Simple zero points of the stochastic Melnikov integral theoretically mean the necessary rising of noise-induced chaotic response in the system based on the stochastic Melnikov method. To quantify the noise-induced chaos, the boundary of the system's safe basin is firstly studied and it is shown to be incursively fractal when chaos arises. Three cases are considered in simulating the safe basin of the system, i.e., the system is excited only by the harmonic excitation, by both the harmonic and the Gaussian white noise excitations, and only by the Gaussian white noise excitation. Secondly, the leading Lyapunov exponent by Rosenstein's algorithm is shown to quantify the chaotic nature of the sample time series of the system. The results show that the boundary of the safe basin can also be fractal even if the system is excited only by the external Gaussian white noise. Most importantly, the almost-harmonic, the noise-induced chaotic and the thoroughly random responses can be found in the system
Najeebullah Khan; Amanullah Khan Miankhel
2013-01-01
Prior research has been focused on the assessment of women representation in lower house of the parliament. This study examines an overtime growth for the descriptive representation of women in both the legislative and executive bodies of Pakistan and Malaysia. Time series plot is used to assess overtime growth of women representation since independence of the countries. The results indicate substantial increase in woman representation over the years in both the countries. However representat...
Investigation of hydraulic transmission noise sources
Klop, Richard J.
Advanced hydrostatic transmissions and hydraulic hybrids show potential in new market segments such as commercial vehicles and passenger cars. Such new applications regard low noise generation as a high priority, thus, demanding new quiet hydrostatic transmission designs. In this thesis, the aim is to investigate noise sources of hydrostatic transmissions to discover strategies for designing compact and quiet solutions. A model has been developed to capture the interaction of a pump and motor working in a hydrostatic transmission and to predict overall noise sources. This model allows a designer to compare noise sources for various configurations and to design compact and inherently quiet solutions. The model describes dynamics of the system by coupling lumped parameter pump and motor models with a one-dimensional unsteady compressible transmission line model. The model has been verified with dynamic pressure measurements in the line over a wide operating range for several system structures. Simulation studies were performed illustrating sensitivities of several design variables and the potential of the model to design transmissions with minimal noise sources. A semi-anechoic chamber has been designed and constructed suitable for sound intensity measurements that can be used to derive sound power. Measurements proved the potential to reduce audible noise by predicting and reducing both noise sources. Sound power measurements were conducted on a series hybrid transmission test bench to validate the model and compare predicted noise sources with sound power.
The Weyl approach to the representation theory of reflection equation algebra
International Nuclear Information System (INIS)
Saponov, P A
2004-01-01
The present paper deals with the representation theory of reflection equation algebra, connected to a Hecke type R-matrix. Up to some reasonable additional conditions, the R-matrix is arbitrary (not necessary originating from quantum groups). We suggest a universal method for constructing finite dimensional irreducible representations in the framework of the Weyl approach well known in the representation theory of classical Lie groups and algebras. With this method a series of irreducible modules is constructed. The modules are parametrized by Young diagrams. The spectrum of central elements s k Tr q L k is calculated in the single-row and single-column representations. A rule for the decomposition of the tensor product of modules into a direct sum of irreducible components is also suggested
Teng, Fei; Jin, Jing; Li, Yong; Zhang, Chunxi
2018-05-01
The contribution of modulator drive circuit noise as a 1/f noise source to the output noise of the high-sensitivity interferometric fiber optic gyroscope (IFOG) was studied here. A noise model of closed-loop IFOG was built. By applying the simulated 1/f noise sequence into the model, a gyroscope output data series was acquired, and the corresponding power spectrum density (PSD) and the Allan variance curve were calculated to analyze the noise characteristic. The PSD curve was in the spectral shape of 1/f, which verifies that the modulator drive circuit induced a low frequency 1/f phase noise into the gyroscope. The random walk coefficient (RWC), a standard metric to characterize the noise performance of the IFOG, was calculated according to the Allan variance curve. Using an operational amplifier with an input 1/f noise of 520 nV/√Hz at 1 Hz, the RWC induced by this 1/f noise was 2 × 10-4°/√h, which accounts for 63% of the total RWC. To verify the correctness of the noise model we proposed, a high-sensitivity gyroscope prototype was built and tested. The simulated Allan variance curve gave a good rendition of the prototype actual measured curve. The error percentage between the simulated RWC and the measured value was less than 13%. According to the model, a noise reduction method is proposed and the effectiveness is verified by the experiment.
Energy Technology Data Exchange (ETDEWEB)
Chesca, Boris, E-mail: B.Chesca@lboro.ac.uk; John, Daniel [Department of Physics, Loughborough University, Loughborough LE11 3TU (United Kingdom); Mellor, Christopher J. [School of Physics and Astronomy, Nottingham University, Nottingham NG7 2RD (United Kingdom)
2015-10-19
A very promising direction to improve the sensitivity of magnetometers based on superconducting quantum interference devices (SQUIDs) is to build a series-array of N non-interacting SQUIDs operating flux-coherently, because in this case their voltage modulation depth, ΔV, linearly scales with N whereas the white flux noise S{sub Φ}{sup 1/2} decreases as 1/N{sup 1/2}. Here, we report the realization of both these improvements in an advanced layout of very large SQUID arrays made of YBa{sub 2}Cu{sub 3}O{sub 7}. Specially designed with large area narrow flux focusers for increased field sensitivity and improved flux-coherency, our arrays have extremely low values for S{sub Φ}{sup 1/2} between (0.25 and 0.44) μΦ{sub 0}/Hz{sup 1/2} for temperatures in the range (77–83) K. In this respect, they outperform niobium/aluminium trilayer technology-based single-SQUIDs operating at 4.2 K. Moreover, with values for ΔV and transimpedance in the range of (10–17) mV and (0.3–2.5) kΩ, respectively, a direct connection to a low-noise room temperature amplifier is allowed, while matching for such readout is simplified and the available bandwidth is greatly increased. These landmark performances suggest such series SQUID arrays are ideal candidates to replace single-SQUIDs operating at 4.2 K in many applications.
A comparative study of time series modeling methods for reactor noise analysis
International Nuclear Information System (INIS)
Kitamura, Masaharu; Shigeno, Kei; Sugiyama, Kazusuke
1978-01-01
Two modeling algorithms were developed to study at-power reactor noise as a multi-input, multi-output process. A class of linear, discrete time description named autoregressive-moving average model was used as a compact mathematical expression of the objective process. One of the model estimation (modeling) algorithms is based on the theory of Kalman filtering, and the other on a conjugate gradient method. By introducing some modifications in the formulation of the problem, realization of the practically usable algorithms was made feasible. Through the testing with several simulation models, reliability and effectiveness of these algorithms were confirmed. By applying these algorithms to experimental data obtained from a nuclear power plant, interesting knowledge about the at-power reactor noise was found out. (author)
Impact of cyclostationarity on fan broadband noise prediction
Wohlbrandt, A.; Kissner, C.; Guérin, S.
2018-04-01
One of the dominant noise sources of modern Ultra High Bypass Ratio (UHBR) engines is the interaction of the rotor wakes with the leading edges of the stator vanes in the fan stage. While the tonal components of this noise generation mechanism are fairly well understood by now, the broadband components are not. This calls to further the understanding of the broadband noise generation in the fan stage. This article introduces a new extension to the Random Particle Mesh (RPM) method, which accommodates in-depth studies of the impact of cyclostationary wake characteristics on the broadband noise in the fan stage. The RPM method is used to synthesize a turbulence field in the stator domain using a URANS simulation characterized by time-periodic turbulence and mean flow. The rotor-stator interaction noise is predicted by a two-dimensional CAA computation of the stator cascade. The impact of cyclostationarity is decomposed into various effects, which are separately investigated. This leads to the finding that the periodic turbulent kinetic energy (TKE) and periodic flow have only a negligible effect on the radiated sound power. The impact of the periodic integral length scale (TLS) is, however, substantial. The limits of a stationary representation of the TLS are demonstrated making this new extension to the RPM method indispensable when background and wake TKE are of comparable level. Good agreement of the predictions with measurements obtained from the 2015 AIAA Fan Broadband Noise Prediction Workshop are also shown.
Talker and background noise specificity in spoken word recognition memory
Directory of Open Access Journals (Sweden)
Angela Cooper
2017-11-01
Full Text Available Prior research has demonstrated that listeners are sensitive to changes in the indexical (talker-specific characteristics of speech input, suggesting that these signal-intrinsic features are integrally encoded in memory for spoken words. Given that listeners frequently must contend with concurrent environmental noise, to what extent do they also encode signal-extrinsic details? Native English listeners’ explicit memory for spoken English monosyllabic and disyllabic words was assessed as a function of consistency versus variation in the talker’s voice (talker condition and background noise (noise condition using a delayed recognition memory paradigm. The speech and noise signals were spectrally-separated, such that changes in a simultaneously presented non-speech signal (background noise from exposure to test would not be accompanied by concomitant changes in the target speech signal. The results revealed that listeners can encode both signal-intrinsic talker and signal-extrinsic noise information into integrated cognitive representations, critically even when the two auditory streams are spectrally non-overlapping. However, the extent to which extra-linguistic episodic information is encoded alongside linguistic information appears to be modulated by syllabic characteristics, with specificity effects found only for monosyllabic items. These findings suggest that encoding and retrieval of episodic information during spoken word processing may be modulated by lexical characteristics.
Benchmarking the Algorithms to Detect Seasonal Signals Under Different Noise Conditions
Klos, A.; Bogusz, J.; Bos, M. S.
2017-12-01
Global Positioning System (GPS) position time series contain seasonal signals. Among the others, annual and semi-annual are the most powerful. Widely, these oscillations are modelled as curves with constant amplitudes, using the Weighted Least-Squares (WLS) algorithm. However, in reality, the seasonal signatures vary over time, as their geophysical causes are not constant. Different algorithms have been already used to cover this time-variability, as Wavelet Decomposition (WD), Singular Spectrum Analysis (SSA), Chebyshev Polynomial (CP) or Kalman Filter (KF). In this research, we employed 376 globally distributed GPS stations which time series contributed to the newest International Terrestrial Reference Frame (ITRF2014). We show that for c.a. 20% of stations the amplitudes of seasonal signal varies over time of more than 1.0 mm. Then, we compare the WD, SSA, CP and KF algorithms for a set of synthetic time series to quantify them under different noise conditions. We show that when variations of seasonal signals are ignored, the power-law character is biased towards flicker noise. The most reliable estimates of the variations were found to be given by SSA and KF. These methods also perform the best for other noise levels while WD, and to a lesser extend also CP, have trouble in separating the seasonal signal from the noise which leads to an underestimation in the spectral index of power-law noise of around 0.1. For real ITRF2014 GPS data we discovered, that SSA and KF are capable to model 49-84% and 77-90% of the variance of the true varying seasonal signals, respectively.
Transition edge sensor series array bolometer
Energy Technology Data Exchange (ETDEWEB)
Beyer, J, E-mail: joern.beyer@ptb.d [Physikalisch-Technische Bundesanstalt (PTB), Abbestrasse 2-12, D-10587 Berlin (Germany)
2010-10-15
A transition edge sensor series array (TES-SA) is an array of identical TESs that are connected in series by low-inductance superconducting wiring. The array elements are equally and well thermally coupled to the absorber and respond to changes in the absorber temperature in synchronization. The TES-SA total resistance increases compared to a single TES while the shape of the superconducting transition is preserved. We are developing a TES-SA with a large number, hundreds to thousands, of array elements with the goal of enabling the readout of a TES-based bolometer operated at 4.2 K with a semiconductor-based amplifier located at room temperature. The noise and dynamic performance of a TES-SA bolometer based on a niobium/aluminum bilayer is analyzed. It is shown that stable readout of the bolometer with a low-noise transimpedance amplifier is feasible.
Transition edge sensor series array bolometer
International Nuclear Information System (INIS)
Beyer, J
2010-01-01
A transition edge sensor series array (TES-SA) is an array of identical TESs that are connected in series by low-inductance superconducting wiring. The array elements are equally and well thermally coupled to the absorber and respond to changes in the absorber temperature in synchronization. The TES-SA total resistance increases compared to a single TES while the shape of the superconducting transition is preserved. We are developing a TES-SA with a large number, hundreds to thousands, of array elements with the goal of enabling the readout of a TES-based bolometer operated at 4.2 K with a semiconductor-based amplifier located at room temperature. The noise and dynamic performance of a TES-SA bolometer based on a niobium/aluminum bilayer is analyzed. It is shown that stable readout of the bolometer with a low-noise transimpedance amplifier is feasible.
Inference from the futures: ranking the noise cancelling accuracy of realized measures
DEFF Research Database (Denmark)
Mirone, Giorgio
We consider the log-linear relationship between futures contracts and their underlying assets and show that in the classical Brownian semi-martingale (BSM) framework the two series must, by no-arbitrage, have the same integrated variance. We then introduce the concept of noise cancelling...... measures in the presence of noise. Moreover, a thorough simulation analysis is employed to evaluate the estimators' sensitivity to different price and noise processes, and sampling frequencies....
Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.
Molenaar, Peter C. M.; Nesselroade, John R.
2001-01-01
Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…
A data-driven approach for denoising GNSS position time series
Li, Yanyan; Xu, Caijun; Yi, Lei; Fang, Rongxin
2017-12-01
Global navigation satellite system (GNSS) datasets suffer from common mode error (CME) and other unmodeled errors. To decrease the noise level in GNSS positioning, we propose a new data-driven adaptive multiscale denoising method in this paper. Both synthetic and real-world long-term GNSS datasets were employed to assess the performance of the proposed method, and its results were compared with those of stacking filtering, principal component analysis (PCA) and the recently developed multiscale multiway PCA. It is found that the proposed method can significantly eliminate the high-frequency white noise and remove the low-frequency CME. Furthermore, the proposed method is more precise for denoising GNSS signals than the other denoising methods. For example, in the real-world example, our method reduces the mean standard deviation of the north, east and vertical components from 1.54 to 0.26, 1.64 to 0.21 and 4.80 to 0.72 mm, respectively. Noise analysis indicates that for the original signals, a combination of power-law plus white noise model can be identified as the best noise model. For the filtered time series using our method, the generalized Gauss-Markov model is the best noise model with the spectral indices close to - 3, indicating that flicker walk noise can be identified. Moreover, the common mode error in the unfiltered time series is significantly reduced by the proposed method. After filtering with our method, a combination of power-law plus white noise model is the best noise model for the CMEs in the study region.
Stochastic resonance: noise-enhanced order
International Nuclear Information System (INIS)
Anishchenko, Vadim S; Neiman, Arkady B; Moss, F; Shimansky-Geier, L
1999-01-01
Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)
Stochastic resonance: noise-enhanced order
Energy Technology Data Exchange (ETDEWEB)
Anishchenko, Vadim S; Neiman, Arkady B [N.G. Chernyshevskii Saratov State University, Saratov (Russian Federation); Moss, F [Department of Physics and Astronomy, University of Missouri at St. Louis (United States); Shimansky-Geier, L [Humboldt University at Berlin (Germany)
1999-01-31
Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)
Identification of neutron noise sources in a boiling water reactor
International Nuclear Information System (INIS)
Sides, W.H. Jr.; Mathis, M.V.; Smith, C.M.
1977-01-01
Measurements were made at units 2 and 3 of the Browns Ferry Nuclear Power Plant in order to characterize the noise signatures of the neutron and process signals and to determine the usefulness of such signatures for anomaly detection in BWR-4s. Previous measurements and theoretical analyses of BWR noise by others were concerned with the determination of steam velocity and void fraction (using the local component of neutron noise) and with the sources of global noise. The work described is under a five-part program to develop a complete and systematic analysis and representation of BWR neutron and process noise through complementary measurements and stochastic model developments. The parts are: (1) recording as many neutron detector and process noise signals as are available in a BWR-4; (2) reducing these data to noise signatures in order to perform an empirical analysis of these signatures, and documenting the relationships between the signals from spatially separated neutron detectors and between neutron and process variables; (3) developing spatially dependent neutronic models coupled with thermal-hydraulic models to aid in interpreting the observed relationships among the measured noise signatures, (4) comparing measured noise signatures with model predictions to obtain additional insight into BWR-4 dynamic behavior and to validate the models; and (5) using these models to predict the sensitivity of noise monitoring for detection, surveillance, and diagnosis of postulated in-core anomalies in BWRs. The paper describes the procedures used to obtain the noise recordings and presents initial empirical analysis and observations pertaining to the noise signatures and the relationships between several noise variables in the 0.01- to 1-Hz range. The mathematical models have not been developed sufficiently to report theoretical results or to compare measured spectra with model predictions at this time
Pope, L. D.; Wilby, E. G.; Willis, C. M.; Mayes, W. H.
1983-01-01
As part of the continuing development of an aircraft interior noise prediction model, in which a discrete modal representation and power flow analysis are used, theoretical results are considered for inclusion of sidewall trim, stiffened structures, and cabin acoustics with floor partition. For validation purposes, predictions of the noise reductions for three test articles (a bare ring-stringer stiffened cylinder, an unstiffened cylinder with floor and insulation, and a ring-stringer stiffened cylinder with floor and sidewall trim) are compared with measurements.
A perturbative approach for enhancing the performance of time series forecasting.
de Mattos Neto, Paulo S G; Ferreira, Tiago A E; Lima, Aranildo R; Vasconcelos, Germano C; Cavalcanti, George D C
2017-04-01
This paper proposes a method to perform time series prediction based on perturbation theory. The approach is based on continuously adjusting an initial forecasting model to asymptotically approximate a desired time series model. First, a predictive model generates an initial forecasting for a time series. Second, a residual time series is calculated as the difference between the original time series and the initial forecasting. If that residual series is not white noise, then it can be used to improve the accuracy of the initial model and a new predictive model is adjusted using residual series. The whole process is repeated until convergence or the residual series becomes white noise. The output of the method is then given by summing up the outputs of all trained predictive models in a perturbative sense. To test the method, an experimental investigation was conducted on six real world time series. A comparison was made with six other methods experimented and ten other results found in the literature. Results show that not only the performance of the initial model is significantly improved but also the proposed method outperforms the other results previously published. Copyright © 2017 Elsevier Ltd. All rights reserved.
Perceptual effects of noise reduction by time-frequency masking of noisy speech.
Brons, Inge; Houben, Rolph; Dreschler, Wouter A
2012-10-01
Time-frequency masking is a method for noise reduction that is based on the time-frequency representation of a speech in noise signal. Depending on the estimated signal-to-noise ratio (SNR), each time-frequency unit is either attenuated or not. A special type of a time-frequency mask is the ideal binary mask (IBM), which has access to the real SNR (ideal). The IBM either retains or removes each time-frequency unit (binary mask). The IBM provides large improvements in speech intelligibility and is a valuable tool for investigating how different factors influence intelligibility. This study extends the standard outcome measure (speech intelligibility) with additional perceptual measures relevant for noise reduction: listening effort, noise annoyance, speech naturalness, and overall preference. Four types of time-frequency masking were evaluated: the original IBM, a tempered version of the IBM (called ITM) which applies limited and non-binary attenuation, and non-ideal masking (also tempered) with two different types of noise-estimation algorithms. The results from ideal masking imply that there is a trade-off between intelligibility and sound quality, which depends on the attenuation strength. Additionally, the results for non-ideal masking suggest that subjective measures can show effects of noise reduction even if noise reduction does not lead to differences in intelligibility.
Simultaneous identification of transfer functions and combustion noise of a turbulent flame
Merk, M.; Jaensch, S.; Silva, C.; Polifke, W.
2018-05-01
The Large Eddy Simulation/System Identification (LES/SI) approach allows to deduce a flame transfer function (FTF) from LES of turbulent reacting flow: Time series of fluctuations of reference velocity and global heat release rate resulting from broad-band excitation of a simulated turbulent flame are post-processed via SI techniques to derive a low order model of the flame dynamics, from which the FTF is readily deduced. The current work investigates an extension of the established LES/SI approach: In addition to estimation of the FTF, a low order model for the combustion noise source is deduced from the same time series data. By incorporating such a noise model into a linear thermoacoustic model, it is possible to predict the overall level as well as the spectral distribution of sound pressure in confined combustion systems that do not exhibit self-excited thermoacoustic instability. A variety of model structures for estimation of a noise model are tested in the present study. The suitability and quality of these model structures are compared against each other, their sensitivity regarding certain time series properties is studied. The influence of time series length, signal-to-noise ratio as well as acoustic reflection coefficient of the boundary conditions on the identification are examined. It is shown that the Box-Jenkins model structure is superior to simpler approaches for the simultaneous identification of models that describe the FTF as well as the combustion noise source. Subsequent to the question of the most adequate model structure, the choice of optimal model order is addressed, as in particular the optimal parametrization of the noise model is not obvious. Akaike's Information Criterion and a model residual analysis are applied to draw qualitative and quantitative conclusions on the most suitable model order. All investigations are based on a surrogate data model, which allows a Monte Carlo study across a large parameter space with modest
Cyclo-speed reducer 6000 series; Saikuro {reg_sign} gensokuki 6000 series
Energy Technology Data Exchange (ETDEWEB)
NONE
2000-04-20
This series was put on the market as the advanced speed reducer '6000 series' in April, 2000 after further improvement of various previous excellent features by adopting innovative technologies. Various series of this cyclo-speed reducers adopting a unique inscribed epicyclic gear mechanism reach 7 million units in sales success. Main specifications: (1) Input capacity range: 0.1-132kW, (2) Output torque: 24-68,200N(center dot)m, (3) Reduction ratio: 6-1,000,000. Features: (1) High efficiency and long life by adopting the analysis system based on the latest analytical technology, (2) Noise reduction by a maximum of nearly 6dB, and tone improvement by adopting a new tooth profile, (3) Weight reduction by a maximum of nearly 40% by adopting a motor direct-coupled mechanism. (translated by NEDO)
Belief propagation and loop series on planar graphs
International Nuclear Information System (INIS)
Chertkov, Michael; Teodorescu, Razvan; Chernyak, Vladimir Y
2008-01-01
We discuss a generic model of Bayesian inference with binary variables defined on edges of a planar graph. The Loop Calculus approach of Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R) [cond-mat/0601487]; 2006 J. Stat. Mech. P06009 [cond-mat/0603189]) is used to evaluate the resulting series expansion for the partition function. We show that, for planar graphs, truncating the series at single-connected loops reduces, via a map reminiscent of the Fisher transformation (Fisher 1961 Phys. Rev. 124 1664), to evaluating the partition function of the dimer-matching model on an auxiliary planar graph. Thus, the truncated series can be easily re-summed, using the Pfaffian formula of Kasteleyn (1961 Physics 27 1209). This allows us to identify a big class of computationally tractable planar models reducible to a dimer model via the Belief Propagation (gauge) transformation. The Pfaffian representation can also be extended to the full Loop Series, in which case the expansion becomes a sum of Pfaffian contributions, each associated with dimer matchings on an extension to a subgraph of the original graph. Algorithmic consequences of the Pfaffian representation, as well as relations to quantum and non-planar models, are discussed
Comparing the effects of aging and background noise on short-term memory performance.
Murphy, Dana R; Craik, Fergus I M; Li, Karen Z H; Schneider, Bruce A
2000-06-01
Paired associate recall was tested as a function of serial position for younger and older adults for five word pairs presented aurally in quiet and in noise. In Experiment 1, the addition of noise adversely affected recall in young adults, but only in the early serial positions. Experiments 2 and 3 suggested that the recall of older adults listening to the words in quiet was nearly equivalent to that of younger adults listening in noise. In Experiment 4, we determined the signal-to-noise ratio (S/N) such that, on average, younger and older adults were able to correctly hear the same percentage of words when words were presented one at a time in noise. In Experiment 5, younger adults were tested under this S/N. Compared with older adults from Experiment 3, younger adults in this experiment recalled more words at all serial positions. The results are interpreted as showing that encoding in secondary memory is impaired by aging and noise either as a function of degraded sensory representations, or as a function of reduced processing resources.
Renormalized powers of quantum white noise
International Nuclear Information System (INIS)
Accardi, L.; Boukas, A.
2009-01-01
Giving meaning to the powers of the creation and annihilation densities (quantum white noise) is an old and important problem in quantum field theory. In this paper we present an account of some new ideas that have recently emerged in the attempt to solve this problem. We emphasize the connection between the Lie algebra of the renormalized higher powers of quantum white noise (RHPWN), which can be interpreted as a suitably deformed (due to renormalization) current algebra over the 1-mode full oscillator algebra, and the current algebra over the centerless Virasoro (or Witt)-Zamolodchikov-ω ∞ Lie algebras of conformal field theory. Through a suitable definition of the action on the vacuum vector we describe how to obtain a Fock representation of all these algebras. We prove that the restriction of the vacuum to the abelian subalgebra generated by the field operators gives an infinitely divisible process whose marginal distribution is the beta (or continuous binomial). (authors)
Background Noise Degrades Central Auditory Processing in Toddlers.
Niemitalo-Haapola, Elina; Haapala, Sini; Jansson-Verkasalo, Eira; Kujala, Teija
2015-01-01
Noise, as an unwanted sound, has become one of modern society's environmental conundrums, and many children are exposed to higher noise levels than previously assumed. However, the effects of background noise on central auditory processing of toddlers, who are still acquiring language skills, have so far not been determined. The authors evaluated the effects of background noise on toddlers' speech-sound processing by recording event-related brain potentials. The hypothesis was that background noise modulates neural speech-sound encoding and degrades speech-sound discrimination. Obligatory P1 and N2 responses for standard syllables and the mismatch negativity (MMN) response for five different syllable deviants presented in a linguistic multifeature paradigm were recorded in silent and background noise conditions. The participants were 18 typically developing 22- to 26-month-old monolingual children with healthy ears. The results showed that the P1 amplitude was smaller and the N2 amplitude larger in the noisy conditions compared with the silent conditions. In the noisy condition, the MMN was absent for the intensity and vowel changes and diminished for the consonant, frequency, and vowel duration changes embedded in speech syllables. Furthermore, the frontal MMN component was attenuated in the noisy condition. However, noise had no effect on P1, N2, or MMN latencies. The results from this study suggest multiple effects of background noise on the central auditory processing of toddlers. It modulates the early stages of sound encoding and dampens neural discrimination vital for accurate speech perception. These results imply that speech processing of toddlers, who may spend long periods of daytime in noisy conditions, is vulnerable to background noise. In noisy conditions, toddlers' neural representations of some speech sounds might be weakened. Thus, special attention should be paid to acoustic conditions and background noise levels in children's daily environments
Hu, Yi
2010-05-01
Recent research results show that combined electric and acoustic stimulation (EAS) significantly improves speech recognition in noise, and it is generally established that access to the improved F0 representation of target speech, along with the glimpse cues, provide the EAS benefits. Under noisy listening conditions, noise signals degrade these important cues by introducing undesired temporal-frequency components and corrupting harmonics structure. In this study, the potential of combining noise reduction and harmonics regeneration techniques was investigated to further improve speech intelligibility in noise by providing improved beneficial cues for EAS. Three hypotheses were tested: (1) noise reduction methods can improve speech intelligibility in noise for EAS; (2) harmonics regeneration after noise reduction can further improve speech intelligibility in noise for EAS; and (3) harmonics sideband constraints in frequency domain (or equivalently, amplitude modulation in temporal domain), even deterministic ones, can provide additional benefits. Test results demonstrate that combining noise reduction and harmonics regeneration can significantly improve speech recognition in noise for EAS, and it is also beneficial to preserve the harmonics sidebands under adverse listening conditions. This finding warrants further work into the development of algorithms that regenerate harmonics and the related sidebands for EAS processing under noisy conditions.
Novel 2D representation of vibration for local damage detection
Directory of Open Access Journals (Sweden)
Grzegorz Żak
2014-07-01
Full Text Available In this paper a new 2D representation for local damage detection is presented. It is based on a vibration time series analysis. A raw vibration signal is decomposed via short-time Fourier transform and new time series for each frequency bin are differentiated to decorrelate them. For each time series, autocorrelation function is calculated. In the next step ACF maps are constructed. For healthy bearing ACF map should not have visible horizontal lines indicating damage. The method is illustrated by analysis of real data containing signals from damaged bearing and healthy for comparison.
Directory of Open Access Journals (Sweden)
Ali Jafari
2012-06-01
Full Text Available The changes of women veil in Iran after the Islamic Revolution and examining its cultural, social, political and economic aspects and outcomes is very important and has turned into a hot issue for cultural studies on veil in the Islamic Republic of Iran. "Chador' as an outstanding type of women veil in Iran has been affected b general trends of these changes and considerable parts of public culture and media atmosphere of Iran specially I RIB and cinema have represented these recent transformations. Although a great part of Iranian women actions on Chador take place in its traditional and classical form , considering these kinds of changes in the sign and function of Chador for some parts of social body and media representations of this veil makes this phenomenon very important and sensitive for cultural studies of dress and veil in Iran. This article has studied some degrees of semiotic, functional and semantic changes of chador hijab in I RIB series. Through 4 focus group interviews with 15 academic and seminarian women dressing traditional and classical Chador, this study analyzed the recent IRIB constructions of Chador dressing women and girls" which describes the wide functional and semantic transformations of Chador representation in IRIB dramatic programs. Thus some media and cultural malfunctions are observed in these progI'3rIlS and Chador hijab has degraded to an attractive and flashy "cape".
Correlated Noise: How it Breaks NMF, and What to Do About It.
Plis, Sergey M; Potluru, Vamsi K; Lane, Terran; Calhoun, Vince D
2011-01-12
Non-negative matrix factorization (NMF) is a problem of decomposing multivariate data into a set of features and their corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and Stodden separability conditions of a dataset and a regular NMF algorithm will fail to decompose it, even when given freedom to be able to represent the noise as a separate feature. To cope with this issue, we present an algorithm for NMF with a generalized least squares objective function (glsNMF) and derive multiplicative updates for the method together with proving their convergence. The new algorithm successfully recovers the true representation from the noisy data. Robust performance can make glsNMF a valuable tool for analyzing empirical data.
Correlation Properties of (Discrete Fractional Gaussian Noise and Fractional Brownian Motion
Directory of Open Access Journals (Sweden)
Didier Delignières
2015-01-01
Full Text Available The fractional Gaussian noise/fractional Brownian motion framework (fGn/fBm has been widely used for modeling and interpreting physiological and behavioral data. The concept of 1/f noise, reflecting a kind of optimal complexity in the underlying systems, is of central interest in this approach. It is generally considered that fGn and fBm represent a continuum, punctuated by the boundary of “ideal” 1/f noise. In the present paper, we focus on the correlation properties of discrete-time versions of these processes (dfGn and dfBm. We especially derive a new analytical expression of the autocorrelation function (ACF of dfBm. We analyze the limit behavior of dfGn and dfBm when they approach their upper and lower limits, respectively. We show that, as H approaches 1, the ACF of dfGn tends towards 1 at all lags, suggesting that dfGn series tend towards straight line. Conversely, as H approaches 0, the ACF of dfBm tends towards 0 at all lags, suggesting that dfBm series tend towards white noise. These results reveal a severe breakdown of correlation properties around the 1/f boundary and challenge the idea of a smooth transition between dfGn and dfBm processes. We discuss the implications of these findings for the application of the dfGn/dfBm model to experimental series, in terms of theoretical interpretation and modeling.
Low-frequency noise properties in Pt-indium gallium zinc oxide Schottky diodes
Energy Technology Data Exchange (ETDEWEB)
Zhang, Jiawei; Zhang, Linqing; Ma, Xiaochen; Wilson, Joshua [School of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL (United Kingdom); Jin, Jidong [Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ (United Kingdom); Du, Lulu; Xin, Qian [School of Physics, Shandong University, Jinan 250100 (China); Song, Aimin, E-mail: A.Song@manchester.ac.uk [School of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL (United Kingdom); School of Physics, Shandong University, Jinan 250100 (China)
2015-08-31
The low-frequency noise properties of Pt-indium gallium zinc oxide (IGZO) Schottky diodes at different forward biases are investigated. The IGZO layer and Pt contact were deposited by RF sputtering at room temperature. The diode showed an ideality factor of 1.2 and a barrier height of 0.94 eV. The current noise spectral density exhibited 1/f behavior at low frequencies. The analysis of the current dependency of the noise spectral density revealed that for the as-deposited diode, the noise followed Luo's mobility and diffusivity fluctuation model in the thermionic-emission-limited region and Hooge's empirical theory in the series-resistance-limited region. A low Hooge's constant of 1.4 × 10{sup −9} was found in the space-charge region. In the series-resistance-limited region, the Hooge's constant was 2.2 × 10{sup −5}. After annealing, the diode showed degradation in the electrical performance. The interface-trap-induced noise dominated the noise spectrum. By using the random walk model, the interface-trap density was obtained to be 3.6 × 10{sup 15 }eV{sup −1 }cm{sup −2}. This work provides a quantitative approach to analyze the properties of Pt-IGZO interfacial layers. These low noise properties are a prerequisite to the use of IGZO Schottky diodes in switch elements in memory devices, photosensors, and mixer diodes.
DEFF Research Database (Denmark)
Möllers, Jan; Ørsted, Bent; Zhang, Genkai
2016-01-01
We explicitly construct a finite number of discrete components in the restriction of complementary series representations of rank one semisimple groups $G$ to rank one subgroups $G_1$. For this we use the realizations of complementary series representations of $G$ and $G_1$ on Sobolev spaces...
Harry Potter book series - trivial or not?
Directory of Open Access Journals (Sweden)
Brigita Pavšič
2006-12-01
Full Text Available The article explores the extcnt to which the features of trivial literature appear in the Harry Potter series by J. K. Rowling.This is done in comparison with another popular children's series, The Famous Five by Enid Blyton, which was analysed by Igor Saksida. The main focus of the analysis is on the schematic representation of plot, characters and the exotic nature of the setting and time of the stories.
Understanding the amplitudes of noise correlation measurements
Tsai, Victor C.
2011-01-01
Cross correlation of ambient seismic noise is known to result in time series from which station-station travel-time measurements can be made. Part of the reason that these cross-correlation travel-time measurements are reliable is that there exists a theoretical framework that quantifies how these travel times depend on the features of the ambient noise. However, corresponding theoretical results do not currently exist to describe how the amplitudes of the cross correlation depend on such features. For example, currently it is not possible to take a given distribution of noise sources and calculate the cross correlation amplitudes one would expect from such a distribution. Here, we provide a ray-theoretical framework for calculating cross correlations. This framework differs from previous work in that it explicitly accounts for attenuation as well as the spatial distribution of sources and therefore can address the issue of quantifying amplitudes in noise correlation measurements. After introducing the general framework, we apply it to two specific problems. First, we show that we can quantify the amplitudes of coherency measurements, and find that the decay of coherency with station-station spacing depends crucially on the distribution of noise sources. We suggest that researchers interested in performing attenuation measurements from noise coherency should first determine how the dominant sources of noise are distributed. Second, we show that we can quantify the signal-to-noise ratio of noise correlations more precisely than previous work, and that these signal-to-noise ratios can be estimated for given situations prior to the deployment of seismometers. It is expected that there are applications of the theoretical framework beyond the two specific cases considered, but these applications await future work.
Multi-scale analysis of teleconnection indices: climate noise and nonlinear trend analysis
Directory of Open Access Journals (Sweden)
C. Franzke
2009-02-01
Full Text Available The multi-scale nature and climate noise properties of teleconnection indices are examined by using the Empirical Mode Decomposition (EMD procedure. The EMD procedure allows for the analysis of non-stationary time series to extract physically meaningful intrinsic mode functions (IMF and nonlinear trends. The climatologically relevant monthly mean teleconnection indices of the North Atlantic Oscillation (NAO, the North Pacific index (NP and the Southern Annular Mode (SAM are analyzed.
The significance of IMFs and trends are tested against the null hypothesis of climate noise. The analysis of surrogate monthly mean time series from a red noise process shows that the EMD procedure is effectively a dyadic filter bank and the IMFs (except the first IMF are nearly Gaussian distributed. The distribution of the variance contained in IMFs of an ensemble of AR(1 simulations is nearly χ^{2} distributed. To test the statistical significance of the IMFs of the teleconnection indices and their nonlinear trends we utilize an ensemble of corresponding monthly averaged AR(1 processes, which we refer to as climate noise. Our results indicate that most of the interannual and decadal variability of the analysed teleconnection indices cannot be distinguished from climate noise. The NP and SAM indices have significant nonlinear trends, while the NAO has no significant trend when tested against a climate noise hypothesis.
A Closer Look: The Representation of Slavery in the "Dear America" Series
Williams, T. Lee
2009-01-01
The "Dear America" series is one of the most successful brands in children's literature. It inspired the publisher, Scholastic Books, to produce four related series that include more than 90 titles. Each book seeks to personalize important events in American history through the diary of a fictionalized main character. According to the publisher,…
ARIMA representation for daily solar irradiance and surface air temperature time series
Kärner, Olavi
2009-06-01
Autoregressive integrated moving average (ARIMA) models are used to compare long-range temporal variability of the total solar irradiance (TSI) at the top of the atmosphere (TOA) and surface air temperature series. The comparison shows that one and the same type of the model is applicable to represent the TSI and air temperature series. In terms of the model type surface air temperature imitates closely that for the TSI. This may mean that currently no other forcing to the climate system is capable to change the random walk type variability established by the varying activity of the rotating Sun. The result should inspire more detailed examination of the dependence of various climate series on short-range fluctuations of TSI.
Agatha: Disentangling period signals from correlated noise in a periodogram framework
Feng, F.; Tuomi, M.; Jones, H. R. A.
2018-04-01
Agatha is a framework of periodograms to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.
Jiang, Weiping; Deng, Liansheng; Zhou, Xiaohui; Ma, Yifang
2014-05-01
Higher-order ionospheric (HIO) corrections are proposed to become a standard part for precise GPS data analysis. For this study, we deeply investigate the impacts of the HIO corrections on the coordinate time series by implementing re-processing of the GPS data from Crustal Movement Observation Network of China (CMONOC). Nearly 13 year data are used in our three processing runs: (a) run NO, without HOI corrections, (b) run IG, both second- and third-order corrections are modeled using the International Geomagnetic Reference Field 11 (IGRF11) to model the magnetic field, (c) run ID, the same with IG but dipole magnetic model are applied. Both spectral analysis and noise analysis are adopted to investigate these effects. Results show that for CMONOC stations, HIO corrections are found to have brought an overall improvement. After the corrections are applied, the noise amplitudes decrease, with the white noise amplitudes showing a more remarkable variation. Low-latitude sites are more affected. For different coordinate components, the impacts vary. The results of an analysis of stacked periodograms show that there is a good match between the seasonal amplitudes and the HOI corrections, and the observed variations in the coordinate time series are related to HOI effects. HOI delays partially explain the seasonal amplitudes in the coordinate time series, especially for the U component. The annual amplitudes for all components are decreased for over one-half of the selected CMONOC sites. Additionally, the semi-annual amplitudes for the sites are much more strongly affected by the corrections. However, when diplole model is used, the results are not as optimistic as IGRF model. Analysis of dipole model indicate that HIO delay lead to the increase of noise amplitudes, and that HIO delays with dipole model can generate false periodic signals. When dipole model are used in modeling HIO terms, larger residual and noise are brought in rather than the effective improvements.
Vilar, J. M. G. (José M. G.), 1972-; Rubí Capaceti, José Miguel
2001-01-01
We have analyzed the interplay between an externally added noise and the intrinsic noise of systems that relax fast towards a stationary state, and found that increasing the intensity of the external noise can reduce the total noise of the system. We have established a general criterion for the appearance of this phenomenon and discussed two examples in detail.
On the Impact of a Quadratic Acceleration Term in the Analysis of Position Time Series
Bogusz, Janusz; Klos, Anna; Bos, Machiel Simon; Hunegnaw, Addisu; Teferle, Felix Norman
2016-04-01
The analysis of Global Navigation Satellite System (GNSS) position time series generally assumes that each of the coordinate component series is described by the sum of a linear rate (velocity) and various periodic terms. The residuals, the deviations between the fitted model and the observations, are then a measure of the epoch-to-epoch scatter and have been used for the analysis of the stochastic character (noise) of the time series. Often the parameters of interest in GNSS position time series are the velocities and their associated uncertainties, which have to be determined with the highest reliability. It is clear that not all GNSS position time series follow this simple linear behaviour. Therefore, we have added an acceleration term in the form of a quadratic polynomial function to the model in order to better describe the non-linear motion in the position time series. This non-linear motion could be a response to purely geophysical processes, for example, elastic rebound of the Earth's crust due to ice mass loss in Greenland, artefacts due to deficiencies in bias mitigation models, for example, of the GNSS satellite and receiver antenna phase centres, or any combination thereof. In this study we have simulated 20 time series with different stochastic characteristics such as white, flicker or random walk noise of length of 23 years. The noise amplitude was assumed at 1 mm/y-/4. Then, we added the deterministic part consisting of a linear trend of 20 mm/y (that represents the averaged horizontal velocity) and accelerations ranging from minus 0.6 to plus 0.6 mm/y2. For all these data we estimated the noise parameters with Maximum Likelihood Estimation (MLE) using the Hector software package without taken into account the non-linear term. In this way we set the benchmark to then investigate how the noise properties and velocity uncertainty may be affected by any un-modelled, non-linear term. The velocities and their uncertainties versus the accelerations for
Highly comparative time-series analysis: the empirical structure of time series and their methods.
Fulcher, Ben D; Little, Max A; Jones, Nick S
2013-06-06
The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.
The Effects of Ambient Conditions on Helicopter Rotor Source Noise Modeling
Schmitz, Frederic H.; Greenwood, Eric
2011-01-01
A new physics-based method called Fundamental Rotorcraft Acoustic Modeling from Experiments (FRAME) is used to demonstrate the change in rotor harmonic noise of a helicopter operating at different ambient conditions. FRAME is based upon a non-dimensional representation of the governing acoustic and performance equations of a single rotor helicopter. Measured external noise is used together with parameter identification techniques to develop a model of helicopter external noise that is a hybrid between theory and experiment. The FRAME method is used to evaluate the main rotor harmonic noise of a Bell 206B3 helicopter operating at different altitudes. The variation with altitude of Blade-Vortex Interaction (BVI) noise, known to be a strong function of the helicopter s advance ratio, is dependent upon which definition of airspeed is flown by the pilot. If normal flight procedures are followed and indicated airspeed (IAS) is held constant, the true airspeed (TAS) of the helicopter increases with altitude. This causes an increase in advance ratio and a decrease in the speed of sound which results in large changes to BVI noise levels. Results also show that thickness noise on this helicopter becomes more intense at high altitudes where advancing tip Mach number increases because the speed of sound is decreasing and advance ratio increasing for the same indicated airspeed. These results suggest that existing measurement-based empirically derived helicopter rotor noise source models may give incorrect noise estimates when they are used at conditions where data were not measured and may need to be corrected for mission land-use planning purposes.
Gender Representation in Japanese EFL Textbooks--A Corpus Study
Lee, Jackie F. K.
2018-01-01
This paper seeks to investigate whether the Japanese government's attempt to promote a 'gender-equal' society in recent decades and the improved status of women are reflected in patterns of gender representation in Japanese English as a foreign language textbooks. The study made an analysis of four popular series of English language textbooks…
A Unified Graphical Representation of Chemical Thermodynamics and Equilibrium
Hanson, Robert M.
2012-01-01
During the years 1873-1879, J. Willard Gibbs published his now-famous set of articles that form the basis of the current perspective on chemical thermodynamics. The second article of this series, "A Method of Geometrical Representation of the Thermodynamic Properties of Substances by Means of Surfaces," published in 1873, is particularly notable…
An adaptive state of charge estimation approach for lithium-ion series-connected battery system
Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael
2018-07-01
Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.
Extra-auditory responses to long-term intermittent noise stimulation in humans.
Fruhstorfer, B; Hensel, H
1980-12-01
Respiration, heart rate, cutaneous blood flow, and electroencephalogram (EEG) reactions to long-term intermittent noise exposure were recorded from 13 volunteers (20-29 yr) with normal hearing and vegetative reactivity. They received daily within 1 h 12 noise stimuli (16 s 100 dB (A) white noise) for 10 or 21 days, respectively. Most subjects reported partial subjective adaptation to the noise. Heart rate adapted within a session but did not change considerably during successive days. Vascular responses did not change during one session but diminished mainly during the first 10 days. Noise responses in the EEG remained constant, but a decrease in vigilance occurred during the whole experimental series. Respiration responses were unpredictable and showed no trend within the sessions. It was concluded that certain physiological responses adapt to loud noise but that the time course of adaptation is different. Therefore a general statement about physiological noise adaptation is not possible.
Representation of hysteresis with wipe-out memory
International Nuclear Information System (INIS)
Friedman, G.; Cha, K.
2001-01-01
A model representing scalar hysteretic systems with wipe-out memory is proposed. In this model a hysteresis operator is represented as a power series expansion containing an infinite number of terms in general. It is shown that this representation converges to any given hysteresis relation having wipe-out memory as long as the output of the given hysteresis varies sufficiently smoothly with input history. [copyright] 2001 American Institute of Physics
Environmental Pollution: Noise Pollution - Sonic Boom. Volume I.
Defense Documentation Center, Alexandria, VA.
The unclassified, annotated bibliography is Volume I of a two-volume set on Noise Pollution - Sonic Boom in a series of scheduled bibliographies on Environmental Pollution. Volume II is Confidential. Corporate author-monitoring agency, subject, title, contract, and report number indexes are included. (Author/JR)
CSIR Research Space (South Africa)
Fedotov, I
2006-07-01
Full Text Available The Combined Helmholtz Integral Equation – Fourier series Formulation (CHIEFF) is based on representation of a velocity potential in terms of Fourier series and finding the Fourier coefficients of this expansion. The solution could be substantially...
Dynamic visual noise reduces confidence in short-term memory for visual information.
Kemps, Eva; Andrade, Jackie
2012-05-01
Previous research has shown effects of the visual interference technique, dynamic visual noise (DVN), on visual imagery, but not on visual short-term memory, unless retention of precise visual detail is required. This study tested the prediction that DVN does also affect retention of gross visual information, specifically by reducing confidence. Participants performed a matrix pattern memory task with three retention interval interference conditions (DVN, static visual noise and no interference control) that varied from trial to trial. At recall, participants indicated whether or not they were sure of their responses. As in previous research, DVN did not impair recall accuracy or latency on the task, but it did reduce recall confidence relative to static visual noise and no interference. We conclude that DVN does distort visual representations in short-term memory, but standard coarse-grained recall measures are insensitive to these distortions.
Bernoulli Polynomials, Fourier Series and Zeta Numbers
DEFF Research Database (Denmark)
Scheufens, Ernst E
2013-01-01
Fourier series for Bernoulli polynomials are used to obtain information about values of the Riemann zeta function for integer arguments greater than one. If the argument is even we recover the well-known exact values, if the argument is odd we find integral representations and rapidly convergent...
International Nuclear Information System (INIS)
Schmitt, Jeremy
2011-01-01
This thesis presents new methods for spherical Poisson data analysis for the Fermi mission. Fermi main scientific objectives, the study of diffuse galactic background et the building of the source catalog, are complicated by the weakness of photon flux and the point spread function of the instrument. This thesis proposes a new multi-scale representation for Poisson data on the sphere, the Multi-Scale Variance Stabilizing Transform on the Sphere (MS-VSTS), consisting in the combination of a spherical multi-scale transform (wavelets, curvelets) with a variance stabilizing transform (VST). This method is applied to mono- and multichannel Poisson noise removal, missing data interpolation, background extraction and multichannel deconvolution. Finally, this thesis deals with the problem of component separation using sparse representations (template fitting). (author) [fr
Basic-level and superordinate-like categorical representations in early infancy.
Behl-Chadha, G
1996-08-01
A series of experiments using the paired-preference procedure examined 3- to 4-month-old infants' ability to form perceptually based categorical representations in the domains of natural kinds and artifacts and probed the underlying organizational structure of these representations. Experiments 1 and 2 found that infants could form categorical representations for chairs that excluded exemplars of couches, beds, and tables and also for couches that excluded exemplars of chairs, beds, and tables. Thus, the adult-like exclusivity shown by infants in the categorization of various animal pictures at the basic-level extends to the domain of artifacts as well--an ecologically significant ability given the numerous artifacts that populate the human environment. Experiments 3 and 4 examined infants' ability to form superordinate-like or global categorical representations for mammals and furniture. It was found that infants could form a global representation for mammals that included novel mammals and excluded other non-mammalian animals such as birds and fish as well as items from cross-ontological categories such as furniture. In addition, it was found that infants formed a representation for furniture that included novel categories of furniture and excluded exemplars from the cross-ontological category of mammals; however, it was less clear if infants' global representation for furniture also excluded other artifacts such as vehicles and thus the category of furniture may have been less exclusively represented. Overall, the present findings, by showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, underscore the importance of these early representations for later conceptual representations.
The romanticization of abstinence: Fan response to sexual restraint in the Twilight series
Directory of Open Access Journals (Sweden)
Jennifer Stevens Aubrey, Elizabeth Behm-Morawitz, and Melissa A. Click
2010-09-01
Full Text Available Meyer's Twilight series has been criticized for its regressive gender representations. To understand its continuing appeal, we problematize the messages of abstinence and romance in the series, and contextualize fans' response with a discussion of postfeminist culture.
An approximate fractional Gaussian noise model with computational cost
Sø rbye, Sigrunn H.; Myrvoll-Nilsen, Eirik; Rue, Haavard
2017-01-01
Fractional Gaussian noise (fGn) is a stationary time series model with long memory properties applied in various fields like econometrics, hydrology and climatology. The computational cost in fitting an fGn model of length $n$ using a likelihood
time series modeling of daily abandoned calls in a call centre
African Journals Online (AJOL)
DJFLEX
Models for evaluating and predicting the short periodic time series in daily ... Ugwuowo (2006) proposed asymmetric angular- linear multivariate regression models, ..... Using the parameter estimates in Table 3, the fitted Fourier series model is ..... For the SARIMA model with the stochastic component also being white noise, ...
Social representations of human papillomavirus in Bogotá, Colombia.
Wiesner, Carolina; Acosta, Jesús; Díaz Del Castillo, Adriana; Tovar, Sandra
2012-01-01
Identifying DNA of Human papillomavirus (HPV) has been proposed as a new screening method for cervical cancer control. Conventionally, health education for screening programs is based on scientific information without considering any community cognitive processes. We examine HPV social representations of 124 men and women from diverse educational status living in Bogotá, Colombia. The social representation of HPV involves a series of figurative nuclei derived from meanings linked to scientific information. While women focused on symbols associated to contagion, men focused on its venereal character. Figurative nuclei also included long-term uncertainty, need or urgent treatment, and feelings of imminent death associated with cancer and chronic sexually transmitted infections. The social representation of HPV impeded many participants from clearly understanding written information about HPV transmission, clearance, and cancer risk; they are built into a framework of values, which must be deconstructed to allow women full participation in HPV screening programs.
Noise performance of microwave humidity sounders over their lifetime
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I. Hans
2017-12-01
Full Text Available The microwave humidity sounders Special Sensor Microwave Water Vapor Profiler (SSMT-2, Advanced Microwave Sounding Unit-B (AMSU-B and Microwave Humidity Sounder (MHS to date have been providing data records for 25 years. So far, the data records lack uncertainty information essential for constructing consistent long time data series. In this study, we assess the quality of the recorded data with respect to the uncertainty caused by noise. We calculate the noise on the raw calibration counts from the deep space views (DSVs of the instrument and the noise equivalent differential temperature (NEΔT as a measure for the radiometer sensitivity. For this purpose, we use the Allan deviation that is not biased from an underlying varying mean of the data and that has been suggested only recently for application in atmospheric remote sensing. Moreover, we use the bias function related to the Allan deviation to infer the underlying spectrum of the noise. As examples, we investigate the noise spectrum in flight for some instruments. For the assessment of the noise evolution in time, we provide a descriptive and graphical overview of the calculated NEΔT over the life span of each instrument and channel. This overview can serve as an easily accessible information for users interested in the noise performance of a specific instrument, channel and time. Within the time evolution of the noise, we identify periods of instrumental degradation, which manifest themselves in an increasing NEΔT, and periods of erratic behaviour, which show sudden increases of NEΔT interrupting the overall smooth evolution of the noise. From this assessment and subsequent exclusion of the aforementioned periods, we present a chart showing available data records with NEΔT < 1 K. Due to overlapping life spans of the instruments, these reduced data records still cover without gaps the time since 1994 and may therefore serve as a first step for constructing long time
Detecting low-dimensional chaos by the “noise titration” technique: Possible problems and remedies
International Nuclear Information System (INIS)
Gao Jianbo; Hu Jing; Mao Xiang; Tung Wenwen
2012-01-01
Highlights: ► Distinguishing low-dimensional chaos from noise is an important issue. ► Noise titration technique is one of the main approaches on the issue. ► Problems of noise titration technique are systematically discussed. ► Solutions to the problems of noise titration technique are provided. - Abstract: Distinguishing low-dimensional chaos from noise is an important issue in time series analysis. Among the many methods proposed for this purpose is the noise titration technique, which quantifies the amount of noise that needs to be added to the signal to fully destroy its nonlinearity. Two groups of researchers recently have questioned the validity of the technique. In this paper, we report a broad range of situations where the noise titration technique fails, and offer solutions to fix the problems identified.
Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.
2013-01-01
Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.
Quiet comfort: noise, otherness, and the mobile production of personal space.
Hagood, Mack
2011-01-01
Marketing, news reports, and reviews of Bose QuietComfort noise-canceling headphones position them as essential gear for the mobile rational actor of the neoliberal market—the business traveler. This article concerns noise-canceling headphones’ utility as soundscaping devices, which render a sense of personal space by mediating sound. The airplane and airport are paradoxical spaces in which the pursuit of freedom impedes its own enjoyment. Rather than fight the discomforts of air travel as a systemic problem, travelers use the tactic of soundscaping to suppress the perceived presence of others. Attention to soundscaping enables the scholar to explore relationships between media, space, freedom, otherness, and selfhood in an era characterized by neoliberalism and increased mobility. Air travel is a moment in which people with diverse backgrounds, beliefs, and bodies crowd together in unusually close proximity. Noise is the sound of individualism and difference in conflict. Noise is othered sound, and like any type of othering, the perception of noise is socially constructed and situated in hierarchies of race, class, age, and gender. The normative QuietComfort user in media representations is white, male, rational, monied, and mobile; women, children, and “chatty” passengers are cast as noisemakers. Moreover, in putting on noise-canceling headphones, diverse selves put on the historically Western subjectivity that has been built into their technology, one that suppresses the noise of difference in favor of the smooth circulation of people, information, and commodities.
Representation of photon limited data in emission tomography using origin ensembles
Sitek, A
2008-01-01
Representation and reconstruction of data obtained by emission tomography scanners are challenging due to high noise levels in the data. Typically, images obtained using tomographic measurements are represented using grids. In this work, we define images as sets of origins of events detected during tomographic measurements; we call these origin ensembles (OEs). A state in the ensemble is characterized by a vector of 3N parameters Y, where the parameters are the coordinates of origins of detec...
Noise and contrast detection in computed tomography images
International Nuclear Information System (INIS)
Faulkner, K.; Moores, B.M.
1984-01-01
A discrete representation of the reconstruction process is used in an analysis of noise in computed tomography (CT) images. This model is consistent with the method of data collection in actual machines. An expression is derived which predicts the variance on the measured linear attenuation coefficient of a single pixel in an image. The dependence of the variance on various CT scanner design parameters such as pixel size, slice width, scan time, number of detectors, etc., is then described. The variation of noise with sampling area is theoretically explained. These predictions are in good agreement with a set of experimental measurements made on a range of CT scanners. The equivalent sampling aperture of the CT process is determined and the effect of the reconstruction filter on the variance of the linear attenuation coefficient is also noted, in particular, the choice and its consequences for reconstructed images and noise behaviour. The theory has been extended to include contrast detail behaviour, and these predictions compare favourably with experimental measurements. The theory predicts that image smoothing will have little effect on the contrast-detail detectability behaviour of reconstructed images. (author)
Time-frequency peak filtering for random noise attenuation of magnetic resonance sounding signal
Lin, Tingting; Zhang, Yang; Yi, Xiaofeng; Fan, Tiehu; Wan, Ling
2018-05-01
When measuring in a geomagnetic field, the method of magnetic resonance sounding (MRS) is often limited because of the notably low signal-to-noise ratio (SNR). Most current studies focus on discarding spiky noise and power-line harmonic noise cancellation. However, the effects of random noise should not be underestimated. The common method for random noise attenuation is stacking, but collecting multiple recordings merely to suppress random noise is time-consuming. Moreover, stacking is insufficient to suppress high-level random noise. Here, we propose the use of time-frequency peak filtering for random noise attenuation, which is performed after the traditional de-spiking and power-line harmonic removal method. By encoding the noisy signal with frequency modulation and estimating the instantaneous frequency using the peak of the time-frequency representation of the encoded signal, the desired MRS signal can be acquired from only one stack. The performance of the proposed method is tested on synthetic envelope signals and field data from different surveys. Good estimations of the signal parameters are obtained at different SNRs. Moreover, an attempt to use the proposed method to handle a single recording provides better results compared to 16 stacks. Our results suggest that the number of stacks can be appropriately reduced to shorten the measurement time and improve the measurement efficiency.
Clustering of financial time series
D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo
2013-05-01
This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
Pre-attentive, context-specific representation of fear memory in the auditory cortex of rat.
Directory of Open Access Journals (Sweden)
Akihiro Funamizu
Full Text Available Neural representation in the auditory cortex is rapidly modulated by both top-down attention and bottom-up stimulus properties, in order to improve perception in a given context. Learning-induced, pre-attentive, map plasticity has been also studied in the anesthetized cortex; however, little attention has been paid to rapid, context-dependent modulation. We hypothesize that context-specific learning leads to pre-attentively modulated, multiplex representation in the auditory cortex. Here, we investigate map plasticity in the auditory cortices of anesthetized rats conditioned in a context-dependent manner, such that a conditioned stimulus (CS of a 20-kHz tone and an unconditioned stimulus (US of a mild electrical shock were associated only under a noisy auditory context, but not in silence. After the conditioning, although no distinct plasticity was found in the tonotopic map, tone-evoked responses were more noise-resistive than pre-conditioning. Yet, the conditioned group showed a reduced spread of activation to each tone with noise, but not with silence, associated with a sharpening of frequency tuning. The encoding accuracy index of neurons showed that conditioning deteriorated the accuracy of tone-frequency representations in noisy condition at off-CS regions, but not at CS regions, suggesting that arbitrary tones around the frequency of the CS were more likely perceived as the CS in a specific context, where CS was associated with US. These results together demonstrate that learning-induced plasticity in the auditory cortex occurs in a context-dependent manner.
Pre-attentive, context-specific representation of fear memory in the auditory cortex of rat.
Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu
2013-01-01
Neural representation in the auditory cortex is rapidly modulated by both top-down attention and bottom-up stimulus properties, in order to improve perception in a given context. Learning-induced, pre-attentive, map plasticity has been also studied in the anesthetized cortex; however, little attention has been paid to rapid, context-dependent modulation. We hypothesize that context-specific learning leads to pre-attentively modulated, multiplex representation in the auditory cortex. Here, we investigate map plasticity in the auditory cortices of anesthetized rats conditioned in a context-dependent manner, such that a conditioned stimulus (CS) of a 20-kHz tone and an unconditioned stimulus (US) of a mild electrical shock were associated only under a noisy auditory context, but not in silence. After the conditioning, although no distinct plasticity was found in the tonotopic map, tone-evoked responses were more noise-resistive than pre-conditioning. Yet, the conditioned group showed a reduced spread of activation to each tone with noise, but not with silence, associated with a sharpening of frequency tuning. The encoding accuracy index of neurons showed that conditioning deteriorated the accuracy of tone-frequency representations in noisy condition at off-CS regions, but not at CS regions, suggesting that arbitrary tones around the frequency of the CS were more likely perceived as the CS in a specific context, where CS was associated with US. These results together demonstrate that learning-induced plasticity in the auditory cortex occurs in a context-dependent manner.
Modeling Financial Time Series Based on a Market Microstructure Model with Leverage Effect
Directory of Open Access Journals (Sweden)
Yanhui Xi
2016-01-01
Full Text Available The basic market microstructure model specifies that the price/return innovation and the volatility innovation are independent Gaussian white noise processes. However, the financial leverage effect has been found to be statistically significant in many financial time series. In this paper, a novel market microstructure model with leverage effects is proposed. The model specification assumed a negative correlation in the errors between the price/return innovation and the volatility innovation. With the new representations, a theoretical explanation of leverage effect is provided. Simulated data and daily stock market indices (Shanghai composite index, Shenzhen component index, and Standard and Poor’s 500 Composite index via Bayesian Markov Chain Monte Carlo (MCMC method are used to estimate the leverage market microstructure model. The results verify the effectiveness of the model and its estimation approach proposed in the paper and also indicate that the stock markets have strong leverage effects. Compared with the classical leverage stochastic volatility (SV model in terms of DIC (Deviance Information Criterion, the leverage market microstructure model fits the data better.
Noise-assisted data processing with empirical mode decomposition in biomedical signals.
Karagiannis, Alexandros; Constantinou, Philip
2011-01-01
In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.
Directory of Open Access Journals (Sweden)
Dennis A Dean
Full Text Available We present a novel approach for analyzing biological time-series data using a context-free language (CFL representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.
The influence of signal type on the internal auditory representation of a room
Teret, Elizabeth
Currently, architectural acousticians make no real distinction between a room impulse response and the auditory system's internal representation of a room. With this lack of a good model for the auditory representation of a room, it is indirectly assumed that our internal representation of a room is independent of the sound source needed to make the room characteristics audible. The extent to which this assumption holds true is examined with perceptual tests. Listeners are presented with various pairs of signals (music, speech, and noise) convolved with synthesized impulse responses of different reverberation times. They are asked to adjust the reverberation of one of the signals to match the other. Analysis of the data show that the source signal significantly influences perceived reverberance. Listeners are less accurate when matching reverberation times of varied signals than they are with identical signals. Additional testing shows that perception of reverberation can be linked to the existence of transients in the signal.
Anti-deterministic behaviour of discrete systems that are less predictable than noise
Urbanowicz, Krzysztof; Kantz, Holger; Holyst, Janusz A.
2005-05-01
We present a new type of deterministic dynamical behaviour that is less predictable than white noise. We call it anti-deterministic (AD) because time series corresponding to the dynamics of such systems do not generate deterministic lines in recurrence plots for small thresholds. We show that although the dynamics is chaotic in the sense of exponential divergence of nearby initial conditions and although some properties of AD data are similar to white noise, the AD dynamics is in fact, less predictable than noise and hence is different from pseudo-random number generators.
Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew
2014-01-01
Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.
Turning Symbolic: The representation of motion direction in working memory
Directory of Open Access Journals (Sweden)
Tal eSeidel Malkinson
2016-02-01
Full Text Available What happens to the representation of a moving stimulus when it is no longer present and its motion direction has to be maintained in working memory (WM? Is the initial, sensorial representation maintained during the delay period or is there another representation, at a higher level of abstraction? It is also feasible that multiple representations may co-exist in WM, manifesting different facets of sensory and more abstract features.To that end, we investigated the mnemonic representation of motion direction in a series of three psychophysical experiments, using a delayed motion-discrimination task (relative clockwisecounter-clockwise judgment. First, we show that a change in the dots' contrast polarity does not hamper performance. Next, we demonstrate that performance is unaffected by relocation of the Test stimulus in either retinotopic or spatiotopic coordinate frames. Finally, we show that an arrow-shaped cue presented during the delay interval between the Sample and Test stimulus, biases performance towards the direction of the arrow, although the cue itself is non-informative (it has no predictive value of the correct answer. These results indicate that the representation of motion direction in WM is independent of the physical features of the stimulus (polarity or position and has non-sensorial abstract qualities. It is plausible that an abstract mnemonic trace might be activated alongside a more basic, analogue representation of the stimulus. We speculate that the specific sensitivity of the mnemonic representation to the arrow-shaped symbol may stem from the long term learned association between direction and the hour in the clock.
Fractal characterization for noise signal validation in power reactors
International Nuclear Information System (INIS)
Aguilar Martinez, Omar
2003-01-01
Up to now, a great variety of methods is used for the dynamical characterization of different components of Nuclear Power Plants (NPPs). With this aim, time and spectral analysis are usually considered, and different tools of non-stationary and non-gaussian analysis are also presented. When applying non-lineal dynamics theory for noise signal validation purposes in power reactors, the extraction of fractal echoes plays a main role. Fractal characterization for noise signal validation purposes can be integrated to the task of processing and acquisition of time signals in noise (fluctuation parameters) analysis systems. The possibility of discrimination between deterministic chaotic signals and pure noise signals has been incorporated, as a complement; to noise signals analysis in normal and anomalous operational conditions in NPPs using a fractal approach. In this work the detailed analysis of a neutronic sensor response is considered and the fractal characterization of its dynamics state (i.e. sensor line) for noise signal classification, it is presented. The experiment from where the time series (signals) were obtained, was carried out at the Research Reactor of the Technical University of Budapest, Hungary, during a model experiment for ageing process study of in-core neutron detectors (author)
Noise-induced chaos and basin erosion in softening Duffing oscillator
International Nuclear Information System (INIS)
Gan Chunbiao
2005-01-01
It is common for many dynamical systems to have two or more attractors coexist and in such cases the basin boundary is fractal. The purpose of this paper is to study the noise-induced chaos and discuss the effect of noises on erosion of safe basin in the softening Duffing oscillator. The Melnikov approach is used to obtain the necessary condition for the rising of chaos, and the largest Lyapunov exponent is computed to identify the chaotic nature of the sample time series from the system. According to the Melnikov condition, the safe basins are simulated for both the deterministic and the stochastic cases of the system. It is shown that the external Gaussian white noise excitation is robust for inducing the chaos, while the external bounded noise is weak. Moreover, the erosion of the safe basin can be aggravated by both the Gaussian white and the bounded noise excitations, and fractal boundary can appear when the system is only excited by the random processes, which means noise-induced chaotic response is induced
Characterization of echoes: A Dyson-series representation of individual pulses
Correia, Miguel R.; Cardoso, Vitor
2018-04-01
The ability to detect and scrutinize gravitational waves from the merger and coalescence of compact binaries opens up the possibility to perform tests of fundamental physics. One such test concerns the dark nature of compact objects: are they really black holes? It was recently pointed out that the absence of horizons—while keeping the external geometry very close to that of General Relativity—would manifest itself in a series of echoes in gravitational wave signals. The observation of echoes by LIGO/Virgo or upcoming facilities would likely inform us on quantum gravity effects or unseen types of matter. Detection of such signals is in principle feasible with relatively simple tools but would benefit enormously from accurate templates. Here we analytically individualize each echo waveform and show that it can be written as a Dyson series, for arbitrary effective potential and boundary conditions. We further apply the formalism to explicitly determine the echoes of a simple toy model: the Dirac delta potential. Our results allow to read off a few known features of echoes and may find application in the modeling for data analysis.
May, Josephine
2018-01-01
Building on the author's previous work on Australian national cinema and schooling, this article explores the representation of the female primary school teacher in the television mini-series entitled "Marion" (Australian Broadcasting Commission, 1974). Using narrative analysis, it argues that this representation is disruptive of…
Two-dimensional shape recognition using oriented-polar representation
Hu, Neng-Chung; Yu, Kuo-Kan; Hsu, Yung-Li
1997-10-01
To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant in spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.
Contour integral representations for the characters of rational conformal field theories
International Nuclear Information System (INIS)
Mukhi, S.; Panda, S.; Sen, A.
1989-01-01
We propose simple Feigin-Fuchs contour integral representations for the characters of a large class of rational conformal field theories. These include the A, D and E series SU(2) WZW theories, the A and D series c<1 minimal theories, and the k=1 SU(N) WZW theories. All these theories are characterized by the absence of the zeroes in the wronskian determinant of the characters in the interior of moduli space. This proposal is verified by several calculations. (orig.)
Mid-level image representations for real-time heart view plane classification of echocardiograms.
Penatti, Otávio A B; Werneck, Rafael de O; de Almeida, Waldir R; Stein, Bernardo V; Pazinato, Daniel V; Mendes Júnior, Pedro R; Torres, Ricardo da S; Rocha, Anderson
2015-11-01
In this paper, we explore mid-level image representations for real-time heart view plane classification of 2D echocardiogram ultrasound images. The proposed representations rely on bags of visual words, successfully used by the computer vision community in visual recognition problems. An important element of the proposed representations is the image sampling with large regions, drastically reducing the execution time of the image characterization procedure. Throughout an extensive set of experiments, we evaluate the proposed approach against different image descriptors for classifying four heart view planes. The results show that our approach is effective and efficient for the target problem, making it suitable for use in real-time setups. The proposed representations are also robust to different image transformations, e.g., downsampling, noise filtering, and different machine learning classifiers, keeping classification accuracy above 90%. Feature extraction can be performed in 30 fps or 60 fps in some cases. This paper also includes an in-depth review of the literature in the area of automatic echocardiogram view classification giving the reader a through comprehension of this field of study. Copyright © 2015 Elsevier Ltd. All rights reserved.
Spatial resolution limits for the localization of noise sources using direct sound mapping
DEFF Research Database (Denmark)
Comesana, D. Fernandez; Holland, K. R.; Fernandez Grande, Efren
2016-01-01
the relationship between spatial resolution, noise level and geometry. The proposed expressions are validated via simulations and experiments. It is shown that particle velocity mapping yields better results for identifying closely spaced sound sources than sound pressure or sound intensity, especially...... extensively been used for many years to locate sound sources. However, it is not yet well defined when two sources should be regarded as resolved by means of direct sound mapping. This paper derives the limits of the direct representation of sound pressure, particle velocity and sound intensity by exploring......One of the main challenges arising from noise and vibration problems is how to identify the areas of a device, machine or structure that produce significant acoustic excitation, i.e. the localization of main noise sources. The direct visualization of sound, in particular sound intensity, has...
Effects of background noise on total noise annoyance
Willshire, K. F.
1987-01-01
Two experiments were conducted to assess the effects of combined community noise sources on annoyance. The first experiment baseline relationships between annoyance and noise level for three community noise sources (jet aircraft flyovers, traffic and air conditioners) presented individually. Forty eight subjects evaluated the annoyance of each noise source presented at four different noise levels. Results indicated the slope of the linear relationship between annoyance and noise level for the traffic noise was significantly different from that of aircraft and of air conditioner noise, which had equal slopes. The second experiment investigated annoyance response to combined noise sources, with aircraft noise defined as the major noise source and traffic and air conditioner noise as background noise sources. Effects on annoyance of noise level differences between aircraft and background noise for three total noise levels and for both background noise sources were determined. A total of 216 subjects were required to make either total or source specific annoyance judgements, or a combination of the two, for a wide range of combined noise conditions.
Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method
Directory of Open Access Journals (Sweden)
Xiaowang Li
2016-01-01
Full Text Available A new method based on the second-order Taylor-series expansion is presented to identify the structural dynamic loads in the time domain. This algorithm expresses the response vectors as Taylor-series approximation and then a series of formulas are deduced. As a result, an explicit discrete equation which associates system response, system characteristic, and input excitation together is set up. In a multi-input-multi-output (MIMO numerical simulation study, sinusoidal excitation and white noise excitation are applied on a cantilever beam, respectively, to illustrate the effectiveness of this algorithm. One also makes a comparison between the new method and conventional state space method. The results show that the proposed method can obtain a more accurate identified force time history whether the responses are polluted by noise or not.
Maximizing noise energy for noise-masking studies.
Jules Étienne, Cédric; Arleo, Angelo; Allard, Rémy
2017-08-01
Noise-masking experiments are widely used to investigate visual functions. To be useful, noise generally needs to be strong enough to noticeably impair performance, but under some conditions, noise does not impair performance even when its contrast approaches the maximal displayable limit of 100 %. To extend the usefulness of noise-masking paradigms over a wider range of conditions, the present study developed a noise with great masking strength. There are two typical ways of increasing masking strength without exceeding the limited contrast range: use binary noise instead of Gaussian noise or filter out frequencies that are not relevant to the task (i.e., which can be removed without affecting performance). The present study combined these two approaches to further increase masking strength. We show that binarizing the noise after the filtering process substantially increases the energy at frequencies within the pass-band of the filter given equated total contrast ranges. A validation experiment showed that similar performances were obtained using binarized-filtered noise and filtered noise (given equated noise energy at the frequencies within the pass-band) suggesting that the binarization operation, which substantially reduced the contrast range, had no significant impact on performance. We conclude that binarized-filtered noise (and more generally, truncated-filtered noise) can substantially increase the energy of the noise at frequencies within the pass-band. Thus, given a limited contrast range, binarized-filtered noise can display higher energy levels than Gaussian noise and thereby widen the range of conditions over which noise-masking paradigms can be useful.
Recursive Bayesian recurrent neural networks for time-series modeling.
Mirikitani, Derrick T; Nikolaev, Nikolay
2010-02-01
This paper develops a probabilistic approach to recursive second-order training of recurrent neural networks (RNNs) for improved time-series modeling. A general recursive Bayesian Levenberg-Marquardt algorithm is derived to sequentially update the weights and the covariance (Hessian) matrix. The main strengths of the approach are a principled handling of the regularization hyperparameters that leads to better generalization, and stable numerical performance. The framework involves the adaptation of a noise hyperparameter and local weight prior hyperparameters, which represent the noise in the data and the uncertainties in the model parameters. Experimental investigations using artificial and real-world data sets show that RNNs equipped with the proposed approach outperform standard real-time recurrent learning and extended Kalman training algorithms for recurrent networks, as well as other contemporary nonlinear neural models, on time-series modeling.
Auditory white noise reduces postural fluctuations even in the absence of vision.
Ross, Jessica Marie; Balasubramaniam, Ramesh
2015-08-01
The contributions of somatosensory, vestibular, and visual feedback to balance control are well documented, but the influence of auditory information, especially acoustic noise, on balance is less clear. Because somatosensory noise has been shown to reduce postural sway, we hypothesized that noise from the auditory modality might have a similar effect. Given that the nervous system uses noise to optimize signal transfer, adding mechanical or auditory noise should lead to increased feedback about sensory frames of reference used in balance control. In the present experiment, postural sway was analyzed in healthy young adults where they were presented with continuous white noise, in the presence and absence of visual information. Our results show reduced postural sway variability (as indexed by the body's center of pressure) in the presence of auditory noise, even when visual information was not present. Nonlinear time series analysis revealed that auditory noise has an additive effect, independent of vision, on postural stability. Further analysis revealed that auditory noise reduced postural sway variability in both low- and high-frequency regimes (> or noise. Our results support the idea that auditory white noise reduces postural sway, suggesting that auditory noise might be used for therapeutic and rehabilitation purposes in older individuals and those with balance disorders.
Autonomous data acquisition system for Paks NPP process noise signals
International Nuclear Information System (INIS)
Lipcsei, S.; Kiss, S.; Czibok, T.; Dezso, Z.; Horvath, Cs.
2005-01-01
A prototype of a new concept noise diagnostics data acquisition system has been developed recently to renew the aged present system. This new system is capable of collecting the whole available noise signal set simultaneously. Signal plugging and data acquisition are performed by autonomous systems (installed at each reactor unit) that are controlled through the standard plant network from a central computer installed at a suitable location. Experts can use this central unit to process and archive data series downloaded from the reactor units. This central unit also provides selected noise diagnostics information for other departments. The paper describes the hardware and software architecture of the new system in detail, emphasising the potential benefits of the new approach. (author)
OCT despeckling via weighted nuclear norm constrained non-local low-rank representation
Tang, Chang; Zheng, Xiao; Cao, Lijuan
2017-10-01
As a non-invasive imaging modality, optical coherence tomography (OCT) plays an important role in medical sciences. However, OCT images are always corrupted by speckle noise, which can mask image features and pose significant challenges for medical analysis. In this work, we propose an OCT despeckling method by using non-local, low-rank representation with weighted nuclear norm constraint. Unlike previous non-local low-rank representation based OCT despeckling methods, we first generate a guidance image to improve the non-local group patches selection quality, then a low-rank optimization model with a weighted nuclear norm constraint is formulated to process the selected group patches. The corrupted probability of each pixel is also integrated into the model as a weight to regularize the representation error term. Note that each single patch might belong to several groups, hence different estimates of each patch are aggregated to obtain its final despeckled result. Both qualitative and quantitative experimental results on real OCT images show the superior performance of the proposed method compared with other state-of-the-art speckle removal techniques.
Time series patterns and language support in DBMS
Telnarova, Zdenka
2017-07-01
This contribution is focused on pattern type Time Series as a rich in semantics representation of data. Some example of implementation of this pattern type in traditional Data Base Management Systems is briefly presented. There are many approaches how to manipulate with patterns and query patterns. Crucial issue can be seen in systematic approach to pattern management and specific pattern query language which takes into consideration semantics of patterns. Query language SQL-TS for manipulating with patterns is shown on Time Series data.
Active Noise Control for Dishwasher noise
Lee, Nokhaeng; Park, Youngjin
2016-09-01
The dishwasher is a useful home appliance and continually used for automatically washing dishes. It's commonly placed in the kitchen with built-in style for practicality and better use of space. In this environment, people are easily exposed to dishwasher noise, so it is an important issue for the consumers, especially for the people living in open and narrow space. Recently, the sound power levels of the noise are about 40 - 50 dBA. It could be achieved by removal of noise sources and passive means of insulating acoustical path. For more reduction, such a quiet mode with the lower speed of cycle has been introduced, but this deteriorates the washing capacity. Under this background, we propose active noise control for dishwasher noise. It is observed that the noise is propagating mainly from the lower part of the front side. Control speakers are placed in the part for the collocation. Observation part of estimating sound field distribution and control part of generating the anti-noise are designed for active noise control. Simulation result shows proposed active noise control scheme could have a potential application for dishwasher noise reduction.
Development of Seasonal ARIMA Models for Traffic Noise Forecasting
Directory of Open Access Journals (Sweden)
Guarnaccia Claudio
2017-01-01
Full Text Available In this paper, a time series analysis approach is adopted to monitor and predict a traffic noise levels dataset, measured in a site of Messina, Italy. In general, acoustical noise shows a high prediction complexity, since its slope is strongly related to the variability of the sources and to intrinsic randomness. In the analysed site the predominant source is road traffic, that has a periodic and non-stationary behaviour. The study of the time evolution of this hazardous agent is very useful to assess the impact to human health and activities. The time series models adopted in this paper are of the stochastic seasonal ARIMA class; these types of model are based on the strong periodicity registered in the acoustical equivalent levels. The observed periodicity is related to the highly variability of urban traffic in the different days of the week. Three different seasonal ARIMA models are proposed and calibrated on a rich dataset of 800 sound level measurements. The predictive capabilities of these techniques are encouraging. The implemented models show a good forecasting performances in terms of low residuals, i.e. difference between observed and estimated noise values. The residuals are analysed by means of statistical indexes, plots and tests.
International Nuclear Information System (INIS)
Dobrev, V.K.
1986-11-01
Let G be a real linear connected semisimple Lie group. We present a canonical construction of the differential operators intertwining elementary (≡ generalized principal series) representations of G. The results are easily extended to real linear reductive Lie groups. (author). 20 refs
A low-noise, wideband, integrated CMOS transimpedance preamplifier for photodiode applications
International Nuclear Information System (INIS)
Binkley, D.M.; Paulus, M.J.; Casey, M.E.; Rochelle, J.M.
1992-01-01
In this paper, a low-noise, wideband, integrated CMOS transimpedance preamplifier is presented for silicon avalanche photodiode (APD) applications. The preamplifier, fabricated in a standard 2μ CMOS technology, features a transimpedance gain of 45 kΩ, a risetime of 22 ns, a series noise of 1.6nV/Hz 1/2 , and a wideband equivalent input-noise current of 12 nA for a source capacitance of 12 pF. The measured 22 Na timing resolution of 9.2-ns FWHM and energy resolution of 22.4% FWHM for the RCA C30994 BGO/APD detector module coupled to the preamplifier is comparable to the performance reported using charge-sensitive preamplifiers. This illustrates that transimpedance preamplifiers should be considered for APD applications, especially where APD noise current dominates noise from feedback resistors in the 1--kΩ to 50-kΩ range
Model of geophysical fields representation in problems of complex correlation-extreme navigation
Directory of Open Access Journals (Sweden)
Volodymyr KHARCHENKO
2015-09-01
Full Text Available A model of the optimal representation of spatial data for the task of complex correlation-extreme navigation is developed based on the criterion of minimum deviation of the correlation functions of the original and the resulting fields. Calculations are presented for one-dimensional case using the approximation of the correlation function by Fourier series. It is shown that in the presence of different geophysical map data fields their representation is possible by single template with optimal sampling without distorting the form of the correlation functions.
Representation and alignment of sung queries for music information retrieval
Adams, Norman H.; Wakefield, Gregory H.
2005-09-01
The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.
Locating noise sources with a microphone array
International Nuclear Information System (INIS)
Bale, A.; Johnson, D.
2010-01-01
Noise pollution is one of the contributors to the public opposition of wind farms. Most of the noise produced by turbines is caused by the aerodynamic interactions between the turbine blades and the surrounding air. This poster presentation discussed a series of aeroacoustic tests conducted to account for the different in vortical structures caused by the rotation of the blades. Microphone arrays were used measure and locate the source of noise. A beam forming technique was used to measure the noise using an algorithm that identified a scanning grid on a plane where the source was thought to be located. It delayed each microphone's signal by the length of time required for the sound to travel from the scan position to each microphone, and accounted for the amplitudes according to the distance from the scan position to each microphone. Demonstration test cases were conducted using piezo buzzers attached to aluminum bars and mounted to the shaft of a DC motor that produced a rotational diameter of 0.95 meter. The buzzers were placed 1 meter from the array. Multiple sound sources at the same frequency were identified, and the moving sources were accurately measured and located. tabs., figs.
Representation of coherent states in many-boson theory
International Nuclear Information System (INIS)
Vakarchuk, I.A.
1978-01-01
Solution of the Bloch equation for the density matrix of the system of interacting Bose particles in the coherent states representation is obtained. The matrix of the thermodynamical potential functional is represented in the form of the functional series over the eigen-values of the annihilation operator and the coefficient functions are the matrix elements of cluster operators. A simple functional integration in the partition sum leads to the well-known quantum virial expansions and the standard perturbation theory series. Possibilities of application of the expressions obtained to the investigation of the lambda-transition in the liquid He 4 and the generalization to the case of the many-fermion system is discussed
Thompson, Elaine C.; Carr, Kali Woodruff; White-Schwoch, Travis; Otto-Meyer, Sebastian; Kraus, Nina
2016-01-01
From bustling classrooms to unruly lunchrooms, school settings are noisy. To learn effectively in the unwelcome company of numerous distractions, children must clearly perceive speech in noise. In older children and adults, speech-in-noise perception is supported by sensory and cognitive processes, but the correlates underlying this critical listening skill in young children (3–5 year olds) remain undetermined. Employing a longitudinal design (two evaluations separated by ~12 months), we followed a cohort of 59 preschoolers, ages 3.0–4.9, assessing word-in-noise perception, cognitive abilities (intelligence, short-term memory, attention), and neural responses to speech. Results reveal changes in word-in-noise perception parallel changes in processing of the fundamental frequency (F0), an acoustic cue known for playing a role central to speaker identification and auditory scene analysis. Four unique developmental trajectories (speech-in-noise perception groups) confirm this relationship, in that improvements and declines in word-in-noise perception couple with enhancements and diminishments of F0 encoding, respectively. Improvements in word-in-noise perception also pair with gains in attention. Word-in-noise perception does not relate to strength of neural harmonic representation or short-term memory. These findings reinforce previously-reported roles of F0 and attention in hearing speech in noise in older children and adults, and extend this relationship to preschool children. PMID:27864051
Detection of "noisy" chaos in a time series
DEFF Research Database (Denmark)
Chon, K H; Kanters, J K; Cohen, R J
1997-01-01
Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both...
Yang, Sejung; Lee, Byung-Uk
2015-01-01
In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138
Directory of Open Access Journals (Sweden)
William L Schuerman
Full Text Available In different tasks involving action perception, performance has been found to be facilitated when the presented stimuli were produced by the participants themselves rather than by another participant. These results suggest that the same mental representations are accessed during both production and perception. However, with regard to spoken word perception, evidence also suggests that listeners' representations for speech reflect the input from their surrounding linguistic community rather than their own idiosyncratic productions. Furthermore, speech perception is heavily influenced by indexical cues that may lead listeners to frame their interpretations of incoming speech signals with regard to speaker identity. In order to determine whether word recognition evinces similar self-advantages as found in action perception, it was necessary to eliminate indexical cues from the speech signal. We therefore asked participants to identify noise-vocoded versions of Dutch words that were based on either their own recordings or those of a statistically average speaker. The majority of participants were more accurate for the average speaker than for themselves, even after taking into account differences in intelligibility. These results suggest that the speech representations accessed during perception of noise-vocoded speech are more reflective of the input of the speech community, and hence that speech perception is not necessarily based on representations of one's own speech.
Directory of Open Access Journals (Sweden)
C. H. López-Caraballo
2015-01-01
Full Text Available An artificial neural network (ANN based on particle swarm optimization (PSO was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term xt+6. The performance prediction was evaluated and compared with other studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO in order to obtain a new estimator of the predictions, which also allowed us to compute the uncertainties of predictions for noisy Mackey-Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level σN from 0.01 to 0.1.
Chen, Yong-fei; Gao, Hong-xia; Wu, Zi-ling; Kang, Hui
2018-01-01
Compressed sensing (CS) has achieved great success in single noise removal. However, it cannot restore the images contaminated with mixed noise efficiently. This paper introduces nonlocal similarity and cosparsity inspired by compressed sensing to overcome the difficulties in mixed noise removal, in which nonlocal similarity explores the signal sparsity from similar patches, and cosparsity assumes that the signal is sparse after a possibly redundant transform. Meanwhile, an adaptive scheme is designed to keep the balance between mixed noise removal and detail preservation based on local variance. Finally, IRLSM and RACoSaMP are adopted to solve the objective function. Experimental results demonstrate that the proposed method is superior to conventional CS methods, like K-SVD and state-of-art method nonlocally centralized sparse representation (NCSR), in terms of both visual results and quantitative measures.
Energy Technology Data Exchange (ETDEWEB)
Gattringer, Christof, E-mail: christof.gattringer@uni-graz.at; Marchis, Carlotta, E-mail: carla.marchis@uni-graz.at
2017-03-15
We propose a new approach to strong coupling series and dual representations for non-abelian lattice gauge theories using the SU(2) case as an example. The Wilson gauge action is written as a sum over “abelian color cycles” (ACC) which correspond to loops in color space around plaquettes. The ACCs are complex numbers which can be commuted freely such that the strong coupling series and the dual representation can be obtained as in the abelian case. Using a suitable representation of the SU(2) gauge variables we integrate out all original gauge links and identify the constraints for the dual variables in the SU(2) case. We show that the construction can be generalized to the case of SU(2) gauge fields with staggered fermions. The result is a strong coupling series where all gauge integrals are known in closed form and we discuss its applicability for possible dual simulations. The abelian color cycle concept can be generalized to other non-abelian gauge groups such as SU(3).
Matsuoka, A J; Abbas, P J; Rubinstein, J T; Miller, C A
2000-11-01
Experimental results from humans and animals show that electrically evoked compound action potential (EAP) responses to constant-amplitude pulse train stimulation can demonstrate an alternating pattern, due to the combined effects of highly synchronized responses to electrical stimulation and refractory effects (Wilson et al., 1994). One way to improve signal representation is to reduce the level of across-fiber synchrony and hence, the level of the amplitude alternation. To accomplish this goal, we have examined EAP responses in the presence of Gaussian noise added to the pulse train stimulus. Addition of Gaussian noise at a level approximately -30 dB relative to EAP threshold to the pulse trains decreased the amount of alternation, indicating that stochastic resonance may be induced in the auditory nerve. The use of some type of conditioning stimulus such as Gaussian noise may provide a more 'normal' neural response pattern.
Tests for nonlinearity in short stationary time series
International Nuclear Information System (INIS)
Chang, T.; Sauer, T.; Schiff, S.J.
1995-01-01
To compare direct tests for detecting determinism in chaotic time series, data from Henon, Lorenz, and Mackey--Glass equations were contaminated with various levels of additive colored noise. These data were analyzed with a variety of recently developed tests for determinism, and the results compared
Impact of non-white noises in pulse amplitude measurements: a time-domain approach
International Nuclear Information System (INIS)
Pullia, A.
1998-01-01
The contribution of the 1/f-noise to the spectral line broadening in pulse amplitude measurements is derived with a time-domain analysis. The known time-domain relationships which provide the contributions of the series and parallel white noises are generalised for the case of 1/f and other typical non-white noises, by using the fractional derivative of either the system impulse response (time-invariant linear filters) or its weight function folded (time-variant linear filters). It is shown that a time-domain approach is also effective to determine the contribution of Lorentzian noises. A simple rule suitable to derive numerically the fractional derivative is given, which permits to calculate the effect of non-white noises even when the filter impulse response is not known analytically but only in sampled form. (orig.)
International Nuclear Information System (INIS)
Almeida Ferreira, A.C. de.
1984-01-01
For problems with azimuthal symmetry in velocity space, the distribution function depends only on the speed and on the pitch angle. The angular dependence of the distribution function is expanded in Legendre polynomials, and the expansions of the collision integrals describing two-body Coulomb interactions in a plasma are determined through the use of the Rosenbluth potentials. The electron distribution function is written as a Maxwellian plus a deviation, and the representation in Legendre polynomials of the electron-electron collision term is given for both its linear and nonlinear part. To determine the representation of the electron-ion collision term it is assumed that the ion distribution is much narrower in velocity space than the electron distribution, and shifted from the origin by a flow velocity. The equations are presented in a form that is suitable for their use in a computer. (Author) [pt
ARMA modelling of neutron stochastic processes with large measurement noise
International Nuclear Information System (INIS)
Zavaljevski, N.; Kostic, Lj.; Pesic, M.
1994-01-01
An autoregressive moving average (ARMA) model of the neutron fluctuations with large measurement noise is derived from langevin stochastic equations and validated using time series data obtained during prompt neutron decay constant measurements at the zero power reactor RB in Vinca. Model parameters are estimated using the maximum likelihood (ML) off-line algorithm and an adaptive pole estimation algorithm based on the recursive prediction error method (RPE). The results show that subcriticality can be determined from real data with high measurement noise using much shorter statistical sample than in standard methods. (author)
Preparation of Ultracold Atom Clouds at the Shot Noise Level
DEFF Research Database (Denmark)
Gajdacz, M.; Hilliard, A. J.; Kristensen, Mick
2016-01-01
We prepare number stabilized ultracold atom clouds through the real-time analysis of nondestructive images and the application of feedback. In our experiments, the atom number N∼10^6 is determined by high precision Faraday imaging with uncertainty ΔN below the shot noise level, i.e., ΔN... on this measurement, feedback is applied to reduce the atom number to a user-defined target, whereupon a second imaging series probes the number stabilized cloud. By this method, we show that the atom number in ultracold clouds can be prepared below the shot noise level....
a Universal De-Noising Algorithm for Ground-Based LIDAR Signal
Ma, Xin; Xiang, Chengzhi; Gong, Wei
2016-06-01
Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.
Advanced supersonic propulsion study. [with emphasis on noise level reduction
Sabatella, J. A. (Editor)
1974-01-01
A study was conducted to determine the promising propulsion systems for advanced supersonic transport application, and to identify the critical propulsion technology requirements. It is shown that noise constraints have a major effect on the selection of the various engine types and cycle parameters. Several promising advanced propulsion systems were identified which show the potential of achieving lower levels of sideline jet noise than the first generation supersonic transport systems. The non-afterburning turbojet engine, utilizing a very high level of jet suppression, shows the potential to achieve FAR 36 noise level. The duct-heating turbofan with a low level of jet suppression is the most attractive engine for noise levels from FAR 36 to FAR 36 minus 5 EPNdb, and some series/parallel variable cycle engines show the potential of achieving noise levels down to FAR 36 minus 10 EPNdb with moderate additional penalty. The study also shows that an advanced supersonic commercial transport would benefit appreciably from advanced propulsion technology. The critical propulsion technology needed for a viable supersonic propulsion system, and the required specific propulsion technology programs are outlined.
Automated system for equivalent noise charge measurements from 10 ns to 10 μs
International Nuclear Information System (INIS)
La Taille, C. de.
1992-07-01
Noise measurements versus filter time constant constitute a very powerful method to investigate series, parallel and 1/f noise contributions in front end electronics. Usually performed with a set of filters and a multichannel analyser, they are tedious and often limited to values greater than 100 ns. A very low noise bipolar filter is described whose time constant can be selected via GPIB bus from 10 ns to 10 μs in 10 steps. The data are transferred from a digital scope to a computer which generates a baseline histogram and determines the overall gain. The Equivalent Noise Charge is then calculated for each time constant and a fit to the results determines the various noise parameters. (author) 13 refs., 10 figs., 1 tab
Validation of the CQU-DTU-LN1 series of airfoils
DEFF Research Database (Denmark)
Shen, Wen Zhong; Zhu, Wei Jun; Fischer, Andreas
2014-01-01
The CQU-DTU-LN1 series of airfoils were designed with an objective of high lift and low noise emission. In the design process, the aerodynamic performance is obtained using XFOIL while noise emission is obtained with the BPM model. In this paper we present some validations of the designed CQU......, the designed Cl and Cl/Cd agrees well with the experiment and are in general higher than those of the NACA airfoil. For the acoustic features, the noise emission of the LN118 airfoil is compared with the acoustic measurements and that of the NACA airfoil. Comparisons show that the BPM model can predict...
Representational contents of domestic violence against women among nursing students
Directory of Open Access Journals (Sweden)
Camila Daiane Silva
2016-12-01
Full Text Available This study aimed to analyze the representational contents of domestic violence against women among nursing students. This is a qualitative research, based on the Theory of Social Representations. We collected the data from August to November/2014 by semi-structured interviews, analyzed by software. Thirty-three students participated, 16 from the initial grades and 17 from the final grades. We identified two categories: representational content acquired in the pre-university and university years. The initial grades listed high school, cases with family members and colleagues. Among the final grades, knowledge was acquired during academic weeks, research groups, practical activities, and internships. The knowledge of common sense is constant, especially between the students of initial grades and the reified, between the final series. The actions of the future professional life can base on personal experiences, reified common sense knowledge, and practical knowledge generated during graduation. It highlights the impact on training to provide assistance to women/persons in situations of violence.
Directory of Open Access Journals (Sweden)
Sabine A. Janssen
2011-05-01
Full Text Available In environmental noise control one commonly employs the A-weighted sound level as an approximate measure of the effect of noise on people. A measure that is more closely related to direct human perception of noise is the loudness level. At constant A-weighted sound level, the loudness level of a noise signal varies considerably with the shape of the frequency spectrum of the noise signal. In particular the bandwidth of the spectrum has a large effect on the loudness level, due to the effect of critical bands in the human hearing system. The low-frequency content of the spectrum also has an effect on the loudness level. In this note the relation between loudness level and A-weighted sound level is analyzed for various environmental noise spectra, including spectra of traffic noise, aircraft noise, and industrial noise. From loudness levels calculated for these environmental noise spectra, diagrams are constructed that show the relation between loudness level, A‑weighted sound level, and shape of the spectrum. The diagrams show that the upper limits of the loudness level for broadband environmental noise spectra are about 20 to 40 phon higher than the lower limits for narrowband spectra, which correspond to the loudness levels of pure tones. The diagrams are useful for assessing limitations and potential improvements of environmental noise control methods and policy based on A-weighted sound levels.
Contemporary theories of 1/f noise in motor control
Diniz, A.; Wijnants, M.L.; Torre, K.; Barreiros, J.; Crato, N.; Bosman, A.M.T.; Hasselman, F.W.; Cox, R.F.A.; Orden, G.C. van; Delignieres, D.
2011-01-01
1/f noise has been discovered in a number of time series collected in psychological and behavioral experiments. This ubiquitous phenomenon has been ignored for a long time and classical models were not designed for accounting for these long-range correlations. The aim of this paper is to present and
Low frequency noise as a control test for spacial solar panels
Orsal, B.; Alabedra, R.; Ruas, R.
1986-07-01
The present study of low frequency noise in a forward-biased dark solar cell, in order to develop an NDE test method for solar panels, notes that a single cell with a given defect is thus detectable under dark conditions. The test subject was a space solar panel consisting of five cells in parallel and five in series; these cells are of the n(+)-p monocrystalline Si junction type. It is demonstrated that the noise associated with the defective cell is 10-15 times higher than that of a good cell. Replacement of a good cell by a defective one leads to a 30-percent increase in the noise level of the panel as a whole.
Using Disks as Models for Proofs of Series
Somchaipeng, Tongta; Kruatong, Tussatrin; Panijpan, Bhinyo
2012-01-01
Exploring and deriving proofs of closed-form expressions for series can be fun for students. However, for some students, a physical representation of such problems is more meaningful. Various approaches have been designed to help students visualize squares of sums and sums of squares; these approaches may be arithmetic-algebraic or combinatorial…
Characterizing time series: when Granger causality triggers complex networks
Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong
2012-08-01
In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.
Characterizing time series: when Granger causality triggers complex networks
International Nuclear Information System (INIS)
Ge Tian; Cui Yindong; Lin Wei; Liu Chong; Kurths, Jürgen
2012-01-01
In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length. (paper)
SensL B-Series and C-Series silicon photomultipliers for time-of-flight positron emission tomography
Energy Technology Data Exchange (ETDEWEB)
O' Neill, K., E-mail: koneill@sensl.com; Jackson, C., E-mail: cjackson@sensl.com
2015-07-01
Silicon photomultipliers from SensL are designed for high performance, uniformity and low cost. They demonstrate peak photon detection efficiency of 41% at 420 nm, which is matched to the output spectrum of cerium doped lutetium orthosilicate. Coincidence resolving time of less than 220 ps is demonstrated. New process improvements have lead to the development of C-Series SiPM which reduces the dark noise by over an order of magnitude. In this paper we will show characterization test results which include photon detection efficiency, dark count rate, crosstalk probability, afterpulse probability and coincidence resolving time comparing B-Series to the newest pre-production C-Series. Additionally we will discuss the effect of silicon photomultiplier microcell size on coincidence resolving time allowing the optimal microcell size choice to be made for time of flight positron emission tomography systems.
Hilton, D. A.; Bruton, D.
1977-01-01
Results of a series of noise measurements that were made under controlled conditions during the static firing of two Nike solid propellant rocket motors are presented. The usefulness of these motors as sources for general spacecraft noise testing was assessed, and the noise expected in the cargo bay of the orbiter was reproduced. Brief descriptions of the Nike motor, the general procedures utilized for the noise tests, and representative noise data including overall sound pressure levels, one third octave band spectra, and octave band spectra were reviewed. Data are presented on two motors of different ages in order to show the similarity between noise measurements made on motors having different loading dates. The measured noise from these tests is then compared to that estimated for the space shuttle orbiter cargo bay.
Orbital Noise of the Earth Causes Intensity Fluctuation in the Geomagnetic Field
Liu, Han-Shou; Kolenkiewicz, R.; Wade, C., Jr.
2003-01-01
Orbital noise of Earth's obliquity can provide an insight into the core of the Earth that causes intensity fluctuations in the geomagnetic field. Here we show that noise spectrum of the obliquity frequency have revealed a series of frequency periods centered at 250-, 1OO-, 50-, 41-, 30-, and 26-kyr which are almost identical with the observed spectral peaks from the composite curve of 33 records of relative paleointensity spanning the past 800 kyr (Sint-800 data). A continuous record for the past two million years also reveals the presence of the major 100 kyr periodicity in obliquity noise and geomagnetic intensity fluctuations. These results of correlation suggest that obliquity noise may power the dynamo, located in the liquid outer core of the Earth, which generates the geomagnetic field.
The use of synthetic input sequences in time series modeling
International Nuclear Information System (INIS)
Oliveira, Dair Jose de; Letellier, Christophe; Gomes, Murilo E.D.; Aguirre, Luis A.
2008-01-01
In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure
Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure.
Birk, Matthias; Ivina, Olga; von Klot, Stephanie; Babisch, Wolfgang; Heinrich, Joachim
2011-11-01
self-reported road traffic noise annoyance is commonly used in epidemiological studies for assessment of potential health effects. Alternatively, some studies have used geographic information system (GIS) modelled exposure to road traffic noise as an objective parameter. The aim of this study was to analyse the association between noise exposure due to neighbouring road traffic and the noise annoyance of adults, taking other determinants into consideration. parents of 951 Munich children from the two German birth cohorts GINIplus and LISAplus reported their annoyance due to road traffic noise at home. GIS modelled road traffic noise exposure (L(den), maximum within a 50 m buffer) from the noise map of the city of Munich was available for all families. GIS-based calculated distance to the closest major road (≥10,000 vehicles per day) and questionnaire based-information about family income, parental education and the type of the street of residence were explored for their potential influence. An ordered logit regression model was applied. The noise levels (L(den)) and the reported noise annoyance were compared with an established exposure-response function. the correlation between noise annoyance and noise exposure (L(den)) was fair (Spearman correlation r(s) = 0.37). The distance to a major road and the type of street were strong predictors for the noise annoyance. The annoyance modelled by the established exposure-response function and that estimated by the ordered logit model were moderately associated (Pearson's correlation r(p) = 0.50). road traffic noise annoyance was associated with GIS modelled neighbouring road traffic noise exposure (L(den)). The distance to a major road and the type of street were additional explanatory factors of the noise annoyance appraisal.
Judgments of aircraft noise in a traffic noise background
Powell, C. A.; Rice, C. G.
1975-01-01
An investigation was conducted to determine subjective response to aircraft noise in different road traffic backgrounds. In addition, two laboratory techniques for presenting the aircraft noise with the background noise were evaluated. For one technique, the background noise was continuous over an entire test session; for the other, the background noise level was changed with each aircraft noise during a session. Subjective response to aircraft noise was found to decrease with increasing background noise level, for a range of typical indoor noise levels. Subjective response was found to be highly correlated with the Noise Pollution Level (NPL) measurement scale.
Fractional Gaussian noise: Prior specification and model comparison
Sørbye, Sigrunn Holbek
2017-07-07
Fractional Gaussian noise (fGn) is a stationary stochastic process used to model antipersistent or persistent dependency structures in observed time series. Properties of the autocovariance function of fGn are characterised by the Hurst exponent (H), which, in Bayesian contexts, typically has been assigned a uniform prior on the unit interval. This paper argues why a uniform prior is unreasonable and introduces the use of a penalised complexity (PC) prior for H. The PC prior is computed to penalise divergence from the special case of white noise and is invariant to reparameterisations. An immediate advantage is that the exact same prior can be used for the autocorrelation coefficient ϕ(symbol) of a first-order autoregressive process AR(1), as this model also reflects a flexible version of white noise. Within the general setting of latent Gaussian models, this allows us to compare an fGn model component with AR(1) using Bayes factors, avoiding the confounding effects of prior choices for the two hyperparameters H and ϕ(symbol). Among others, this is useful in climate regression models where inference for underlying linear or smooth trends depends heavily on the assumed noise model.
Fractional Gaussian noise: Prior specification and model comparison
Sø rbye, Sigrunn Holbek; Rue, Haavard
2017-01-01
Fractional Gaussian noise (fGn) is a stationary stochastic process used to model antipersistent or persistent dependency structures in observed time series. Properties of the autocovariance function of fGn are characterised by the Hurst exponent (H), which, in Bayesian contexts, typically has been assigned a uniform prior on the unit interval. This paper argues why a uniform prior is unreasonable and introduces the use of a penalised complexity (PC) prior for H. The PC prior is computed to penalise divergence from the special case of white noise and is invariant to reparameterisations. An immediate advantage is that the exact same prior can be used for the autocorrelation coefficient ϕ(symbol) of a first-order autoregressive process AR(1), as this model also reflects a flexible version of white noise. Within the general setting of latent Gaussian models, this allows us to compare an fGn model component with AR(1) using Bayes factors, avoiding the confounding effects of prior choices for the two hyperparameters H and ϕ(symbol). Among others, this is useful in climate regression models where inference for underlying linear or smooth trends depends heavily on the assumed noise model.
International Nuclear Information System (INIS)
Deenen, J.; Quesne, C.
1985-01-01
Both non-Hermitian Dyson and Hermitian Holstein--Primakoff representations of the Sp(2d,R) algebra are obtained when the latter is restricted to a positive discrete series irreducible representation 1 +n/2>. For such purposes, some results for boson representations, recently deduced from a study of the Sp(2d,R) partially coherent states, are combined with some standard techniques of boson expansion theories. The introduction of Usui operators enables the establishment of useful relations between the various boson representations. Two Dyson representations of the Sp(2d,R) algebra are obtained in compact form in terms of ν = d(d+1)/2 pairs of boson creation and annihilation operators, and of an extra U(d) spin, characterized by the irreducible representation [lambda 1 xxxlambda/sub d/]. In contrast to what happens when lambda 1 = xxx = lambda/sub d/ = lambda, it is shown that the Holstein--Primakoff representation of the Sp(2d,R) algebra cannot be written in such a compact form for a generic irreducible representation. Explicit expansions are, however, obtained by extending the Marumori, Yamamura, and Tokunaga method of boson expansion theories. The Holstein--Primakoff representation is then used to prove that, when restricted to the Sp(2d,R) irreducible representation 1 +n/2>, the dn-dimensional harmonic oscillator Hamiltonian has a U(ν) x SU(d) symmetry group
Explaining Infinite Series--An Exploration of Students' Images
Champney, Danielle Dawn
2013-01-01
This study uses self-generated representations (SGR)--images produced in the act of explaining--as a means of uncovering what university calculus students understand about infinite series convergence. It makes use of student teaching episodes, in which students were asked to explain to a peer what that student might have missed had they been…
Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring.
Everss-Villalba, Estrella; Melgarejo-Meseguer, Francisco Manuel; Blanco-Velasco, Manuel; Gimeno-Blanes, Francisco Javier; Sala-Pla, Salvador; Rojo-Álvarez, José Luis; García-Alberola, Arcadi
2017-10-25
Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported
Scale-dependent intrinsic entropies of complex time series.
Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E
2016-04-13
Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).
Design and validation of the high performance and low noise CQU-DTU-LN1 airfoils
DEFF Research Database (Denmark)
Cheng, Jiangtao; Zhu, Wei Jun; Fischer, Andreas
2014-01-01
with the blade element momentum theory, the viscous-inviscid XFOIL code and an airfoil self-noise prediction model, an optimization algorithm has been developed for designing the high performance and low noise CQU-DTU-LN1 series of airfoils with targets of maximum power coefficient and low noise emission...... emission between the CQU-DTU-LN118 airfoil and the National Advisory Committee for Aeronautics (NACA) 64618 airfoil, which is used in modern wind turbine blades, are carried out. Copyright © 2013 John Wiley & Sons, Ltd....
Representations of Nature of Science in Selected Histories of Science in
Wei, Bing; Li, Yue; Chen, Bo
2013-01-01
This study aimed to examine the representations of nature of science (NOS) in the eight histories of science selected from three series of integrated science textbooks used in junior high school in China. Ten aspects of NOS were adopted in the analytical framework. It was found that NOS had not been well treated in the selected histories of…
Sensitivity of PPI analysis to differences in noise reduction strategies.
Barton, M; Marecek, R; Rektor, I; Filip, P; Janousova, E; Mikl, M
2015-09-30
In some fields of fMRI data analysis, using correct methods for dealing with noise is crucial for achieving meaningful results. This paper provides a quantitative assessment of the effects of different preprocessing and noise filtering strategies on psychophysiological interactions (PPI) methods for analyzing fMRI data where noise management has not yet been established. Both real and simulated fMRI data were used to assess these effects. Four regions of interest (ROIs) were chosen for the PPI analysis on the basis of their engagement during two tasks. PPI analysis was performed for 32 different preprocessing and analysis settings, which included data filtering with RETROICOR or no such filtering; different filtering of the ROI "seed" signal with a nuisance data-driven time series; and the involvement of these data-driven time series in the subsequent PPI GLM analysis. The extent of the statistically significant results was quantified at the group level using simple descriptive statistics. Simulated data were generated to assess statistical improvement of different filtering strategies. We observed that different approaches for dealing with noise in PPI analysis yield differing results in real data. In simulated data, we found RETROICOR, seed signal filtering and the addition of data-driven covariates to the PPI design matrix significantly improves results. We recommend the use of RETROICOR, and data-driven filtering of the whole data, or alternatively, seed signal filtering with data-driven signals and the addition of data-driven covariates to the PPI design matrix. Copyright © 2015 Elsevier B.V. All rights reserved.
Harikrishnan, K. P.; Misra, R.; Ambika, G.
2009-09-01
We show that the combined use of correlation dimension (D2) and correlation entropy (K2) as discriminating measures can extract a more accurate information regarding the different types of noise present in a time series data. For this, we make use of an algorithmic approach for computing D2 and K2 proposed by us recently [Harikrishnan KP, Misra R, Ambika G, Kembhavi AK. Physica D 2006;215:137; Harikrishnan KP, Ambika G, Misra R. Mod Phys Lett B 2007;21:129; Harikrishnan KP, Misra R, Ambika G. Pramana - J Phys, in press], which is a modification of the standard Grassberger-Proccacia scheme. While the presence of white noise can be easily identified by computing D2 of data and surrogates, K2 is a better discriminating measure to detect colored noise in the data. Analysis of time series from a real world system involving both white and colored noise is presented as evidence. To our knowledge, this is the first time that such a combined analysis is undertaken on a real world data.
International Nuclear Information System (INIS)
Stan, Cristina; Cristescu, Cristina Maria; Alexandroaei, D.; Cristescu, C.P.
2014-01-01
Highlights: •We study the white Gaussian noise effect on the fractality of plasma fluctuations. •Multifractality strength is increased by the noise, at all inter-anode voltages. •New positive influence of noise resulting in an increasing of the predictability. •Identifying the fluctuations nature: chaotic or stochastic by multifractal analysis. •Noise changes the position of the maximum in the singularity spectra. - Abstract: In this work we investigate the influence of white Gaussian noise on the fluctuations in the plasma of a symmetrical discharge using multifractal detrended fluctuation analysis. We observe that in the range of noise intensity used in our study, the multifractality strength is increased by the noise, at all values of the inter-anode voltage, both for original and filtered time-series. This is interpreted as a new positive influence of noise because this effect can be understood as an increasing in the predictability on the dynamics in a time-series. A constructive influence of noise can appear only for fluctuations with underlying chaotic dynamics. The shuffling analysis demonstrates that the multifractality is purely a consequence of the correlations of the fluctuations. The noise influence is also observed in the change of the position of the maximum in the singularity spectra. The multifractal detrended cross correlation between light intensity and current intensity demonstrates that the fluctuations in both parameters are generated by the same physical processes though they are very different in nature: one is a local parameter and the other is a global one
Measurement of the effect of an oil additive on vibration, noise and smokiness
International Nuclear Information System (INIS)
Dimitrovski, M.
1999-01-01
The contents of this article provides a analysis of vibration, noise and smokiness in compression ignition engines. Further explanation has been given on types of lubrication and oils with their characteristic. Series of experiments has been conducted on vibration. Noise and smokiness before and after adding additive. Presentation has been given of data obtained from examination of the vehicle. At the end comparison of data analysis and conclusion has been done. (Author)
Reduction of Impact Noise of Trams on a Major Bridge
Dittrich, M.G.; Bosshaart, C.; Wessels, P.W.
2015-01-01
As part of a recent renovation of the Erasmus bridge in Rotterdam, improvements were made to reduce impact noise caused by trams passing a series of rai! joints. The bridge inciudes several different sections inciuding a bascule bridge and is in an inner city tocation with new adjacent apartment
Energy Technology Data Exchange (ETDEWEB)
Kirkove, M.; Seret, A. [Liege Univ., Imagerie Medicale Experimentale, Institut de Physique (Belgium)
2007-05-15
Scintigraphic images are strongly affected by Poisson noise. This article presents the results of a comparison between de-noising methods for Poisson noise according to different criteria: the gain in signal-to-noise ratio, the preservation of resolution and contrast. and the visual quality. The wavelet techniques recently developed to de-noise Poisson noise limited images are divided into two groups based on: (1) the Haar representation. 1 (2) the transformation of Poisson noise into white Gaussian noise by the Haar-Fisz transform followed by a de-noising. In this study, three variants of the first group and three variants of the second. including the adaptative Wiener filter, four types of wavelet thresholding and the Bayesian method of Pizurica were compared to Metz and Hanning filters and to Shine, a systematic noise elimination process. All these methods, except Shine, are parametric. For each of them, ranges of optimal values for the parameters were highlighted as a function of the aforementioned criteria. The intersection of ranges for the wavelet methods without thresholding was empty, and these methods were therefore not further compared quantitatively. The thresholding techniques and Shine gave the best results in resolution and contrast. The largest improvement in signal-to-noise ratio was obtained by the filters. Ideally, these filters should be accurately defined for each image. This is difficult in the clinical context. Moreover. they generate oscillation artefacts. In addition, the wavelet techniques did not bring significant improvements, and are rather slow. Therefore, Shine, which is fast and works automatically, appears to be an interesting alternative. (authors)
Continuous spatial representations in the olfactory bulb may reflect perceptual categories
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Benjamin eAuffarth
2011-10-01
Full Text Available In sensory processing of odors, the olfactory bulb is an important relay station, where odor representations are noise-filtered, sharpened, and possibly re-organized. An organization by perceptual qualities has been found previously in the piriform cortex, however several recent studies indicate that the olfactory bulb code reflects behaviorally relevant dimensions spatially as well as at the population level. We apply a statistical analysis on 2-deoxyglucose images, taken over the entire bulb of glomerular layer of the rat, in order to see how the recognition of odors in the nose is translated into a map of odor quality in the brain. We first confirm previous studies that the first principal component could be related to pleasantness, however the next higher principal components are not directly clear. We then find mostly continuous spatial representations for perceptual categories. We compare the space spanned by spatial and population codes to human reports of perceptual similarity between odors and our results suggest that perceptual categories could be already embedded in glomerular activations and that spatial representations give a better match than population codes. This suggests that human and rat perceptual dimensions of odorant coding are related and indicates that perceptual qualities could be represented as continuous spatial codes of the olfactory bulb glomerulus population.
Taylor series maps and their domain of convergence
International Nuclear Information System (INIS)
Abell, D.T.; Dragt, A.J.
1992-01-01
This paper tries to make clear what limits the validity of a Taylor series map, and how. We describe the concept of a transfer map and quote some theorems that justify not only their existence but also their advantages. Then, we describe the Taylor series representation for transfer maps. Following that, we attempt to elucidate some of the basic theorems from the theory of functions of one and several complex variables. This material forms the core of our understanding of what limits the domain of convergence of Taylor series maps. Lastly, we use the concrete example of a simple anharmonic oscillator to illustrate how the theorems from several complex variable theory affect the domain convergence of Taylor series maps. There we describe the singularities of the anharmonic oscillator in the complex planes of the initial conditions, show how they constrain our use of a Taylor series map, and then discuss our findings
High-frequency signal and noise estimates of CSR GRACE RL04
Bonin, Jennifer A.; Bettadpur, Srinivas; Tapley, Byron D.
2012-12-01
A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04's poor ability to accurately and reliably measure hydrological signal above 3-9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.
The quantitative representation of fiber-and sheet-texture in metals of cubic system
International Nuclear Information System (INIS)
Kim, H.J.; Kim, S.C.; Chun, B.C.; Lee, C.Y.
1983-01-01
This is the first article of a series dealing with studies on the quantitative representation of fiber-and sheet-type textures in metals of cubic crystal system. Texture measurements by neutron diffraction method are analyzed using Bunge's series expansion method and the effect of series truncation is studied for samples of various texture sharpness. The present article describes two computer programs, TXFIB and TXSHT, develped for the analysis of the respective fiber-and sheet-type texture. Using these computer programs, the orientation distribution function can be expanded in the series of generalized spherical harmonics up to 58th term from 6 experimental pole figures as input. Estimations of various errors involved in the texture analysis and texture sharpness index are also included in the programs. (Author)
Directory of Open Access Journals (Sweden)
Mohamed Yaseen Jabarulla
2018-05-01
Full Text Available Ultrasound images are corrupted with multiplicative noise known as speckle, which reduces the effectiveness of image processing and hampers interpretation. This paper proposes a multiplicative speckle suppression technique for ultrasound liver images, based on a new signal reconstruction model known as sparse representation (SR over dictionary learning. In the proposed technique, the non-uniform multiplicative signal is first converted into additive noise using an enhanced homomorphic filter. This is followed by pixel-based total variation (TV regularization and patch-based SR over a dictionary trained using K-singular value decomposition (KSVD. Finally, the split Bregman algorithm is used to solve the optimization problem and estimate the de-speckled image. The simulations performed on both synthetic and clinical ultrasound images for speckle reduction, the proposed technique achieved peak signal-to-noise ratios of 35.537 dB for the dictionary trained on noisy image patches and 35.033 dB for the dictionary trained using a set of reference ultrasound image patches. Further, the evaluation results show that the proposed method performs better than other state-of-the-art denoising algorithms in terms of both peak signal-to-noise ratio and subjective visual quality assessment.
International Nuclear Information System (INIS)
Bao, L J; Zhu, Y M; Liu, W Y; Pu, Z B; Magnin, I E; Croisille, P; Robini, M
2009-01-01
Cardiac diffusion tensor magnetic resonance imaging (DT-MRI) is noise sensitive, and the noise can induce numerous systematic errors in subsequent parameter calculations. This paper proposes a sparse representation-based method for denoising cardiac DT-MRI images. The method first generates a dictionary of multiple bases according to the features of the observed image. A segmentation algorithm based on nonstationary degree detector is then introduced to make the selection of atoms in the dictionary adapted to the image's features. The denoising is achieved by gradually approximating the underlying image using the atoms selected from the generated dictionary. The results on both simulated image and real cardiac DT-MRI images from ex vivo human hearts show that the proposed denoising method performs better than conventional denoising techniques by preserving image contrast and fine structures.
Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng
2015-01-01
The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior.
A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image
Directory of Open Access Journals (Sweden)
Fei Wang
2017-01-01
Full Text Available An Intensified Charge-Coupled Device (ICCD image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a Different from the independent identically distributed (i.i.d. noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.
Klos, A.; Bogusz, J.; Moreaux, G.
2017-12-01
This research focuses on the investigation of the deterministic and stochastic parts of the DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) weekly coordinate time series from the IDS contribution to the ITRF2014A set of 90 stations was divided into three groups depending on when the data was collected at an individual station. To reliably describe the DORIS time series, we employed a mathematical model that included the long-term nonlinear signal, linear trend, seasonal oscillations (these three sum up to produce the Polynomial Trend Model) and a stochastic part, all being resolved with Maximum Likelihood Estimation (MLE). We proved that the values of the parameters delivered for DORIS data are strictly correlated with the time span of the observations, meaning that the most recent data are the most reliable ones. Not only did the seasonal amplitudes decrease over the years, but also, and most importantly, the noise level and its type changed significantly. We examined five different noise models to be applied to the stochastic part of the DORIS time series: a pure white noise (WN), a pure power-law noise (PL), a combination of white and power-law noise (WNPL), an autoregressive process of first order (AR(1)) and a Generalized Gauss Markov model (GGM). From our study it arises that the PL process may be chosen as the preferred one for most of the DORIS data. Moreover, the preferred noise model has changed through the years from AR(1) to pure PL with few stations characterized by a positive spectral index.
Estimation of Spectral Exponent Parameter of 1/f Process in Additive White Background Noise
Directory of Open Access Journals (Sweden)
Semih Ergintav
2007-01-01
Full Text Available An extension to the wavelet-based method for the estimation of the spectral exponent, γ, in a 1/fγ process and in the presence of additive white noise is proposed. The approach is based on eliminating the effect of white noise by a simple difference operation constructed on the wavelet spectrum. The γ parameter is estimated as the slope of a linear function. It is shown by simulations that the proposed method gives reliable results. Global positioning system (GPS time-series noise is analyzed and the results provide experimental verification of the proposed method.
What does the structure of its visibility graph tell us about the nature of the time series?
Franke, Jasper G.; Donner, Reik V.
2017-04-01
Visibility graphs are a recently introduced method to construct complex network representations based upon univariate time series in order to study their dynamical characteristics [1]. In the last years, this approach has been successfully applied to studying a considerable variety of geoscientific research questions and data sets, including non-trivial temporal patterns in complex earthquake catalogs [2] or time-reversibility in climate time series [3]. It has been shown that several characteristic features of the thus constructed networks differ between stochastic and deterministic (possibly chaotic) processes, which is, however, relatively hard to exploit in the case of real-world applications. In this study, we propose studying two new measures related with the network complexity of visibility graphs constructed from time series, one being a special type of network entropy [4] and the other a recently introduced measure of the heterogeneity of the network's degree distribution [5]. For paradigmatic model systems exhibiting bifurcation sequences between regular and chaotic dynamics, both properties clearly trace the transitions between both types of regimes and exhibit marked quantitative differences for regular and chaotic dynamics. Moreover, for dynamical systems with a small amount of additive noise, the considered properties demonstrate gradual changes prior to the bifurcation point. This finding appears closely related to the subsequent loss of stability of the current state known to lead to a critical slowing down as the transition point is approaches. In this spirit, both considered visibility graph characteristics provide alternative tracers of dynamical early warning signals consistent with classical indicators. Our results demonstrate that measures of visibility graph complexity (i) provide a potentially useful means to tracing changes in the dynamical patterns encoded in a univariate time series that originate from increasing autocorrelation and (ii
Directory of Open Access Journals (Sweden)
Mihael Brenčič
2009-12-01
Full Text Available Statistical analyses of calcimetric data from boreholes BV-1 (north of PodpeČ and BV-2 (south of ^rna vas on Ljubljansko barje in central Slovenia are given. The original data are represented as unevenly spaced time series that are translated into evenly spaced time series. To calculate the interpolation weighted influence function,amodel based on the power correlated influence is defined.Parameters electionisper formed basedon the maximum entropy principle. In the reconstructed time series, autocorrelation and Fourier power spectrum analyses are performed. In both time series, a transition from white noise to red noise was detected. Such behaviour can be describedby a Lorentz process. Red noise is the result of a stochastic process with long-term memory. This effect can be seen predominantly in the autocorrelation function of borehole BV-1. In the calcimetric time series of borehole BV-2, periodicity with a period between 10.0 m and 12.5 m was also detected. We suppose that this period reflects climatic fluctuations during the Quaternary Period.
Quantifying complexity of financial short-term time series by composite multiscale entropy measure
Niu, Hongli; Wang, Jun
2015-05-01
It is significant to study the complexity of financial time series since the financial market is a complex evolved dynamic system. Multiscale entropy is a prevailing method used to quantify the complexity of a time series. Due to its less reliability of entropy estimation for short-term time series at large time scales, a modification method, the composite multiscale entropy, is applied to the financial market. To qualify its effectiveness, its applications in the synthetic white noise and 1 / f noise with different data lengths are reproduced first in the present paper. Then it is introduced for the first time to make a reliability test with two Chinese stock indices. After conducting on short-time return series, the CMSE method shows the advantages in reducing deviations of entropy estimation and demonstrates more stable and reliable results when compared with the conventional MSE algorithm. Finally, the composite multiscale entropy of six important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.
Sinogram denoising via simultaneous sparse representation in learned dictionaries
International Nuclear Information System (INIS)
Karimi, Davood; Ward, Rabab K
2016-01-01
Reducing the radiation dose in computed tomography (CT) is highly desirable but it leads to excessive noise in the projection measurements. This can significantly reduce the diagnostic value of the reconstructed images. Removing the noise in the projection measurements is, therefore, essential for reconstructing high-quality images, especially in low-dose CT. In recent years, two new classes of patch-based denoising algorithms proved superior to other methods in various denoising applications. The first class is based on sparse representation of image patches in a learned dictionary. The second class is based on the non-local means method. Here, the image is searched for similar patches and the patches are processed together to find their denoised estimates. In this paper, we propose a novel denoising algorithm for cone-beam CT projections. The proposed method has similarities to both these algorithmic classes but is more effective and much faster. In order to exploit both the correlation between neighboring pixels within a projection and the correlation between pixels in neighboring projections, the proposed algorithm stacks noisy cone-beam projections together to form a 3D image and extracts small overlapping 3D blocks from this 3D image for processing. We propose a fast algorithm for clustering all extracted blocks. The central assumption in the proposed algorithm is that all blocks in a cluster have a joint-sparse representation in a well-designed dictionary. We describe algorithms for learning such a dictionary and for denoising a set of projections using this dictionary. We apply the proposed algorithm on simulated and real data and compare it with three other algorithms. Our results show that the proposed algorithm outperforms some of the best denoising algorithms, while also being much faster. (paper)
Direct-reading dial for noise temperature and noise resistance
DEFF Research Database (Denmark)
Diamond, J.M.
1967-01-01
An attenuator arrangement for a noise generator is described. The scheme permits direct reading of both noise resistance and noise temperature¿the latter with a choice of source resistance.......An attenuator arrangement for a noise generator is described. The scheme permits direct reading of both noise resistance and noise temperature¿the latter with a choice of source resistance....
Estimation of system parameters in discrete dynamical systems from time series
International Nuclear Information System (INIS)
Palaniyandi, P.; Lakshmanan, M.
2005-01-01
We propose a simple method to estimate the parameters involved in discrete dynamical systems from time series. The method is based on the concept of controlling chaos by constant feedback. The major advantages of the method are that it needs a minimal number of time series data (either vector or scalar) and is applicable to dynamical systems of any dimension. The method also works extremely well even in the presence of noise in the time series. The method is specifically illustrated by means of logistic and Henon maps
Soltysik, David A; Thomasson, David; Rajan, Sunder; Biassou, Nadia
2015-02-15
Functional magnetic resonance imaging (fMRI) time series are subject to corruption by many noise sources, especially physiological noise and motion. Researchers have developed many methods to reduce physiological noise, including RETROICOR, which retroactively removes cardiac and respiratory waveforms collected during the scan, and CompCor, which applies principal components analysis (PCA) to remove physiological noise components without any physiological monitoring during the scan. We developed four variants of the CompCor method. The optimized CompCor method applies PCA to time series in a noise mask, but orthogonalizes each component to the BOLD response waveform and uses an algorithm to determine a favorable number of components to use as "nuisance regressors." Whole brain component correction (WCompCor) is similar, except that it applies PCA to time-series throughout the whole brain. Low-pass component correction (LCompCor) identifies low-pass filtered components throughout the brain, while high-pass component correction (HCompCor) identifies high-pass filtered components. We compared the new methods with the original CompCor method by examining the resulting functional contrast-to-noise ratio (CNR), sensitivity, and specificity. (1) The optimized CompCor method increased the CNR and sensitivity compared to the original CompCor method and (2) the application of WCompCor yielded the best improvement in the CNR and sensitivity. The sensitivity of the optimized CompCor, WCompCor, and LCompCor methods exceeded that of the original CompCor method. However, regressing noise signals showed a paradoxical consequence of reducing specificity for all noise reduction methods attempted. Published by Elsevier B.V.
Noise frame duration, masking potency and whiteness of temporal noise.
Kukkonen, Heljä; Rovamo, Jyrki; Donner, Kristian; Tammikallio, Marja; Raninen, Antti
2002-09-01
Because of the limited contrast range, increasing the duration of the noise frame is often the only option for increasing the masking potency of external, white temporal noise. This, however, reduces the high-frequency cutoff beyond which noise is no longer white. This study was conducted to determine the longest noise frame duration that produces the strongest masking effect and still mimics white noise on the detection of sinusoidal flicker. Contrast energy thresholds (E(th)) were measured for flicker at 1.25 to 20 Hz in strong, purely temporal (spatially uniform), additive, external noise. The masking power of white external noise, characterized by its spectral density at zero frequency N0, increases with the duration of the noise frame. For short noise frame durations, E(th) increased in direct proportion to N0, keeping the nominal signal-to-noise ratio [SNR = (E(th)/N0)(0.5)] constant at threshold. The masking effect thus increased with the duration of the noise frame and the noise mimicked white noise. When noise frame duration and N0 increased further, the nominal SNR at threshold started to decrease, indicating that noise no longer mimicked white noise. The minimum number of noise frames per flicker cycle needed to mimic white noise decreased with increasing flicker frequency from 8.3 at 1.25 Hz to 1.6 at 20 Hz. The critical high-frequency cutoff of detection-limiting temporal noise in terms of noise frames per signal cycle depends on the temporal frequency of the signal. This is opposite to the situation in the spatial domain and must be taken into consideration when temporal signals are masked with temporal noise.
Factorizations and physical representations
International Nuclear Information System (INIS)
Revzen, M; Khanna, F C; Mann, A; Zak, J
2006-01-01
A Hilbert space in M dimensions is shown explicitly to accommodate representations that reflect the decomposition of M into prime numbers. Representations that exhibit the factorization of M into two relatively prime numbers: the kq representation (Zak J 1970 Phys. Today 23 51), and related representations termed q 1 q 2 representations (together with their conjugates) are analysed, as well as a representation that exhibits the complete factorization of M. In this latter representation each quantum number varies in a subspace that is associated with one of the prime numbers that make up M
Kast, J. R.
1988-01-01
The Upper Atmosphere Research Satellite (UARS) is a three-axis stabilized Earth-pointing spacecraft in a low-Earth orbit. The UARS onboard computer (OBC) uses a Fourier Power Series (FPS) ephemeris representation that includes 42 position and 42 velocity coefficients per axis, with position residuals at 10-minute intervals. New coefficients and 32 hours of residuals are uploaded daily. This study evaluated two backup methods that permit the OBC to compute an approximate spacecraft ephemeris in the event that new ephemeris data cannot be uplinked for several days: (1) extending the use of the FPS coefficients previously uplinked, and (2) switching to a simple circular orbit approximation designed and tested (but not implemented) for LANDSAT-D. The FPS method provides greater accuracy during the backup period and does not require additional ground operational procedures for generating and uplinking an additional ephemeris table. The tradeoff is that the high accuracy of the FPS will be degraded slightly by adopting the longer fit period necessary to obtain backup accuracy for an extended period of time. The results for UARS show that extended use of the FPS is superior to the circular orbit approximation for short-term ephemeris backup.
Noise and Vibration Risk Prevention Virtual Web for Ubiquitous Training
Redel-Macías, María Dolores; Cubero-Atienza, Antonio J.; Martínez-Valle, José Miguel; Pedrós-Pérez, Gerardo; del Pilar Martínez-Jiménez, María
2015-01-01
This paper describes a new Web portal offering experimental labs for ubiquitous training of university engineering students in work-related risk prevention. The Web-accessible computer program simulates the noise and machine vibrations met in the work environment, in a series of virtual laboratories that mimic an actual laboratory and provide the…
Directory of Open Access Journals (Sweden)
Charles F Cadieu
2014-12-01
Full Text Available The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition. This remarkable performance is mediated by the representation formed in inferior temporal (IT cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs. It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of "kernel analysis" that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds.
Active noise control in a duct to cancel broadband noise
Chen, Kuan-Chun; Chang, Cheng-Yuan; Kuo, Sen M.
2017-09-01
The paper presents cancelling duct noises by using the active noise control (ANC) techniques. We use the single channel feed forward algorithm with feedback neutralization to realize ANC. Several kinds of ducts noises including tonal noises, sweep tonal signals, and white noise had investigated. Experimental results show that the proposed ANC system can cancel these noises in a PVC duct very well. The noise reduction of white noise can be up to 20 dB.
On the performance of metrics to predict quality in point cloud representations
Alexiou, Evangelos; Ebrahimi, Touradj
2017-09-01
Point clouds are a promising alternative for immersive representation of visual contents. Recently, an increased interest has been observed in the acquisition, processing and rendering of this modality. Although subjective and objective evaluations are critical in order to assess the visual quality of media content, they still remain open problems for point cloud representation. In this paper we focus our efforts on subjective quality assessment of point cloud geometry, subject to typical types of impairments such as noise corruption and compression-like distortions. In particular, we propose a subjective methodology that is closer to real-life scenarios of point cloud visualization. The performance of the state-of-the-art objective metrics is assessed by considering the subjective scores as the ground truth. Moreover, we investigate the impact of adopting different test methodologies by comparing them. Advantages and drawbacks of every approach are reported, based on statistical analysis. The results and conclusions of this work provide useful insights that could be considered in future experimentation.
Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.
Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen
2015-04-01
In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.
Anthropogenic noise compromises antipredator behaviour in European eels.
Simpson, Stephen D; Purser, Julia; Radford, Andrew N
2015-02-01
Increases in noise-generating human activities since the Industrial Revolution have changed the acoustic landscape of many terrestrial and aquatic ecosystems. Anthropogenic noise is now recognized as a major pollutant of international concern, and recent studies have demonstrated impacts on, for instance, hearing thresholds, communication, movement and foraging in a range of species. However, consequences for survival and reproductive success are difficult to ascertain. Using a series of laboratory-based experiments and an open-water test with the same methodology, we show that acoustic disturbance can compromise antipredator behaviour--which directly affects survival likelihood--and explore potential underlying mechanisms. Juvenile European eels (Anguilla anguilla) exposed to additional noise (playback of recordings of ships passing through harbours), rather than control conditions (playback of recordings from the same harbours without ships), performed less well in two simulated predation paradigms. Eels were 50% less likely and 25% slower to startle to an 'ambush predator' and were caught more than twice as quickly by a 'pursuit predator'. Furthermore, eels experiencing additional noise had diminished spatial performance and elevated ventilation and metabolic rates (indicators of stress) compared with control individuals. Our results suggest that acoustic disturbance could have important physiological and behavioural impacts on animals, compromising life-or-death responses. © 2014 John Wiley & Sons Ltd.
Complex network approach to fractional time series
Energy Technology Data Exchange (ETDEWEB)
Manshour, Pouya [Physics Department, Persian Gulf University, Bushehr 75169 (Iran, Islamic Republic of)
2015-10-15
In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacency matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.
Directory of Open Access Journals (Sweden)
Maria Carolina da Silva
2012-01-01
Full Text Available The aim of this paper is to analyze the representations of school and syllabus divulged by the Harry Potter book series. Successful all around the world, this series consists of seven books telling the adventures of a boy who, at 11 years of age, discovers himself to be a wizard, being sent to Hogwarts School of Witchcraft and Wizardry, where he learns to use his magic powers. Based on the post-structuralist Cultural Studies, I consider the representation not only presents a reality, but pushes actively for its construction. The claim developed is that the school ideally understood by the books is the one serving as home to teachers and students, safe, and grouping the students according to their skills and individual features. The curricular model divulged by the series is a fusion between the scientific syllabus and the practical one. Having in mind the comprehensiveness of the books, it is important to understand how education has been divulged in a non-school cultural product addressed to young people.
Kalman-Takens filtering in the presence of dynamical noise
Hamilton, Franz; Berry, Tyrus; Sauer, Timothy
2017-12-01
The use of data assimilation for the merging of observed data with dynamical models is becoming standard in modern physics. If a parametric model is known, methods such as Kalman filtering have been developed for this purpose. If no model is known, a hybrid Kalman-Takens method has been recently introduced, in order to exploit the advantages of optimal filtering in a nonparametric setting. This procedure replaces the parametric model with dynamics reconstructed from delay coordinates, while using the Kalman update formulation to assimilate new observations. In this article, we study the efficacy of this method for identifying underlying dynamics in the presence of dynamical noise. Furthermore, by combining the Kalman-Takens method with an adaptive filtering procedure we are able to estimate the statistics of the observational and dynamical noise. This solves a long-standing problem of separating dynamical and observational noise in time series data, which is especially challenging when no dynamical model is specified.
The deterministic chaos and random noise in turbulent jet
International Nuclear Information System (INIS)
Yao, Tian-Liang; Liu, Hai-Feng; Xu, Jian-Liang; Li, Wei-Feng
2014-01-01
A turbulent flow is usually treated as a superposition of coherent structure and incoherent turbulence. In this paper, the largest Lyapunov exponent and the random noise in the near field of round jet and plane jet are estimated with our previously proposed method of chaotic time series analysis [T. L. Yao, et al., Chaos 22, 033102 (2012)]. The results show that the largest Lyapunov exponents of the round jet and plane jet are in direct proportion to the reciprocal of the integral time scale of turbulence, which is in accordance with the results of the dimensional analysis, and the proportionality coefficients are equal. In addition, the random noise of the round jet and plane jet has the same linear relation with the Kolmogorov velocity scale of turbulence. As a result, the random noise may well be from the incoherent disturbance in turbulence, and the coherent structure in turbulence may well follow the rule of chaotic motion
Noise Studies of Externally Dispersed Interferometry for Doppler Velocimetry
International Nuclear Information System (INIS)
Erskine, D J; Edelstein, J; Lloyd, J; Muirhead, P
2006-01-01
Externally Dispersed Interferometry (EDI) is the series combination of a fixed-delay field-widened Michelson interferometer with a dispersive spectrograph. This combination boosts the spectrograph performance for both Doppler velocimetry and high resolution spectroscopy. The interferometer creates a periodic comb that multiplies against the input spectrum to create moire fringes, which are recorded in combination with the regular spectrum. Both regular and high-frequency spectral components can be recovered from the data--the moire component carries additional information that increases the signal to noise for velocimetry and spectroscopy. Here we present simulations and theoretical studies of the photon limited Doppler velocity noise in an EDI. We used a model spectrum of a 1600K temperature star. For several rotational blurring velocities 0, 7.5, 15 and 25 km/s we calculated the dimensionless Doppler quality index (Q) versus wavenumber v. This is the normalized RMS of the derivative of the spectrum and is proportional to the photon-limited Doppler signal to noise ratio
Upper-limit on the Advanced Virgo output mode cleaner cavity length noise
Bonnand, R.; Ducrot, M.; Gouaty, R.; Marion, F.; Masserot, A.; Mours, B.; Pacaud, E.; Rolland, L.; Was, M.
2017-09-01
The Advanced Virgo detector uses two monolithic optical cavities at its output port to suppress higher order modes and radio frequency sidebands from the carrier light used for gravitational wave detection. These two cavities in series form the output mode cleaner. We present a measured upper limit on the length noise of these cavities that is consistent with the thermo-refractive noise prediction of 8×10-16~m~Hz-1/2 at 15 Hz. The cavity length is controlled using Peltier cells and piezo-electric actuators to maintain resonance on the incoming light. A length lock precision of 3.5×10-13 m is achieved. These two results are combined to demonstrate that the broadband length noise of the output mode cleaner in the 10-60 Hz band is at least a factor 10 below other expected noise sources in the Advanced Virgo detector design configuration.
Low-count PET image restoration using sparse representation
Li, Tao; Jiang, Changhui; Gao, Juan; Yang, Yongfeng; Liang, Dong; Liu, Xin; Zheng, Hairong; Hu, Zhanli
2018-04-01
In the field of positron emission tomography (PET), reconstructed images are often blurry and contain noise. These problems are primarily caused by the low resolution of projection data. Solving this problem by improving hardware is an expensive solution, and therefore, we attempted to develop a solution based on optimizing several related algorithms in both the reconstruction and image post-processing domains. As sparse technology is widely used, sparse prediction is increasingly applied to solve this problem. In this paper, we propose a new sparse method to process low-resolution PET images. Two dictionaries (D1 for low-resolution PET images and D2 for high-resolution PET images) are learned from a group real PET image data sets. Among these two dictionaries, D1 is used to obtain a sparse representation for each patch of the input PET image. Then, a high-resolution PET image is generated from this sparse representation using D2. Experimental results indicate that the proposed method exhibits a stable and superior ability to enhance image resolution and recover image details. Quantitatively, this method achieves better performance than traditional methods. This proposed strategy is a new and efficient approach for improving the quality of PET images.
A Modified Sparse Representation Method for Facial Expression Recognition
Directory of Open Access Journals (Sweden)
Wei Wang
2016-01-01
Full Text Available In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit method is used to speed up the convergence of OMP (orthogonal matching pursuit. Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan’s JAFFE and CMU’s CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result.
Patterns of physiological and affective responses to vehicle pass-by noises
Directory of Open Access Journals (Sweden)
Gert Notbohm
2013-01-01
Full Text Available Traffic noise is considered causing annoyance and severe health effects like cardiovascular disease (CVD. The present laboratory study examines the importance of individual factors, namely age, gender and personality traits on short term physiological and affective response to vehicle pass-by noises. Four groups of subjects (20-30 vs. 40-55 year-old male or female, n = 66 in total were exposed to a series of vehicle pass-by noises. Physiological responses (finger-pulse amplitude [FPA], skin conductance level [SCL] were registered during the exposure; affective responses and judgements regarding the sounds were assessed by questionnaires. Noise sensitivity and sensation seeking were measured by validated questionnaires. The results show different patterns of response depending on age, gender and personality. The strongest sympathetic stress reaction as measured by SCL was found for the older female group. In regression analysis, the SCL response was predicted by the female gender and low score of sensation seeking only (adjusted R2 = 0.139. The FPA response was strongest among the young men and age was the only significant predictor. For affective responses of pleasantness and activation, regression analysis proved noise sensitivity and sensation seeking to be significant predictors (adjusted R2 = 0.187 respectively 0.154. Age, gender and personality influence physiological and affective reactions to traffic noise, which might affect health conditions. Especially, a potential risk of older women for CVD owing to noise should be investigated further. Individual sensitiveness in terms of noise sensitivity or sensation seeking proves to be important for explaining differences in response to noise.
Indefinite theta series and generalized error functions
Alexandrov, Sergei; Manschot, Jan; Pioline, Boris
2016-01-01
Theta series for lattices with indefinite signature $(n_+,n_-)$ arise in many areas of mathematics including representation theory and enumerative algebraic geometry. Their modular properties are well understood in the Lorentzian case ($n_+=1$), but have remained obscure when $n_+\\geq 2$. Using a higher-dimensional generalization of the usual (complementary) error function, discovered in an independent physics project, we construct the modular completion of a class of `conformal' holomorphic theta series ($n_+=2$). As an application, we determine the modular properties of a generalized Appell-Lerch sum attached to the lattice ${\\operatorname A}_2$, which arose in the study of rank 3 vector bundles on $\\mathbb{P}^2$. The extension of our method to $n_+>2$ is outlined.
Evans, Samuel; Davis, Matthew H
2015-12-01
How humans extract the identity of speech sounds from highly variable acoustic signals remains unclear. Here, we use searchlight representational similarity analysis (RSA) to localize and characterize neural representations of syllables at different levels of the hierarchically organized temporo-frontal pathways for speech perception. We asked participants to listen to spoken syllables that differed considerably in their surface acoustic form by changing speaker and degrading surface acoustics using noise-vocoding and sine wave synthesis while we recorded neural responses with functional magnetic resonance imaging. We found evidence for a graded hierarchy of abstraction across the brain. At the peak of the hierarchy, neural representations in somatomotor cortex encoded syllable identity but not surface acoustic form, at the base of the hierarchy, primary auditory cortex showed the reverse. In contrast, bilateral temporal cortex exhibited an intermediate response, encoding both syllable identity and the surface acoustic form of speech. Regions of somatomotor cortex associated with encoding syllable identity in perception were also engaged when producing the same syllables in a separate session. These findings are consistent with a hierarchical account of how variable acoustic signals are transformed into abstract representations of the identity of speech sounds. © The Author 2015. Published by Oxford University Press.
Sounds and Noises. A Position Paper on Noise Pollution.
Chapman, Thomas L.
This position paper focuses on noise pollution and the problems and solutions associated with this form of pollution. The paper is divided into the following five sections: Noise and the Ear, Noise Measurement, III Effects of Noise, Acoustics and Action, and Programs and Activities. The first section identifies noise and sound, the beginnings of…
Noise influence on spike activation in a Hindmarsh–Rose small-world neural network
International Nuclear Information System (INIS)
Zhe, Sun; Micheletto, Ruggero
2016-01-01
We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh−Rose (H−R) neural networks. (paper)
Noise influence on spike activation in a Hindmarsh-Rose small-world neural network
Zhe, Sun; Micheletto, Ruggero
2016-07-01
We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.
Marković, D.; Koch, M.
2005-09-01
The influence of the periodic signals in time series on the Hurst parameter estimate is investigated with temporal, spectral and time-scale methods. The Hurst parameter estimates of the simulated periodic time series with a white noise background show a high sensitivity on the signal to noise ratio and for some methods, also on the data length used. The analysis is then carried on to the investigation of extreme monthly river flows of the Elbe River (Dresden) and of the Rhine River (Kaub). Effects of removing the periodic components employing different filtering approaches are discussed and it is shown that such procedures are a prerequisite for an unbiased estimation of H. In summary, our results imply that the first step in a time series long-correlation study should be the separation of the deterministic components from the stochastic ones. Otherwise wrong conclusions concerning possible memory effects may be drawn.
Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le
2018-02-12
The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.
Gang, Zhang; Fansong, Meng; Jianzhong, Wang; Mingtao, Ding
2018-02-01
Determining magnetotelluric impedance precisely and accurately is fundamental to valid inversion and geological interpretation. This study aims to determine the minimum value of signal-to-noise ratio (SNR) which maintains the effectiveness of remote reference technique. Results of standard time series simulation, addition of different Gaussian noises to obtain the different SNR time series, and analysis of the intermediate data, such as polarization direction, correlation coefficient, and impedance tensor, show that when the SNR value is larger than 23.5743, the polarization direction disorder at morphology and a smooth and accurate sounding carve value can be obtained. At this condition, the correlation coefficient value of nearly complete segments between the base and remote station is larger than 0.9, and impedance tensor Zxy presents only one aggregation, which meet the natural magnetotelluric signal characteristic.
Multi-representation based on scientific investigation for enhancing students’ representation skills
Siswanto, J.; Susantini, E.; Jatmiko, B.
2018-03-01
This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis value of .64 which means some medium improvements. The result of t-test (α = .05) is shows p-value = .001. This learning significantly improves students representation skills.
The influence of low frequencies on the assessment of noise from neighbours
DEFF Research Database (Denmark)
Rindel, Jens Holger; Rasmussen, Birgit; Nielsen, Jesper Rye
1996-01-01
Lightweight building constructions often suffer from insufficient sound insulation at low frequencies. In order to investigate the degree of the problems, a laboratory experiment has been carried out. Twenty test persons have been asked to evaluate series of typical noise from neighbours, ie, two...
1/f noise as a reliability estimation for solar panels
Alabedra, R.; Orsal, B.
The purpose of this work is a study of the 1/f noise from a forward biased dark solar cell as a nondestructive reliability estimation of solar panels. It is shown that one cell with a given defect can be detected in a solar panel by low frequency noise measurements at obscurity. One real solar panel of 5 cells in parallel and 5 cells in series is tested by this method. The cells for space application are n(+)p monocrystalline silicon junction with an area of 8 sq cm and a base resistivity of 10 ohm/cm. In the first part of this paper the I-V, Rd=f(1) characteristics of one cell or of a panel are not modified when a small defect is introduced by a mechanical constraint. In the second part, the theoretical results on the 1/f noise in a p-n junction under forward bias are recalled. It is shown that the noise of the cell with a defect is about 10 to 15 times higher than that of a good cell. If one good cell is replaced by a cell with defect in the panel 5 x 5, this leads to an increase of about 30 percent of the noise level of the panel.
Noise from wind turbines. Final report of project JOU2-CT92-0124
International Nuclear Information System (INIS)
Van der Borg, N.; Andersen, B.; Mackinnon, A.; Klug, H.; Theofiloyannakos, D.
1995-04-01
Part of the planning procedure for the erection of a wind turbine or a wind farm is the prediction of the acoustic noise due to the wind turbine(s) at the nearest dwelling. The noise is normally predicted using the acoustic characteristics of the regarded wind turbine as measured on a wind turbine of equal make and model and using a general noise propagation model. Both inputs introduce uncertainties in the predicted noise level: (a) turbines of equal make and model may have different acoustic characteristics; (b) the acoustic characteristics of a turbine may change in time - from day to day (repeatability of the measurement), - during the years (ageing of the turbine); (c) the general propagation model does not take into account the effects of source elevation and wind. The project aimed at the quantification of these uncertainties and at the development of a wind turbine noise propagation model. Statistical information has been collected on the individual differences of the sound power and tonality of turbines of equal make and model by measuring 6 different types of wind turbines. Of each type 5 individual turbines have been measured (total 30 turbines). Additionally the sound power of a series of 4 wind turbines and of a series of 29 wind turbines (from earlier measurements) have been introduced into the project. Statistical information has been collected on the day to day variations of the sound power and tonality of wind turbines by measuring 3 different turbines 5 times (total 15 measurements). Statistical information has been collected on the effect of ageing on the sound power and tonality of wind turbines by the repeated measurement of 5 wind turbines that have been measured in an identical situation 3 to 7 years earlier. A method for the prediction of wind turbine noise propagation has been developed based on measurements of sound propagation from an elevated noise source and theoretical calculations. (Abstract Truncated)
Rumelhart, David E.; Norman, Donald A.
This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics…
Attention and Representational Momentum
Hayes, Amy; Freyd, Jennifer J
1995-01-01
Representational momentum, the tendency for memory to be distorted in the direction of an implied transformation, suggests that dynamics are an intrinsic part of perceptual representations. We examined the effect of attention on dynamic representation by testing for representational momentum under conditions of distraction. Forward memory shifts increase when attention is divided. Attention may be involved in halting but not in maintaining dynamic representations.
Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section
Directory of Open Access Journals (Sweden)
Chaolong Jia
2014-01-01
Full Text Available Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.
International Nuclear Information System (INIS)
Adzhemyan, L.Ts.; Vasil'ev, A.N.; Pis'mak, Yu.M.
1988-01-01
The investigation of the infrared behavior of the propagator of a light wave in a randomly inhomogeneous medium with massless Gaussian noise is continued. The infrared representation of the propagator for correlation function D varphi (k)∼k -2 is generalized to the case of an arbitrary power-law noise correlation function is rigorously established in the first two orders of the infrared asymptotic behavior by construction of a suitable R operation. As a consequence, the results are generalized to the case of critical opalescence, when D varphi (k)∼k -2+η , where η ∼ 0.03 is the Fisher index
LGBT Representations on Facebook : Representations of the Self and the Content
Chu, Yawen
2017-01-01
The topic of LGBT rights has been increasingly discussed and debated over recent years. More and more scholars show their interests in the field of LGBT representations in media. However, not many studies involved LGBT representations in social media. This paper explores LGBT representations on Facebook by analysing posts on an open page and in a private group, including both representations of the self as the identity of sexual minorities, content that is displayed on Facebook and the simila...
A 3-D discontinuous Galerkin Method for jet engine buzz-saw noise propagation
International Nuclear Information System (INIS)
Remaki, M.; Habashi, W.G.; Ait-Ali-Yahia, D.; Jay, A.
2002-01-01
This paper presents a 3-D methodology for solving jet engine aero-acoustics problems in the presence of strong shocks and rarefactions. For example, turbofan engines suffer from Multiple Pure Tone noise, also called Buzz-saw noise, generated by the fan when the blade rotational tip speed is supersonic. These waves are composed of a series of shocks and rarefactions produced by a coalescence of shocks due to non-uniformities in the blade spacing and in the blade stagger angles, arising from manufacturing tolerances
Sparse representation of sounds in the unanesthetized auditory cortex.
Directory of Open Access Journals (Sweden)
Tomás Hromádka
2008-01-01
Full Text Available How do neuronal populations in the auditory cortex represent acoustic stimuli? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. To quantify the relative contributions of these different subpopulations in the awake preparation, we have estimated the representation of sounds across the neuronal population using a representative ensemble of stimuli. We used cell-attached recording with a glass electrode, a method for which single-unit isolation does not depend on neuronal activity, to quantify the fraction of neurons engaged by acoustic stimuli (tones, frequency modulated sweeps, white-noise bursts, and natural stimuli in the primary auditory cortex of awake head-fixed rats. We find that the population response is sparse, with stimuli typically eliciting high firing rates (>20 spikes/second in less than 5% of neurons at any instant. Some neurons had very low spontaneous firing rates (<0.01 spikes/second. At the other extreme, some neurons had driven rates in excess of 50 spikes/second. Interestingly, the overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. Our results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.
Electrochemical Noise Chaotic Analysis of NiCoAg Alloy in Hank Solution
Directory of Open Access Journals (Sweden)
D. Bahena
2011-01-01
Full Text Available The potential and current oscillations during corrosion of NiCoAg alloy in Hank solution were studied. Detailed nonlinear fractal analyses were used to characterize complex time series clearly showing that the irregularity in these time series corresponds to deterministic chaos rather than to random noise. The chaotic oscillations were characterized by power spectral densities, phase space, and Lyapunov exponents. Electrochemical impedance was also applied the fractal dimensions for the corroded surface was obtained, and a corrosion mechanism was proposed.
Noise-induced hearing loss: a recreational noise perspective.
Ivory, Robert; Kane, Rebecca; Diaz, Rodney C
2014-10-01
This review will discuss the real-world risk factors involved in noise-induced hearing loss as a result of common and popular recreational activities prone to mid and high levels of noise exposure. Although there are currently no interventional measures available to reverse or mitigate preexisting hearing loss from noise, we discuss the vital importance of hearing loss prevention from noise exposure avoidance and reduction. Despite a seeming understanding of the effects of noise exposure from various recreational activities and devices, a large percentage of the general public who is at risk of such noise-induced hearing loss still chooses to refrain from using hearing protection instruments. While occupational exposures pose the greatest traditional risk to hearing conservation in selected workers, recreational risk factors for noise-induced hearing loss may be more insidious in overall effect given the indifferent attitude of much of the general public and particularly our youths toward hearing protection during recreational activities. Active counseling regarding the consequences of excessive noise exposure and the potential benefits to hearing from usage of hearing protection instruments is critical to providing best possible care in the hearing health professions.
Data fusion of multi-scale representations for structural damage detection
Guo, Tian; Xu, Zili
2018-01-01
Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.
Splettstoesser, W. R.; Schultz, K. J.; Boxwell, D. A.; Schmitz, F. H.
1984-01-01
Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model scale data were compared with averaged full scale, inflight acoustic data under similar nondimensional test conditions. At low advance ratios (mu = 0.164 to 0.194), the data scale remarkable well in level and waveform shape, and also duplicate the directivity pattern of BVI impulsive noise. At moderate advance ratios (mu = 0.224 to 0.270), the scaling deteriorates, suggesting that the model scale rotor is not adequately simulating the full scale BVI noise; presently, no proved explanation of this discrepancy exists. Carefully performed parametric variations over a complete matrix of testing conditions have shown that all of the four governing nondimensional parameters - tip Mach number at hover, advance ratio, local inflow ratio, and thrust coefficient - are highly sensitive to BVI noise radiation.
Faithful representation of similarities among three-dimensional shapes in human vision.
Cutzu, F; Edelman, S
1996-01-01
Efficient and reliable classification of visual stimuli requires that their representations reside a low-dimensional and, therefore, computationally manageable feature space. We investigated the ability of the human visual system to derive such representations from the sensory input-a highly nontrivial task, given the million or so dimensions of the visual signal at its entry point to the cortex. In a series of experiments, subjects were presented with sets of parametrically defined shapes; the points in the common high-dimensional parameter space corresponding to the individual shapes formed regular planar (two-dimensional) patterns such as a triangle, a square, etc. We then used multidimensional scaling to arrange the shapes in planar configurations, dictated by their experimentally determined perceived similarities. The resulting configurations closely resembled the original arrangements of the stimuli in the parameter space. This achievement of the human visual system was replicated by a computational model derived from a theory of object representation in the brain, according to which similarities between objects, and not the geometry of each object, need to be faithfully represented. Images Fig. 3 PMID:8876260
Salomons, E.M.; Janssen, S.A.
2011-01-01
In environmental noise control one commonly employs the A-weighted sound level as an approximate measure of the effect of noise on people. A measure that is more closely related to direct human perception of noise is the loudness level. At constant A-weighted sound level, the loudness level of a
First Test of Fan Active Noise Control (ANC) Completed
2005-01-01
With the advent of ultrahigh-bypass engines, the space available for passive acoustic treatment is becoming more limited, whereas noise regulations are becoming more stringent. Active noise control (ANC) holds promise as a solution to this problem. It uses secondary (added) noise sources to reduce or eliminate the offending noise radiation. The first active noise control test on the low-speed fan test bed was a General Electric Company system designed to control either the exhaust or inlet fan tone. This system consists of a "ring source," an induct array of error microphones, and a control computer. Fan tone noise propagates in a duct in the form of spinning waves. These waves are detected by the microphone array, and the computer identifies their spinning structure. The computer then controls the "ring source" to generate waves that have the same spinning structure and amplitude, but 180 out of phase with the fan noise. This computer generated tone cancels the fan tone before it radiates from the duct and is heard in the far field. The "ring source" used in these tests is a cylindrical array of 16 flat-plate acoustic radiators that are driven by thin piezoceramic sheets bonded to their back surfaces. The resulting source can produce spinning waves up to mode 7 at levels high enough to cancel the fan tone. The control software is flexible enough to work on spinning mode orders from -6 to 6. In this test, the fan was configured to produce a tone of order 6. The complete modal (spinning and radial) structure of the tones was measured with two builtin sets of rotating microphone rakes. These rakes provide a measurement of the system performance independent from the control system error microphones. In addition, the far-field noise was measured with a semicircular array of 28 microphones. This test represents the first in a series of tests that demonstrate different active noise control concepts, each on a progressively more complicated modal structure. The tests are
Noise performance of microwave humidity sounders over their lifetime
Hans, Imke; Burgdorf, Martin; John, Viju O.; Mittaz, Jonathan; Buehler, Stefan A.
2017-12-01
The microwave humidity sounders Special Sensor Microwave Water Vapor Profiler (SSMT-2), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) to date have been providing data records for 25 years. So far, the data records lack uncertainty information essential for constructing consistent long time data series. In this study, we assess the quality of the recorded data with respect to the uncertainty caused by noise. We calculate the noise on the raw calibration counts from the deep space views (DSVs) of the instrument and the noise equivalent differential temperature (NEΔT) as a measure for the radiometer sensitivity. For this purpose, we use the Allan deviation that is not biased from an underlying varying mean of the data and that has been suggested only recently for application in atmospheric remote sensing. Moreover, we use the bias function related to the Allan deviation to infer the underlying spectrum of the noise. As examples, we investigate the noise spectrum in flight for some instruments. For the assessment of the noise evolution in time, we provide a descriptive and graphical overview of the calculated NEΔT over the life span of each instrument and channel. This overview can serve as an easily accessible information for users interested in the noise performance of a specific instrument, channel and time. Within the time evolution of the noise, we identify periods of instrumental degradation, which manifest themselves in an increasing NEΔT, and periods of erratic behaviour, which show sudden increases of NEΔT interrupting the overall smooth evolution of the noise. From this assessment and subsequent exclusion of the aforementioned periods, we present a chart showing available data records with NEΔT processing to provide input values for the uncertainty propagation in the generation of a new set of Fundamental Climate Data Records (FCDRs) that are currently produced in the project Fidelity and Uncertainty in Climate data
Effects of a traffic noise background on judgements of aircraft noise
Powell, C. A.; Rice, C. G.
1974-01-01
A study was conducted in which subjects judged aircraft noises in the presence of road traffic background noise. Two different techniques for presenting the background noises were evaluated. For one technique, the background noise was continuous over the whole of a test session. For the other, the background noise was changed with each aircraft noise. A range of aircraft noise levels and traffic noise levels were presented to simulate typical indoor levels.
Directory of Open Access Journals (Sweden)
F. Golbabaei
2007-09-01
Full Text Available Background and aims Overexposure to industrial noise pollution induce hearing loss workers. Occupational hearing loss may cause interference whit oral communication, so it may increase the risk of occupational accidents in workplace as well as affects whit social activities. This study was conducted on Lavan Island, are of oil extracting regions in the south of Iran. The object of this study was to evaluate noise pollution and determining the effect of noise enclosure on noise abatement. Methods The noise sources were recognized and noise pressure level was measured by CEL- 440. Noise dose of the exposed workers in high level noise area were measured by CEL 272. Results Major noise sources were gas turbines, diesel generators, compressors, fans and gas containing pips, noise contour map revealers that noise level were higher than the recommended national exposure limit. The results of workers noise dose show that their noise exposure were higher than the recommended value, (p<0.001. Finally, by using the results of noise frequency analysis of different noise sources, the noise pressure level of each sources was determined in terms of enclosing them. Conclusion By enclosing the noise sources, noise pressure levels can be lowered douse to acceptable levels but limitation of applying enclosure should be regarded.
Noise cancellation properties of displacement noise free interferometer
International Nuclear Information System (INIS)
Sato, Shuichi; Kawamura, Seiji; Nishizawa, Atsushi; Chen Yanbei
2010-01-01
We have demonstrated the practical feasibility of a displacement- and frequency-noise-free laser interferometer (DFI) by partially implementing a recently proposed optical configuration using bi-directional Mach-Zehnder interferometers (MZIs). The noise cancellation efficiency was evaluated by comparing the displacement noise spectrum of the MZIs and the DFI, demonstrating up to 50 dB of noise cancellation. In addition, the possible extension of DFI as QND device is explored.
International Nuclear Information System (INIS)
Joung, Euihun; Mourad, Jihad; Parentani, Renaud
2007-01-01
We use an algebraic approach based on representations of de Sitter group to construct covariant quantum fields in arbitrary dimensions. We study the complementary and the discrete series which correspond to light and massless fields and which lead new feature with respect to the massive principal series we previously studied (hep-th/0606119). When considering the complementary series, we make use of a non-trivial scalar product in order to get local expressions in the position representation. Based on these, we construct a family of covariant canonical fields parametrized by SU(1, 1)/U(1). Each of these correspond to the dS invariant alpha-vacua. The behavior of the modes at asymptotic times brings another difficulty as it is incompatible with the usual definition of the in and out vacua. We propose a generalized notion of these vacua which reduces to the usual conformal vacuum in the conformally massless limit. When considering the massless discrete series we find that no covariant field obeys the canonical commutation relations. To further analyze this singular case, we consider the massless limit of the complementary scalar fields we previously found. We obtain canonical fields with a deformed representation by zero modes. The zero modes have a dS invariant vacuum with singular norm. We propose a regularization by a compactification of the scalar field and a dS invariant definition of the vertex operators. The resulting two-point functions are dS invariant and have a universal logarithmic infrared divergence
Directory of Open Access Journals (Sweden)
Francucci M
2010-01-01
Full Text Available Amplitude-modulated (AM laser imaging is a promising technology for the production of accurate three-dimensional (3D images of submerged scenes. The main challenge is that radiation scattered off water gives rise to a disturbing signal (optical noise that degrades more and more the quality of 3D images for increasing turbidity. In this paper, we summarize a series of theoretical findings, that provide valuable hints for the development of experimental methods enabling a partial rejection of optical noise in underwater imaging systems. In order to assess the effectiveness of these methods, which range from modulation/demodulation to polarimetry, we carried out a series of experiments by using the laboratory prototype of an AM 3D imager ( = 405 nm for marine archaeology surveys, in course of realization at the ENEA Artificial Vision Laboratory (Frascati, Rome. The obtained results confirm the validity of the proposed methods for optical noise rejection.
Directory of Open Access Journals (Sweden)
R. Ricci
2010-01-01
Full Text Available Amplitude-modulated (AM laser imaging is a promising technology for the production of accurate three-dimensional (3D images of submerged scenes. The main challenge is that radiation scattered off water gives rise to a disturbing signal (optical noise that degrades more and more the quality of 3D images for increasing turbidity. In this paper, we summarize a series of theoretical findings, that provide valuable hints for the development of experimental methods enabling a partial rejection of optical noise in underwater imaging systems. In order to assess the effectiveness of these methods, which range from modulation/demodulation to polarimetry, we carried out a series of experiments by using the laboratory prototype of an AM 3D imager (λ = 405 nm for marine archaeology surveys, in course of realization at the ENEA Artificial Vision Laboratory (Frascati, Rome. The obtained results confirm the validity of the proposed methods for optical noise rejection.
Consistent modelling of wind turbine noise propagation from source to receiver.
Barlas, Emre; Zhu, Wei Jun; Shen, Wen Zhong; Dag, Kaya O; Moriarty, Patrick
2017-11-01
The unsteady nature of wind turbine noise is a major reason for annoyance. The variation of far-field sound pressure levels is not only caused by the continuous change in wind turbine noise source levels but also by the unsteady flow field and the ground characteristics between the turbine and receiver. To take these phenomena into account, a consistent numerical technique that models the sound propagation from the source to receiver is developed. Large eddy simulation with an actuator line technique is employed for the flow modelling and the corresponding flow fields are used to simulate sound generation and propagation. The local blade relative velocity, angle of attack, and turbulence characteristics are input to the sound generation model. Time-dependent blade locations and the velocity between the noise source and receiver are considered within a quasi-3D propagation model. Long-range noise propagation of a 5 MW wind turbine is investigated. Sound pressure level time series evaluated at the source time are studied for varying wind speeds, surface roughness, and ground impedances within a 2000 m radius from the turbine.
Time-variant power spectral analysis of heart-rate time series by ...
Indian Academy of Sciences (India)
Frequency domain representation of a short-term heart-rate time series (HRTS) signal is a popular method for evaluating the cardiovascular control system. The spectral parameters, viz. percentage power in low frequency band (%PLF), percentage power in high frequency band (%PHF), power ratio of low frequency to high ...
Wavelet transform approach for fitting financial time series data
Ahmed, Amel Abdoullah; Ismail, Mohd Tahir
2015-10-01
This study investigates a newly developed technique; a combined wavelet filtering and VEC model, to study the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in daily data set of NASDAQ stock market of US, and three stock markets of Middle East and North Africa (MENA) region, namely, Egypt, Jordan, and Istanbul. The data covered is from 6/29/2001 to 5/5/2009. After that, the returns of generated series by wavelet filter and original series are analyzed by cointegration test and VEC model. The results show that the cointegration test affirms the existence of cointegration between the studied series, and there is a long-term relationship between the US, stock markets and MENA stock markets. A comparison between the proposed model and traditional model demonstrates that, the proposed model (DWT with VEC model) outperforms traditional model (VEC model) to fit the financial stock markets series well, and shows real information about these relationships among the stock markets.
Masking potency and whiteness of noise at various noise check sizes.
Kukkonen, H; Rovamo, J; Näsänen, R
1995-02-01
The masking effect of spatial noise can be increased by increasing either the rms contrast or check size of noise. In this study, the authors investigated the largest noise check size that still mimics the effect of white noise in grating detection and how it depends on the bandwidth and spatial frequency of a grating. The authors measured contrast energy thresholds, E, for vertical cosine gratings at various spatial frequencies and bandwidths. Gratings were embedded in two-dimensional spatial noise. The side length of the square noise checks was varied in the experiments. The spectral density, N(0,0), of white spatial noise at zero frequency was calculated by multiplying the noise check area by the rms contrast of noise squared. The physical signal-to-noise ratio at threshold [E/N(0,0)]0.5 was initially constant but then started to decrease. The largest noise check that still produced a constant physical signal-to-noise ratio at threshold was directly proportional to the spatial frequency. When expressed as a fraction of grating cycle, the largest noise check size depended only on stimulus bandwidth. The smallest number of noise checks per grating cycle needed to mimic the effect of white noise decreased from 4.2 to 2.6 when the number of grating cycles increased from 1 to 64. Spatial noise can be regarded as white in grating detection if there are at least four square noise checks per grating cycle at all spatial frequencies.
Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.
Downer, Joshua D; Rapone, Brittany; Verhein, Jessica; O'Connor, Kevin N; Sutter, Mitchell L
2017-05-24
Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations ( r noise ) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on r noise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in r noise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments. SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations ( r noise ) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on r noise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning
International Nuclear Information System (INIS)
Fulinski, A.
1994-01-01
The properties of non-Markovian noises with exponentially correlated memory are discussed. Considered are dichotomic noise, white shot noise, Gaussian white noise, and Gaussian colored noise. The stationary correlation functions of the non-Markovian versions of these noises are given by linear combinations of two or three exponential functions (colored noises) or of the δ function and exponential function (white noises). The non-Markovian white noises are well defined only when the kernel of the non-Markovian master equation contains a nonzero admixture of a Markovian term. Approximate equations governing the probability densities for processes driven by such non-Markovian noises are derived, including non-Markovian versions of the Fokker-Planck equation and the telegrapher's equation. As an example, it is shown how the non-Markovian nature changes the behavior of the driven linear process
Social representations of climate change
International Nuclear Information System (INIS)
BOY, D.
2013-01-01
Each year since 2000, the French 'ADEME' (Agency for Environment and Energy Management) conducts a survey on the social representations of greenhouse effect and global warming. This survey is administered by telephone to a representative sample of the French population. The information gathered in the database can answer a series of basic questions concerning public perception in this area. What do the concepts of 'greenhouse effect' and 'global warming' mean for the public? To what extent do people think there is a consensus among scientists to explain these phenomena? Is responsibility for human action clearly established? What kind of solutions, based on public regulation or private initiative can help to remedy this situation? Finally, what were the major changes in public opinion over this 12 years period? (author)
Representation Elements of Spatial Thinking
Fiantika, F. R.
2017-04-01
This paper aims to add a reference in revealing spatial thinking. There several definitions of spatial thinking but it is not easy to defining it. We can start to discuss the concept, its basic a forming representation. Initially, the five sense catch the natural phenomenon and forward it to memory for processing. Abstraction plays a role in processing information into a concept. There are two types of representation, namely internal representation and external representation. The internal representation is also known as mental representation; this representation is in the human mind. The external representation may include images, auditory and kinesthetic which can be used to describe, explain and communicate the structure, operation, the function of the object as well as relationships. There are two main elements, representations properties and object relationships. These elements play a role in forming a representation.
Kim, Jaehwan; Lim, Changwoo; Hong, Jiyoung; Lee, Soogab
2010-02-01
An experimental study was performed to compare the annoyances from civil-aircraft noise, military-aircraft noise, railway noise, and road-traffic noise. Two-way within-subjects designs were applied in this research. Fifty-two subjects, who were naive listeners, were given various stimuli with varying levels through a headphone in an anechoic chamber. Regardless of the frequency weighting network, even under the same average energy level, civil-aircraft noise was the most annoying, followed by military-aircraft noise, railway noise, and road-traffic noise. In particular, penalties in the time-averaged, A-weighted sound level (TAL) of about 8, 5, and 5 dB, respectively, were found in the civil-aircraft, military-aircraft, and railway noises. The reason could be clarified through the high-frequency component and the variability in the level. When people were exposed to sounds with the same maximum A-weighted level, a railway bonus of about 3 dB was found. However, transportation noise has been evaluated by the time-averaged A-weighted level in most countries. Therefore, in the present situation, the railway bonus is not acceptable for railway vehicles with diesel-electric engines.
Eisenstein series and string thresholds
International Nuclear Information System (INIS)
Obers, N.A.; Pioline, B.
2000-01-01
We investigate the relevance of Eisenstein series for representing certain G(Z)-invariant string theory amplitudes which receive corrections from BPS states only. G(Z) may stand for any of the mapping class, T-duality and U-duality groups Sl(d,Z), SO(d,d,Z) or E d+1(d+1) (Z) respectively. Using G(Z)-invariant mass formulae, we construct invariant modular functions on the symmetric space K backslash G(R) of non-compact type, with K the maximal compact subgroup of G(R), that generalize the standard non-holomorphic Eisenstein series arising in harmonic analysis on the fundamental domain of the Poincare upper half-plane. Comparing the asymptotics and eigenvalues of the Eisenstein series under second order differential operators with quantities arising in one- and g-loop string amplitudes, we obtain a manifestly T-duality invariant representation of the latter, conjecture their non-perturbative U-duality invariant extension, and analyze the resulting non-perturbative effects. This includes the R 4 and R 4 H -4 g -4 couplings in toroidal compactifications of M-theory to any dimension D≥4 and D≥6 respectively. (orig.)
When cognition kicks in: Working memory and speech understanding in noise
Directory of Open Access Journals (Sweden)
Jerker Ronnberg
2010-01-01
Full Text Available Perceptual load and cognitive load can be separately manipulated and dissociated in their effects on speech understanding in noise. The Ease of Language Understanding model assumes a theoretical position where perceptual task characteristics interact with the individual′s implicit capacities to extract the phonological elements of speech. Phonological precision and speed of lexical access are important determinants for listening in adverse conditions. If there are mismatches between the phonological elements perceived and phonological representations in long-term memory, explicit working memory (WM-related capacities will be continually invoked to reconstruct and infer the contents of the ongoing discourse. Whether this induces a high cognitive load or not will in turn depend on the individual′s storage and processing capacities in WM. Data suggest that modulated noise maskers may serve as triggers for speech maskers and therefore induce a WM, explicit mode of processing. Individuals with high WM capacity benefit more than low WM-capacity individuals from fast amplitude compression at low or negative input speech-to-noise ratios. The general conclusion is that there is an overarching interaction between the focal purpose of processing in the primary listening task and the extent to which a secondary, distracting task taps into these processes.
Environmental noise and noise modelling-some aspects in Malaysian development
International Nuclear Information System (INIS)
Leong, Mohd Salman; Mohd Shafiek bin Hj Yaacob
1994-01-01
Environmental noise is of growing concern in Malaysia with the increasing awareness of the need for an environmental quality consistent with improved quality of life. While noise is one of the several elements in an Environmental Impact Assessment report, the degree of emphasis in the assessment is not as thorough as other aspects in the EIA study. The measurements, prediction (if at all any), and evaluation tended to be superficial. The paper presents a summary of correct noise descriptors and annoyance assessment parameters appropriate for the evaluation of environmental noise. The paper further highlights current inadequacies in the Environmental Quality Act for noise pollution, and annoyance assessment. Some examples of local noise pollution are presented. A discussion on environmental noise modelling is presented. Examples illustrating environmental noise modelling for a mining operation and a power station are given. It is the authors' recommendation that environmental noise modelling be made mandatory in all EIA studies such that a more definitive assessment could be realised
On the labeling and symmetry adaptation of the solvable finite groups representations
International Nuclear Information System (INIS)
Caride, A.O.; Zanette, S.I.; Nogueira, S.R.A.
1987-01-01
We propose a method to simultaneously perform a symmetry adaptation and a labeling of the bases of the irreducible representations of the solvable finite groups. It is performed by difining a self-adjoint operator with ligenvalues which evidence the descent in symmetry of the group-subgroups sequences. We also prove two theorems on the canonicity of the cpomposition series of the solvable groups. (author) [pt
Annoyance of low frequency noise and traffic noise
DEFF Research Database (Denmark)
Mortensen, F.R.; Poulsen, Torben
2001-01-01
The annoyance of different low frequency noise sources was determined and compared to the annoyance from traffic noise. Twenty-two subjects participated in laboratory listening tests. The sounds were presented by loudspeakers in a listening room and the spectra of the low frequency noises were...
Detection of chaotic determinism in time series from randomly forced maps
DEFF Research Database (Denmark)
Chon, K H; Kanters, J K; Cohen, R J
1997-01-01
Time series from biological system often display fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". Despite this effort, it has been difficult to establish the presence of cha...... series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data....
Drunk driving detection based on classification of multivariate time series.
Li, Zhenlong; Jin, Xue; Zhao, Xiaohua
2015-09-01
This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.
SOME PROPERTIES OF HORN TYPE SECOND ORDER DOUBLE HYPERGEOMETRIC SERIES
Directory of Open Access Journals (Sweden)
Anvar Hasanov
2018-04-01
Full Text Available Horn [1931, Hypergeometrische Funktionen zweier Veranderlichen, Math. Ann.,105(1, 381-407], (corrections in Borngasser [1933, Uber hypergeometrische funkionen zweier Veranderlichen, Dissertation, Darmstadt], defined and investigated ten second order hypergeometric series of two variables. In the course of further investigation of Horn’s series, we noticed the existence of hypergeometric double series H*2 analogous to Horn’s double series H*2. The principal object of this paper is to present a natural further step toward the mathematical properties and presentations concerning the analogous hypergeometric double series H*2 Indeed, motivated by the important role of the Horn’s functions in several diverse fields of physics and the contributions toward the unification and generalization of the hyper-geometric functions, we establish a system of partial differential equations, integral representations, expansions, analytic continuation, transformation formulas and generating relations. Also, we discuss the links for the various results, which are presented in this paper, with known results.
Evaluating noise abatement measures using strategic noise maps
Borst, H.C.; Miedema, H.M.E.; Laan, W.P.N. van der; Lohman, W.J.A.
2006-01-01
Noise annoyance due to transportation is widespread in industrialized countries and in urban areas in the developing countries. The European Noise Directive (END) requires an assessment of the noise situation as well as the formulation of action plans for the reduction of the number of people
Indirect inference with time series observed with error
DEFF Research Database (Denmark)
Rossi, Eduardo; Santucci de Magistris, Paolo
estimation. We propose to solve this inconsistency by jointly estimating the nuisance and the structural parameters. Under standard assumptions, this estimator is consistent and asymptotically normal. A condition for the identification of ARMA plus noise is obtained. The proposed methodology is used......We analyze the properties of the indirect inference estimator when the observed series are contaminated by measurement error. We show that the indirect inference estimates are asymptotically biased when the nuisance parameters of the measurement error distribution are neglected in the indirect...... to estimate the parameters of continuous-time stochastic volatility models with auxiliary specifications based on realized volatility measures. Monte Carlo simulations shows the bias reduction of the indirect estimates obtained when the microstructure noise is explicitly modeled. Finally, an empirical...
Reconstruction of ensembles of coupled time-delay systems from time series.
Sysoev, I V; Prokhorov, M D; Ponomarenko, V I; Bezruchko, B P
2014-06-01
We propose a method to recover from time series the parameters of coupled time-delay systems and the architecture of couplings between them. The method is based on a reconstruction of model delay-differential equations and estimation of statistical significance of couplings. It can be applied to networks composed of nonidentical nodes with an arbitrary number of unidirectional and bidirectional couplings. We test our method on chaotic and periodic time series produced by model equations of ensembles of diffusively coupled time-delay systems in the presence of noise, and apply it to experimental time series obtained from electronic oscillators with delayed feedback coupled by resistors.
Naguib, M.; Van Oers, K.; Braakhuis, A.; Griffioen, M.; De Goede, P.; Waas, J.R.
2013-01-01
Anthropogenic noise can have serious implications for animals, especially when they communicate acoustically. Yet, the impacts of noise may depend not only on noise characteristics but also on an individual's coping style or personality. We tested whether noise is more disturbing if it masks
International Nuclear Information System (INIS)
Ferrie, Christopher; Emerson, Joseph
2008-01-01
Several finite-dimensional quasi-probability representations of quantum states have been proposed to study various problems in quantum information theory and quantum foundations. These representations are often defined only on restricted dimensions and their physical significance in contexts such as drawing quantum-classical comparisons is limited by the non-uniqueness of the particular representation. Here we show how the mathematical theory of frames provides a unified formalism which accommodates all known quasi-probability representations of finite-dimensional quantum systems. Moreover, we show that any quasi-probability representation is equivalent to a frame representation and then prove that any such representation of quantum mechanics must exhibit either negativity or a deformed probability calculus. (fast track communication)
Evaluating an animated and static time series map of District Six: A ...
African Journals Online (AJOL)
Visualization of spatial information is an important aspect in the representation of map displays. Maps today are visually adapted to a variety of mediums in displaying spatial information temporally and as time series phenomena. GIS technology has incorporated tools for analysing these spatio-temporal trends. However ...
Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.
Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen
2017-08-29
In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.
Spatial Pyramid Covariance based Compact Video Code for Robust Face Retrieval in TV-series.
Li, Yan; Wang, Ruiping; Cui, Zhen; Shan, Shiguang; Chen, Xilin
2016-10-10
We address the problem of face video retrieval in TV-series which searches video clips based on the presence of specific character, given one face track of his/her. This is tremendously challenging because on one hand, faces in TV-series are captured in largely uncontrolled conditions with complex appearance variations, and on the other hand retrieval task typically needs efficient representation with low time and space complexity. To handle this problem, we propose a compact and discriminative representation for the huge body of video data, named Compact Video Code (CVC). Our method first models the face track by its sample (i.e., frame) covariance matrix to capture the video data variations in a statistical manner. To incorporate discriminative information and obtain more compact video signature suitable for retrieval, the high-dimensional covariance representation is further encoded as a much lower-dimensional binary vector, which finally yields the proposed CVC. Specifically, each bit of the code, i.e., each dimension of the binary vector, is produced via supervised learning in a max margin framework, which aims to make a balance between the discriminability and stability of the code. Besides, we further extend the descriptive granularity of covariance matrix from traditional pixel-level to more general patchlevel, and proceed to propose a novel hierarchical video representation named Spatial Pyramid Covariance (SPC) along with a fast calculation method. Face retrieval experiments on two challenging TV-series video databases, i.e., the Big Bang Theory and Prison Break, demonstrate the competitiveness of the proposed CVC over state-of-the-art retrieval methods. In addition, as a general video matching algorithm, CVC is also evaluated in traditional video face recognition task on a standard Internet database, i.e., YouTube Celebrities, showing its quite promising performance by using an extremely compact code with only 128 bits.
DEFF Research Database (Denmark)
Wulf-Andersen, Trine Østergaard
2012-01-01
, and dialogue, of situated participants. The article includes a lengthy example of a poetic representation of one participant’s story, and the author comments on the potentials of ‘doing’ poetic representations as an example of writing in ways that challenges what sometimes goes unasked in participative social...
Energy Technology Data Exchange (ETDEWEB)
Lieu, Richard [Department of Physics, University of Alabama, Huntsville, AL 35899 (United States)
2017-07-20
A hierarchy of statistics of increasing sophistication and accuracy is proposed to exploit an interesting and fundamental arithmetic structure in the photon bunching noise of incoherent light of large photon occupation number, with the purpose of suppressing the noise and rendering a more reliable and unbiased measurement of the light intensity. The method does not require any new hardware, rather it operates at the software level with the help of high-precision computers to reprocess the intensity time series of the incident light to create a new series with smaller bunching noise coherence length. The ultimate accuracy improvement of this method of flux measurement is limited by the timing resolution of the detector and the photon occupation number of the beam (the higher the photon number the better the performance). The principal application is accuracy improvement in the signal-limited bolometric flux measurement of a radio source.
Lieu, Richard
2018-01-01
A hierarchy of statistics of increasing sophistication and accuracy is proposed, to exploit an interesting and fundamental arithmetic structure in the photon bunching noise of incoherent light of large photon occupation number, with the purpose of suppressing the noise and rendering a more reliable and unbiased measurement of the light intensity. The method does not require any new hardware, rather it operates at the software level, with the help of high precision computers, to reprocess the intensity time series of the incident light to create a new series with smaller bunching noise coherence length. The ultimate accuracy improvement of this method of flux measurement is limited by the timing resolution of the detector and the photon occupation number of the beam (the higher the photon number the better the performance). The principal application is accuracy improvement in the bolometric flux measurement of a radio source.
Fast computation of the roots of polynomials over the ring of power series
DEFF Research Database (Denmark)
Neiger, Vincent; Rosenkilde, Johan; Schost, Éric
2017-01-01
We give an algorithm for computing all roots of polynomials over a univariate power series ring over an exact field K. More precisely, given a precision d, and a polynomial Q whose coefficients are power series in x, the algorithm computes a representation of all power series f(x) such that Q......(f(x)) = 0 mod xd. The algorithm works unconditionally, in particular also with multiple roots, where Newton iteration fails. Our main motivation comes from coding theory where instances of this problem arise and multiple roots must be handled. The cost bound for our algorithm matches the worst-case input...
Podboy, Gary G.; Bridges, James E.; Henderson, Brenda S.
2010-01-01
A 48-microphone planar phased array system was used to acquire jet noise source localization data on both a full-scale F404-GE-F400 engine and on a 1/4th scale model of a F400 series nozzle. The full-scale engine test data show the location of the dominant noise sources in the jet plume as a function of frequency for the engine in both baseline (no chevron) and chevron configurations. Data are presented for the engine operating both with and without afterburners. Based on lessons learned during this test, a set of recommendations are provided regarding how the phased array measurement system could be modified in order to obtain more useful acoustic source localization data on high-performance military engines in the future. The data obtained on the 1/4th scale F400 series nozzle provide useful insights regarding the full-scale engine jet noise source mechanisms, and document some of the differences associated with testing at model-scale versus fullscale.
Convergent Power Series of sech(x and Solutions to Nonlinear Differential Equations
Directory of Open Access Journals (Sweden)
U. Al Khawaja
2018-01-01
Full Text Available It is known that power series expansion of certain functions such as sech(x diverges beyond a finite radius of convergence. We present here an iterative power series expansion (IPS to obtain a power series representation of sech(x that is convergent for all x. The convergent series is a sum of the Taylor series of sech(x and a complementary series that cancels the divergence of the Taylor series for x≥π/2. The method is general and can be applied to other functions known to have finite radius of convergence, such as 1/(1+x2. A straightforward application of this method is to solve analytically nonlinear differential equations, which we also illustrate here. The method provides also a robust and very efficient numerical algorithm for solving nonlinear differential equations numerically. A detailed comparison with the fourth-order Runge-Kutta method and extensive analysis of the behavior of the error and CPU time are performed.
Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.
2018-05-01
The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.
Tischenko, Oleg; Hoeschen, Christoph; Effenberger, Olaf; Reissberg, Steffen; Buhr, Egbert; Doehring, Wilfried
2003-06-01
There are many aspects that influence and deteriorate the detection of pathologies in X-ray images. Some of those are due to effects taking place in the stage of forming the X-ray intensity pattern in front of the x-ray detector. These can be described as motion blurring, depth blurring, anatomical background, scatter noise and structural noise. Structural noise results from an overlapping of fine irrelevant anatomical structures. A method for measuring the combined effect of structural noise and scatter noise was developed and will be presented in this paper. This method is based on the consideration that within a pair of projections created after rotation of the object with a small angle (which is within the typical uncertainty in positioning the patient) both images would show the same relevant structures whereas the projection of the fine overlapping structures will appear quite differently in the two images. To demonstrate the method two X-ray radiographs of a lung phantom were produced. The second radiograph was achieved after rotating the lung by an angle of about 3. Dyadic wavelet representations of both images were regarded. For each value of the wavelet scale parameter the corresponding pair of approximations was matched using the cross correlation matching technique. The homologous regions of approximations were extracted. The image containing only those structures that appear in both images simultaneously was then reconstructed from the wavelet coefficients corresponding to the homologous regions. The difference between one of the original images and the noise-reduced image contains the structural noise and the scatter noise.
Auditory Sketches: Very Sparse Representations of Sounds Are Still Recognizable.
Directory of Open Access Journals (Sweden)
Vincent Isnard
Full Text Available Sounds in our environment like voices, animal calls or musical instruments are easily recognized by human listeners. Understanding the key features underlying this robust sound recognition is an important question in auditory science. Here, we studied the recognition by human listeners of new classes of sounds: acoustic and auditory sketches, sounds that are severely impoverished but still recognizable. Starting from a time-frequency representation, a sketch is obtained by keeping only sparse elements of the original signal, here, by means of a simple peak-picking algorithm. Two time-frequency representations were compared: a biologically grounded one, the auditory spectrogram, which simulates peripheral auditory filtering, and a simple acoustic spectrogram, based on a Fourier transform. Three degrees of sparsity were also investigated. Listeners were asked to recognize the category to which a sketch sound belongs: singing voices, bird calls, musical instruments, and vehicle engine noises. Results showed that, with the exception of voice sounds, very sparse representations of sounds (10 features, or energy peaks, per second could be recognized above chance. No clear differences could be observed between the acoustic and the auditory sketches. For the voice sounds, however, a completely different pattern of results emerged, with at-chance or even below-chance recognition performances, suggesting that the important features of the voice, whatever they are, were removed by the sketch process. Overall, these perceptual results were well correlated with a model of auditory distances, based on spectro-temporal excitation patterns (STEPs. This study confirms the potential of these new classes of sounds, acoustic and auditory sketches, to study sound recognition.
Speckle noise reduction for optical coherence tomography based on adaptive 2D dictionary
Lv, Hongli; Fu, Shujun; Zhang, Caiming; Zhai, Lin
2018-05-01
As a high-resolution biomedical imaging modality, optical coherence tomography (OCT) is widely used in medical sciences. However, OCT images often suffer from speckle noise, which can mask some important image information, and thus reduce the accuracy of clinical diagnosis. Taking full advantage of nonlocal self-similarity and adaptive 2D-dictionary-based sparse representation, in this work, a speckle noise reduction algorithm is proposed for despeckling OCT images. To reduce speckle noise while preserving local image features, similar nonlocal patches are first extracted from the noisy image and put into groups using a gamma- distribution-based block matching method. An adaptive 2D dictionary is then learned for each patch group. Unlike traditional vector-based sparse coding, we express each image patch by the linear combination of a few matrices. This image-to-matrix method can exploit the local correlation between pixels. Since each image patch might belong to several groups, the despeckled OCT image is finally obtained by aggregating all filtered image patches. The experimental results demonstrate the superior performance of the proposed method over other state-of-the-art despeckling methods, in terms of objective metrics and visual inspection.
The effects of noise reduction technologies on the acceptance of background noise.
Lowery, Kristy Jones; Plyler, Patrick N
2013-09-01
Directional microphones (D-Mics) and digital noise reduction (DNR) algorithms are used in hearing aids to reduce the negative effects of background noise on performance. Directional microphones attenuate sounds arriving from anywhere other than the front of the listener while DNR attenuates sounds with physical characteristics of noise. Although both noise reduction technologies are currently available in hearing aids, it is unclear if the use of these technologies in isolation or together affects acceptance of noise and/or preference for the end user when used in various types of background noise. The purpose of the research was to determine the effects of D-Mic, DNR, or the combination of D-Mic and DNR on acceptance of noise and preference when listening in various types of background noise. An experimental study in which subjects were exposed to a repeated measures design was utilized. Thirty adult listeners with mild sloping to moderately severe sensorineural hearing loss participated (mean age 67 yr). Acceptable noise levels (ANLs) were obtained using no noise reduction technologies, D-Mic only, DNR only, and the combination of the two technologies (Combo) for three different background noises (single-talker speech, speech-shaped noise, and multitalker babble) for each listener. In addition, preference rankings of the noise reduction technologies were obtained within each background noise (1 = best, 3 = worst). ANL values were significantly better for each noise reduction technology than baseline; and benefit increased significantly from DNR to D-Mic to Combo. Listeners with higher (worse) baseline ANLs received more benefit from noise reduction technologies than listeners with lower (better) baseline ANLs. Neither ANL values nor ANL benefit values were significantly affected by background noise type; however, ANL benefit with D-Mic and Combo was similar when speech-like noise was present while ANL benefit was greatest for Combo when speech spectrum noise was
Bragdon, C. R.
Airport and community land use planning as they relate to airport noise reduction are discussed. Legislation, community relations, and the physiological effect of airport noise are considered. Noise at the Logan, Los Angeles, and Minneapolis/St. Paul airports is discussed.
Hyperbolic Cross Truncations for Stochastic Fourier Cosine Series
Zhang, Zhihua
2014-01-01
Based on our decomposition of stochastic processes and our asymptotic representations of Fourier cosine coefficients, we deduce an asymptotic formula of approximation errors of hyperbolic cross truncations for bivariate stochastic Fourier cosine series. Moreover we propose a kind of Fourier cosine expansions with polynomials factors such that the corresponding Fourier cosine coefficients decay very fast. Although our research is in the setting of stochastic processes, our results are also new for deterministic functions. PMID:25147842
Are binaural recordings needed for subjective and objective annoyance assessment of traffic noise?
DEFF Research Database (Denmark)
Rodríguez, Estefanía Cortés; Song, Wookeun; Brunskog, Jonas
2011-01-01
Humans are annoyed when they are exposed to environmental noise. Traditional measures such as sound pressure levels may not correlate well with how humans perceive annoyance, therefore it is important to investigate psychoacoustic metrics that may correlate better with the perceived annoyance...... of environmental noise than the A-weighted equivalent sound pressure level. This study examined whether the use of binaural recordings of sound events improves the correlation between the objective metrics and the perceived annoyance, particularly for road traffic noise. Metrics based on measurement with a single...... microphone and on binaural sound field recordings have been examined and compared. In order to acquire data for the subjective perception of annoyance, a series of listening tests has been carried out. It is concluded that binaural loudness metrics from binaural recordings are better correlated...
Challenges in noise removal from Doppler spectra acquired by a continuous-wave lidar
DEFF Research Database (Denmark)
Angelou, Nikolas; Foroughi Abari, Farzad; Mann, Jakob
2012-01-01
are presented. A method for determining the background noise spectrum without interrupting the transmission of the laser beam is described. Moreover, the dependency between the determination of the threshold of a Doppler spectrum with low signal-to-noise ratios and the characteristics of the wind flow......This paper is focused on the required post processing of Doppler spectra, acquired from a continuous-wave coherent lidar at high sampling rates (400 Hz) and under rapid scanning of the laser beam. In particular, the necessary steps followed for extracting the wind speed from such Doppler spectra...... are investigated and a systematic approach for removing the noise is outlined. The suggested post processing procedures are applied to two sample time series acquired by a short-range WindScanner during one second each....
The Influence of Cue Reliability and Cue Representation on Spatial Reorientation in Young Children
Lyons, Ian M.; Huttenlocher, Janellen; Ratliff, Kristin R.
2014-01-01
Previous studies of children's reorientation have focused on cue representation (e.g., whether cues are geometric) as a predictor of performance but have not addressed cue reliability (the regularity of the relation between a given cue and an outcome) as a predictor of performance. Here we address both factors within the same series of…
Covariant representations of nuclear *-algebras
International Nuclear Information System (INIS)
Moore, S.M.
1978-01-01
Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations
Modulator noise suppression in the LISA time-delay interferometric combinations
International Nuclear Information System (INIS)
Tinto, Massimo; Armstrong, J W; Estabrook, Frank B
2008-01-01
Laser Interferometer Space Antenna (LISA) is a mission to detect and study low-frequency cosmic gravitational radiation through its influence on the phases of six modulated laser beams exchanged between three remote spacecraft. We previously showed how the measurements of some 18 time series of relative frequency or phase shifts could be combined (1) to cancel the phase noise of the lasers, (2) to cancel the Doppler fluctuations due to non-inertial motions of the six optical benches and (3) to remove the phase noise of the onboard reference oscillators required to track the photodetector fringes, all the while preserving signals from passing gravitational waves. Here we analyze the effect of the additional noise due to the optical modulators used for removing the phase fluctuations of the onboard reference oscillators. We use the recently measured noise spectrum of an individual modulator (Klipstein et al 2006 Proc. 6th Int. LISA Symp. (Greenbelt, MA) (AIP Conf. Proc. vol 873) ed S M Merkowitz and J C Livas pp 19-23) to quantify the contribution of modulator noise to the first and second-generation time-delay interferometric (TDI) combinations as a function of the modulation frequency. We show that modulator noise can be made smaller than the expected proof-mass acceleration and optical-path noises if the modulation frequencies are larger than ∼682 MHz in the case of the unequal-arm Michelson TDI combination X 1 , ∼ 1.08 GHz for the Sagnac TDI combination α 1 , and ∼706 MHz for the symmetrical Sagnac TDI combination ζ 1 . These modulation frequencies are substantially smaller than previously estimated and may lead to less stringent requirements on the LISA's oscillator noise calibration subsystem. The measurements in Klipstein et al were performed in a laboratory experiment for a range of modulation frequencies, but we emphasize that, for the reference oscillator noise calibration algorithm to work, the modulation frequencies must be equal to the
DEFF Research Database (Denmark)
Loaldi, D.; Calaon, Matteo; Quagliotti, Danilo
, on an injection compression moulded (ICM) Fresnel lens, is defined. A set of two different objectives is considered, i.e. a standard series (SO), against a long working distance one (LWD); two different magnifications objectives, 50x and 100x and the use or not of a dark environment. The noise evaluation...... are measuring working distance, objective magnification and room lighting. The result confirms a strong difference of noise, using the considered objectives. The most interesting result is that the performance of SO 50x objective is better than LWD 100x....
Noise Estimation and Quality Assessment of Gaussian Noise Corrupted Images
Kamble, V. M.; Bhurchandi, K.
2018-03-01
Evaluating the exact quantity of noise present in an image and quality of an image in the absence of reference image is a challenging task. We propose a near perfect noise estimation method and a no reference image quality assessment method for images corrupted by Gaussian noise. The proposed methods obtain initial estimate of noise standard deviation present in an image using the median of wavelet transform coefficients and then obtains a near to exact estimate using curve fitting. The proposed noise estimation method provides the estimate of noise within average error of +/-4%. For quality assessment, this noise estimate is mapped to fit the Differential Mean Opinion Score (DMOS) using a nonlinear function. The proposed methods require minimum training and yields the noise estimate and image quality score. Images from Laboratory for image and Video Processing (LIVE) database and Computational Perception and Image Quality (CSIQ) database are used for validation of the proposed quality assessment method. Experimental results show that the performance of proposed quality assessment method is at par with the existing no reference image quality assessment metric for Gaussian noise corrupted images.
Report on inter-noise 99; Inter-noise 99 sanka hokok
Energy Technology Data Exchange (ETDEWEB)
Koike, H. [Japan Automobile Research Institute Inc., Tsukuba (Japan)
2000-04-01
Inter-Noise (International Congress on Noise Control Engineering) is a society on noise/vibration and the control technology. Inter-Noise 99 was held on December 6, 7 and 8, 1999, at Fort Lauderdale, Florida, the U.S. The theme was Noise Control in the New Millennium. The number of the participants registered was 555 (151 from the U.S., 89 from Japan, 248 from European countries, and 69 from Asian/other countries). Dr. Harold Marshall gave a keynote lecture titled Noise Control by Design in the 21st Century - An Architectural Acoustic Perspective. From a standpoint of architectural acoustics, he stated the perspective, subjects, and course of the technical development pertaining to technologies needed in the 21st century. The papers read are mostly from the following fields: measuring technology, military exercise noise, modeling, forecast and simulation, aerodynamic/underwater sound, etc. In the session on the tire noise where the author read a paper, 14 papers were read. The number of the papers read was more than that in 1998, probably influenced by the tire noise regulation in Europe and Japan. (translated by NEDO)
Noise frame duration, masking potency and whiteness of temporal noise
Kukkonen, Helja; Rovamo, Jyrki; Donner, Kristian; Tammikallio, Marja; Raninen, Antii
2002-01-01
PURPOSE. Because of the limited contrast range, increasing the duration of the noise frame is often the only option for increasing the masking potency of external, white temporal noise. This, however, reduces the high-frequency cutoff beyond which noise is no longer white. This study was conducted to determine the longest noise frame duration that produces the strongest masking effect and still mimics white noise on the detection of sinusoidal flicker. \\ud \\ud METHODS. Contrast energy thresho...
Noise is all around you, from televisions and radios to lawn mowers and washing machines. Normally, you ... sensitive structures of the inner ear and cause noise-induced hearing loss. More than 30 million Americans ...
Yang, Jian-Yi; Peng, Zhen-Ling; Yu, Zu-Guo; Zhang, Rui-Jie; Anh, Vo; Wang, Desheng
2009-04-21
In this paper, we intend to predict protein structural classes (alpha, beta, alpha+beta, or alpha/beta) for low-homology data sets. Two data sets were used widely, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence homology being 40% and 25%, respectively. We propose to decompose the chaos game representation of proteins into two kinds of time series. Then, a novel and powerful nonlinear analysis technique, recurrence quantification analysis (RQA), is applied to analyze these time series. For a given protein sequence, a total of 16 characteristic parameters can be calculated with RQA, which are treated as feature representation of protein sequences. Based on such feature representation, the structural class for each protein is predicted with Fisher's linear discriminant algorithm. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies with step-by-step procedure are 65.8% and 64.2% for 1189 and 25PDB data sets, respectively. With one-against-others procedure used widely, we compare our method with five other existing methods. Especially, the overall accuracies of our method are 6.3% and 4.1% higher for the two data sets, respectively. Furthermore, only 16 parameters are used in our method, which is less than that used by other methods. This suggests that the current method may play a complementary role to the existing methods and is promising to perform the prediction of protein structural classes.
Pilot study of methods and equipment for in-home noise level measurements.
Neitzel, Richard L; Heikkinen, Maire S A; Williams, Christopher C; Viet, Susan Marie; Dellarco, Michael
2015-01-15
Knowledge of the auditory and non-auditory effects of noise has increased dramatically over the past decade, but indoor noise exposure measurement methods have not advanced appreciably, despite the introduction of applicable new technologies. This study evaluated various conventional and smart devices for exposure assessment in the National Children's Study. Three devices were tested: a sound level meter (SLM), a dosimeter, and a smart device with a noise measurement application installed. Instrument performance was evaluated in a series of semi-controlled tests in office environments over 96-hour periods, followed by measurements made continuously in two rooms (a child's bedroom and a most used room) in nine participating homes over a 7-day period with subsequent computation of a range of noise metrics. The SLMs and dosimeters yielded similar A-weighted average noise levels. Levels measured by the smart devices often differed substantially (showing both positive and negative bias, depending on the metric) from those measured via SLM and dosimeter, and demonstrated attenuation in some frequency bands in spectral analysis compared to SLM results. Virtually all measurements exceeded the Environmental Protection Agency's 45 dBA day-night limit for indoor residential exposures. The measurement protocol developed here can be employed in homes, demonstrates the possibility of measuring long-term noise exposures in homes with technologies beyond traditional SLMs, and highlights potential pitfalls associated with measurements made by smart devices.
The role of Urbis' noise and noise effects maps in local policy
Borst, H.C.
2001-01-01
An important aspect of the EU noise policy is mapping of noise and noise effects and the formulation of noise action plans. In the Netherlands, due to the new policy on noise (MIG), the municipalities will be responsible for the formulation of a local noise policy. An instrument for the assessment
Experimental Research into Noise Emission of A Gear Micropump with Plastic Rotor
Rodionov, L. V.; Rekadze, P. D.
2018-01-01
The previous researches show that it’s possible to replace several parts of gear pump to plastic ones. This substitution leads to cost and noise reduction of the pump. Therefore, the series of acoustic experiments on a test bench were carry-out. Sound pressure levels were recorded with microphone, located in a pipe made of a vacuum rubber. Conducted experiment shows that acoustic characteristics of the micropump depend on the different material of driven rotor. Experimental result indicates that the proposed measures for replacing metal rotor to plastic one reduce micropump noise on the studied modes. The maximum achieved acoustic efficiency on equivalent level is 11 dB.
Social Representation of "Loud Music" in Young Adults: A Cross-Cultural Study.
Manchaiah, Vinaya; Zhao, Fei; Widen, Stephen; Auzenne, Jasmin; Beukes, Eldré W; Ahmadi, Tayebeh; Tomé, David; Mahadeva, Deepthi; Krishna, Rajalakshmi; Germundsson, Per
2017-06-01
Exposure to recreational noise, particularly music exposure, is considered one of the biggest public health hazards of our time. Some important influencing factors such as socioeconomic status, educational background, and cross-cultural perspectives have previously been found to be associated with attitudes toward loud music and the use of hearing protection. Although culture seems to play an important role, there is relatively little known about how it influences perceptions regarding loud music exposure in young adults. The present study was aimed to explore cross-cultural perceptions of and reactions to loud music in young adults (18-25 yr) using the theory of social representations. The study used a cross-sectional survey design. The study sample included young adults (n = 534) from five different countries (India, Iran, Portugal, the United States, and the United Kingdom) who were recruited using convenience sampling. Data were collected using a questionnaire. Data were analyzed using a content analysis, co-occurrence analysis, and also χ² analysis. Fairly equal numbers of positive and negative connotations (∼40%) were noted in all countries. However, the χ² analysis showed significant differences between the countries (most positive connotations were found in India and Iran, whereas the most negative connotations were found in the United Kingdom and Portugal) regarding the informants' perception of loud music. The co-occurrence analysis results generally indicate that the category "negative emotions and actions" occurred most frequently, immediately followed by the category "positive emotions and actions." The other most frequently occurring categories included "acoustics," "physical aliment," "location," and "ear and hearing problems." These six categories formed the central nodes of the social representation of loud music exposure in the global index. Although some similarities and differences were noted among the social representations toward loud
Standard model of knowledge representation
Yin, Wensheng
2016-09-01
Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.
Quantifying the role of noise on droplet decisions in bifurcating microchannels
Norouzi Darabad, Masoud; Vaughn, Mark; Vanapalli, Siva
2017-11-01
While many aspects of path selection of droplets flowing through a bifurcating microchannel have been studied, there are still unaddressed issues in predicting and controlling droplet traffic. One of the more important is understanding origin of aperiodic patterns. As a new tool to investigate this phenomena we propose monitoring the continuous time response of pressure fluctuations at different locations. Then we use time-series analysis to investigate the dynamics of the system. We suggest that natural system noise is the cause of irregularity in the traffic patterns. Using a mathematical model, we investigate the effect of noise on droplet decisions at the junction. Noise can be derived from different sources including droplet size variation, droplet spacing, and pump induced velocity fluctuation. By analyzing different situations we explain system behavior. We also investigate the ``memory'' of a microfluidic system in terms of the resistance to perturbations that quantify the allowable deviation in operating condition before the system changes state.
DEFF Research Database (Denmark)
Jeppesen, Palle
1997-01-01
Noise in optical amplifiers is discussed on the basis of photons and electromagntic fields. Formulas for quantum noise from spontaneous emission, signal-spontaneous beat noise and spontaneous-spontaneous beat noise are derived.......Noise in optical amplifiers is discussed on the basis of photons and electromagntic fields. Formulas for quantum noise from spontaneous emission, signal-spontaneous beat noise and spontaneous-spontaneous beat noise are derived....
Evaluation of noise pollution in urban traffic hubs—Noise maps and measurements
International Nuclear Information System (INIS)
Fiedler, Paulo Eduardo Kirrian; Zannin, Paulo Henrique Trombetta
2015-01-01
A study was made of some of the main traffic hubs in a Latin American metropolis, in order to determine the presence or absence of noise by means of noise measurements and acoustic mapping. To characterize noise in the evaluated road stretches, 232 measurements were taken at different points. The Predictor software package was used for the noise mapping calculations. Noise sensitive areas, e.g., hospitals, were identified in the evaluated road stretches. Noise maps were calculated for two hospitals, showing the current levels of noise that reach their facades. Hypothetical scenarios were simulated by making changes in the composition of traffic and total number of vehicles, and an assessment was made of the potential influence of these modifications in reducing the noise levels reaching the facades of the buildings in question. The simulations indicated that a 50% reduction in total traffic flow, or a 50% reduction in heavy vehicle traffic flow, would reduce the noise levels by about 3 dB(A). - Highlights: • Evaluation of noise pollution in urban traffic hubs • Street systems • Environmental noise impacts • Noise mapping
Evaluation of noise pollution in urban traffic hubs—Noise maps and measurements
Energy Technology Data Exchange (ETDEWEB)
Fiedler, Paulo Eduardo Kirrian; Zannin, Paulo Henrique Trombetta, E-mail: paulo.zannin@pesquisador.cnpq.br
2015-02-15
A study was made of some of the main traffic hubs in a Latin American metropolis, in order to determine the presence or absence of noise by means of noise measurements and acoustic mapping. To characterize noise in the evaluated road stretches, 232 measurements were taken at different points. The Predictor software package was used for the noise mapping calculations. Noise sensitive areas, e.g., hospitals, were identified in the evaluated road stretches. Noise maps were calculated for two hospitals, showing the current levels of noise that reach their facades. Hypothetical scenarios were simulated by making changes in the composition of traffic and total number of vehicles, and an assessment was made of the potential influence of these modifications in reducing the noise levels reaching the facades of the buildings in question. The simulations indicated that a 50% reduction in total traffic flow, or a 50% reduction in heavy vehicle traffic flow, would reduce the noise levels by about 3 dB(A). - Highlights: • Evaluation of noise pollution in urban traffic hubs • Street systems • Environmental noise impacts • Noise mapping.
Nonlinear Bayesian Estimation of BOLD Signal under Non-Gaussian Noise
Directory of Open Access Journals (Sweden)
Ali Fahim Khan
2015-01-01
Full Text Available Modeling the blood oxygenation level dependent (BOLD signal has been a subject of study for over a decade in the neuroimaging community. Inspired from fluid dynamics, the hemodynamic model provides a plausible yet convincing interpretation of the BOLD signal by amalgamating effects of dynamic physiological changes in blood oxygenation, cerebral blood flow and volume. The nonautonomous, nonlinear set of differential equations of the hemodynamic model constitutes the process model while the weighted nonlinear sum of the physiological variables forms the measurement model. Plagued by various noise sources, the time series fMRI measurement data is mostly assumed to be affected by additive Gaussian noise. Though more feasible, the assumption may cause the designed filter to perform poorly if made to work under non-Gaussian environment. In this paper, we present a data assimilation scheme that assumes additive non-Gaussian noise, namely, the e-mixture noise, affecting the measurements. The proposed filter MAGSF and the celebrated EKF are put to test by performing joint optimal Bayesian filtering to estimate both the states and parameters governing the hemodynamic model under non-Gaussian environment. Analyses using both the synthetic and real data reveal superior performance of the MAGSF as compared to EKF.
The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools
International Nuclear Information System (INIS)
Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia
2001-01-01
Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components
International Nuclear Information System (INIS)
Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.
2007-01-01
Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)
Xie, Hong-Bo; Dokos, Socrates
2013-06-01
We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.
Furman, Wyndol; Collibee, Charlene
2018-01-01
This study examined how representations of parent-child relationships, friendships, and past romantic relationships are related to subsequent romantic representations. Two-hundred 10th graders (100 female; M age = 15.87 years) from diverse neighborhoods in a Western U.S. city were administered questionnaires and were interviewed to assess avoidant and anxious representations of their relationships with parents, friends, and romantic partners. Participants then completed similar questionnaires and interviews about their romantic representations six more times over the next 7.5 years. Growth curve analyses revealed that representations of relationships with parents, friends, and romantic partners each uniquely predicted subsequent romantic representations across development. Consistent with attachment and behavioral systems theory, representations of romantic relationships are revised by representations and experiences in other relationships. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.
Adaptive EMG noise reduction in ECG signals using noise level approximation
Marouf, Mohamed; Saranovac, Lazar
2017-12-01
In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.
The Assessment of Noise Exposure and Noise Annoyance at a Petrochemical Company
Directory of Open Access Journals (Sweden)
S. Farhang Dehghan
2013-12-01
.Conclusion: Based on the obtained results of investigating the noise level (objective exposure as well as the noise annoyance (subjective exposure at the studied company, it is necessary to adopt the management –technical noise reduction measures at manufacturing sectors as the personal noise exposure and environmental noise exposure and also noise personal exposure of administrative staff can be decreased.
Noise pollution resources compendium
1973-01-01
Abstracts of reports concerning noise pollution are presented. The abstracts are grouped in the following areas of activity: (1) sources of noise, (2) noise detection and measurement, (3) noise abatement and control, (4) physical effects of noise and (5) social effects of noise.
Elgaroy, E O
2013-01-01
Solar Noise Storms examines the properties and features of solar noise storm phenomenon. The book also presents some theories that can be used to gain a better understanding of the phenomenon. The coverage of the text includes topics that cover the features and behavior of noise storms, such as the observable features of noise storms; the relationship between noise storms and the observable features on the sun; and ordered behavior of storm bursts in the time-frequency plane. The book also covers the spectrum, polarization, and directivity of noise storms. The text will be of great use to astr
Low noise constant current source for bias dependent noise measurements
International Nuclear Information System (INIS)
Talukdar, D.; Bose, Suvendu; Bardhan, K. K.; Chakraborty, R. K.
2011-01-01
A low noise constant current source used for measuring the 1/f noise in disordered systems in ohmic as well as nonohmic regime is described. The source can supply low noise constant current starting from as low as 1 μA to a few tens of milliampere with a high voltage compliance limit of around 20 V. The constant current source has several stages, which can work in a standalone manner or together to supply the desired value of load current. The noise contributed by the current source is very low in the entire current range. The fabrication of a low noise voltage preamplifier modified for bias dependent noise measurements and based on the existing design available in the MAT04 data sheet is also described.
Closed-Loop Dynamic Parameter Identification of Robot Manipulators Using Modified Fourier Series
Directory of Open Access Journals (Sweden)
Wenxiang Wu
2012-05-01
Full Text Available This paper concerns the problem of dynamic parameter identification of robot manipulators and proposes a closed-loop identification procedure using modified Fourier series (MFS as exciting trajectories. First, a static continuous friction model is involved to model joint friction for realizable friction compensation in controller design. Second, MFS satisfying the boundary conditions are firstly designed as periodic exciting trajectories. To minimize the sensitivity to measurement noise, the coefficients of MFS are optimized according to the condition number criterion. Moreover, to obtain accurate parameter estimates, the maximum likelihood estimation (MLE method considering the influence of measurement noise is adopted. The proposed identification procedure has been implemented on the first three axes of the QIANJIANG-I 6-DOF robot manipulator. Experiment results verify the effectiveness of the proposed approach, and comparison between identification using MFS and that using finite Fourier series (FFS reveals that the proposed method achieves better identification accuracy.
A technique for filling gaps in time series with complicated power spectra
International Nuclear Information System (INIS)
Brown, T.M.
1984-01-01
Fahlman and Ulrych (1982) describe a method for estimating the power and phase spectra of gapped time series, using a maximum-entropy reconstruction of the data in the gaps. It has proved difficult to apply this technique to solar oscillations data, because of the great complexity of the solar oscillations spectrum. We describe a means for avoiding this difficulty, and report the results of a series of blind tests of the modified technique. The main results of these tests are: 1. Gap-filling gives good results, provided that the signal-to-noise ration in the original data is large enough, and provided the gaps are short enough. For low-noise data, the duty cycle of the observations should not be less than about 50%. 2. The frequencies and widths of narrow spectrum features are well reproduced by the technique. 3. The technique systematically reduces the apparent amplitudes of small features in the spectrum relative to large ones. (orig.)
A neural network for noise correlation classification
Paitz, Patrick; Gokhberg, Alexey; Fichtner, Andreas
2018-02-01
We present an artificial neural network (ANN) for the classification of ambient seismic noise correlations into two categories, suitable and unsuitable for noise tomography. By using only a small manually classified data subset for network training, the ANN allows us to classify large data volumes with low human effort and to encode the valuable subjective experience of data analysts that cannot be captured by a deterministic algorithm. Based on a new feature extraction procedure that exploits the wavelet-like nature of seismic time-series, we efficiently reduce the dimensionality of noise correlation data, still keeping relevant features needed for automated classification. Using global- and regional-scale data sets, we show that classification errors of 20 per cent or less can be achieved when the network training is performed with as little as 3.5 per cent and 16 per cent of the data sets, respectively. Furthermore, the ANN trained on the regional data can be applied to the global data, and vice versa, without a significant increase of the classification error. An experiment where four students manually classified the data, revealed that the classification error they would assign to each other is substantially larger than the classification error of the ANN (>35 per cent). This indicates that reproducibility would be hampered more by human subjectivity than by imperfections of the ANN.
Pan, Feng; Yang, Lizhi; Xiao, Wen
2017-09-04
In digital holographic microscopy (DHM), it is undesirable to observe coherent noise in the reconstructed images. The sources of the noise are mainly the parasitic interference fringes caused by multiple reflections and the speckle pattern caused by the optical scattering on the object surface. Here we propose a noise reduction approach in DHM by averaging multiple holograms recorded with a multimode laser. Based on the periodicity of the temporal coherence of a multimode semiconductor laser, we acquire a series of holograms by changing the optical path length difference between the reference beam and object beam. Because of the use of low coherence light, we can remove the parasitic interference fringes caused by multiple reflections in the holograms. In addition, the coherent noise patterns change in this process due to the different optical paths. Therefore, the coherent noise can be reduced by averaging the multiple reconstructions with uncorrelated noise patterns. Several experiments have been carried out to validate the effectiveness of the proposed approach for coherent noise reduction in DHM. It is shown a remarkable improvement both in amplitude imaging quality and phase measurement accuracy.
International Nuclear Information System (INIS)
Fan Hongyi; Wang Yong
2006-01-01
With the help of Bose operator identities and entangled state representation and based on our previous work [Phys. Lett. A 325 (2004) 188] we derive some new generalized Bessel equations which also have Bessel function as their solution. It means that for these intricate higher-order differential equations, we can get Bessel function solutions without using the expatiatory power-series expansion method.
Representation of the Coulomb Matrix Elements by Means of Appell Hypergeometric Function F 2
Bentalha, Zine el abidine
2018-06-01
Exact analytical representation for the Coulomb matrix elements by means of Appell's double series F 2 is derived. The finite sum obtained for the Appell function F 2 allows us to evaluate explicitly the matrix elements of the two-body Coulomb interaction in the lowest Landau level. An application requiring the matrix elements of Coulomb potential in quantum Hall effect regime is presented.
Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism
Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G.
2015-04-01
We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation.
Spatiotemporal chaos in rf-driven Josephson junction series arrays
International Nuclear Information System (INIS)
Dominguez, D.; Cerdeira, H.A.
1995-01-01
We study underdamped Josephson junction series arrays that are globally coupled through a resistive shunting load and driven by an rf bias current. They can be an experimental realization of many phenomena currently studied in globally coupled logistic maps. We study their spatiotemporal dynamics and we find coherent, ordered, partially ordered, turbulent, and quasiperiodic phases. The ordered phase corresponds to giant Shapiro steps in the IV characteristics. In the turbulent phase there is a saturation of the broad-band noise for a large number of junctions. This corresponds to a breakdown of the law of large numbers as seen in globally coupled maps. Coexisting with this phenomenon, we find an emergence of pseudosteps in the IV characteristics. This effect can be experimentally distinguished from the true Shapiro steps, which do not have broad-band noise emission. We study the stability of the breakdown of the law of large numbers against thermal fluctuations. We find that it is stable below a critical temperature T c1 . A measurement of the broad-band noise as a function of temperature T will show three different regimes: below T c1 the broad-band noise decreases when increasing T, and there is turbulence and the breakdown of the law of large numbers. Between T c1 and a second critical temperature T c2 the broad-band noise is constant and the dynamics is dominated by the chaos of the individual junctions. Finally above T c2 all the broad-band noise is due to thermal fluctuations, since it increases linearly with T
Proceedings of the 2009 spring noise conference : noise awareness : supporting sound partnerships
International Nuclear Information System (INIS)
2009-01-01
This conference provided a forum for industry, government, public, academics and acoustical professionals to discuss innovations in environmental and occupational noise identification, measurement, regulation and control. In addition to raising awareness about expanding noise issues, the conference objectives were to promote responsible industrial development and to identify strategies for reducing workplace noise exposure. The papers focused on research, developments and case studies and highlighted current issues and advancements in technology and software. Speakers from around the world discussed topics ranging from occupational noise issues to low frequency. The 8 sessions were entitled: (1) plenary session, (2) architecture, community planning and public health: effects of noise and noise control, (3) modeling, measurement and technology; (4) noise awareness and education: public, occupational and industrial, (5) regulations and economics: bylaws, legislation and the economics of noise control; (6) student papers, (7) vibration, industrial noise, transportation noise and occupational noise control, and (8) lunch speakers. The conference featured 46 presentations, of which 19 have been catalogued separately for inclusion in this database. refs., tabs., figs.
Noise in strong laser-atom interactions: Phase telegraph noise
International Nuclear Information System (INIS)
Eberly, J.H.; Wodkiewicz, K.; Shore, B.W.
1984-01-01
We discuss strong laser-atom interactions that are subjected to jump-type (random telegraph) random-phase noise. Physically, the jumps may arise from laser fluctuations, from collisions of various kinds, or from other external forces. Our discussion is carried out in two stages. First, direct and partially heuristic calculations determine the laser spectrum and also give a third-order differential equation for the average inversion of a two-level atom on resonance. At this stage a number of general features of the interaction are able to be studied easily. The optical analog of motional narrowing, for example, is clearly predicted. Second, we show that the theory of generalized Poisson processes allows laser-atom interactions in the presence of random telegraph noise of all kinds (not only phase noise) to be treated systematically, by means of a master equation first used in the context of quantum optics by Burshtein. We use the Burshtein equation to obtain an exact expression for the two-level atom's steady-state resonance fluorescence spectrum, when the exciting laser exhibits phase telegraph noise. Some comparisons are made with results obtained from other noise models. Detailed treatments of the effects ofmly jumps, or as a model of finite laser bandwidth effects, in which the laser frequency exhibits random jumps. We show that these two types of frequency noise can be distinguished in light-scattering spectra. We also discuss examples which demonstrate both temporal and spectral motional narrowing, nonexponential correlations, and non-Lorentzian spectra. Its exact solubility in finite terms makes the frequency-telegraph noise model an attractive alternative to the white-noise Ornstein-Uhlenbeck frequency noise model which has been previously applied to laser-atom interactions
Time series analysis of the developed financial markets' integration using visibility graphs
Zhuang, Enyu; Small, Michael; Feng, Gang
2014-09-01
A time series representing the developed financial markets' segmentation from 1973 to 2012 is studied. The time series reveals an obvious market integration trend. To further uncover the features of this time series, we divide it into seven windows and generate seven visibility graphs. The measuring capabilities of the visibility graphs provide means to quantitatively analyze the original time series. It is found that the important historical incidents that influenced market integration coincide with variations in the measured graphical node degree. Through the measure of neighborhood span, the frequencies of the historical incidents are disclosed. Moreover, it is also found that large "cycles" and significant noise in the time series are linked to large and small communities in the generated visibility graphs. For large cycles, how historical incidents significantly affected market integration is distinguished by density and compactness of the corresponding communities.
Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation
Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.
2012-01-01
Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.
Helsy, I.; Maryamah; Farida, I.; Ramdhani, M. A.
2017-09-01
This study aimed to describe the application of teaching materials, analyze the increase in the ability of students to connect the three levels of representation and student responses after application of multiple representations based teaching materials chemistry. The method used quasi one-group pretest-posttest design to 71 students. The results showed the application of teaching materials carried 88% with very good category. A significant increase ability to connect the three levels of representation of students after the application of multiple representations based teaching materials chemistry with t-value > t-crit (11.402 > 1.991). Recapitulation N-gain pretest and posttest showed relatively similar for all groups is 0.6 criterion being achievement. Students gave a positive response to the application of multiple representations based teaching materials chemistry. Students agree teaching materials used in teaching chemistry (88%), and agrees teaching materials to provide convenience in connecting the three levels of representation (95%).
Classical noise, quantum noise and secure communication
International Nuclear Information System (INIS)
Tannous, C; Langlois, J
2016-01-01
Secure communication based on message encryption might be performed by combining the message with controlled noise (called pseudo-noise) as performed in spread-spectrum communication used presently in Wi-Fi and smartphone telecommunication systems. Quantum communication based on entanglement is another route for securing communications as demonstrated by several important experiments described in this work. The central role played by the photon in unifying the description of classical and quantum noise as major ingredients of secure communication systems is highlighted and described on the basis of the classical and quantum fluctuation dissipation theorems. (review)
Threshold-based system for noise detection in multilead ECG recordings
International Nuclear Information System (INIS)
Jekova, Irena; Krasteva, Vessela; Christov, Ivaylo; Abächerli, Roger
2012-01-01
This paper presents a system for detection of the most common noise types seen on the electrocardiogram (ECG) in order to evaluate whether an episode from 12-lead ECG is reliable for diagnosis. It implements criteria for estimation of the noise corruption level in specific frequency bands, aiming to identify the main sources of ECG quality disruption, such as missing signal or limited dynamics of the QRS components above 4 Hz; presence of high amplitude and steep artifacts seen above 1 Hz; baseline drift estimated at frequencies below 1 Hz; power–line interference in a band ±2 Hz around its central frequency; high-frequency and electromyographic noises above 20 Hz. All noise tests are designed to process the ECG series in the time domain, including 13 adjustable thresholds for amplitude and slope criteria which are evaluated in adjustable time intervals, as well as number of leads. The system allows flexible extension toward application-specific requirements for the noise levels in acceptable quality ECGs. Training of different thresholds’ settings to determine different positive noise detection rates is performed with the annotated set of 1000 ECGs from the PhysioNet database created for the Computing in Cardiology Challenge 2011. Two implementations are highlighted on the receiver operating characteristic (area 0.968) to fit to different applications. The implementation with high sensitivity (Se = 98.7%, Sp = 80.9%) appears as a reliable alarm when there are any incidental problems with the ECG acquisition, while the implementation with high specificity (Sp = 97.8%, Se = 81.8%) is less susceptible to transient problems but rather validates noisy ECGs with acceptable quality during a small portion of the recording. (paper)
Representation of individual elements of a complex call sequence in primary auditory cortex
Directory of Open Access Journals (Sweden)
Mark Nelson Wallace
2013-10-01
Full Text Available Conspecific communication calls can be rhythmic or contain extended, discontinuous series of either constant or frequency modulated harmonic tones and noise bursts separated by brief periods of silence. In the guinea pig, rhythmic calls can produce isomorphic responses within the primary auditory cortex (AI where single units respond to every call element. Other calls such as the chutter comprise a series of short irregular syllables that vary in their spectral content and are more like human speech. These calls can also evoke isomorphic responses, but may only do so in fields in the auditory belt and not in AI. Here we present evidence that cells in AI treat the individual elements within a syllable as separate auditory objects and respond selectively to one or a subset of them. We used a single chutter exemplar to compare single/multi-unit responses in the low-frequency portion of AI - AI(LF and the low-frequency part of the thalamic medial geniculate body - MGB(LF in urethane anaesthetised guinea pigs. Both thalamic and cortical cells responded with brief increases in firing rate to one, or more, of the 8 main elements present in the chutter call. Almost none of the units responded to all 8 elements. While there were many different combinations of responses to between one and five of the elements, MBG(LF and AI(LF neurons exhibited the same specific types of response combinations. Nearby units in the upper layers of the cortex tended to respond to similar combinations of elements while the deep layers were less responsive. Thus the responses from a number of AI units would need to be combined in order to represent the entire chutter call. Our results don’t rule out the possibility of constructive convergence but there was no evidence that a convergence of inputs within AI led to a complete representation of all eight elements.
On signal design by the R/0/ criterion for non-white Gaussian noise channels
Bordelon, D. L.
1977-01-01
The use of the cut-off rate criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate for vector channels with additive non-white Gaussian noise and unquantized demodulation is derived. When the signal input to the channel is a continuous random vector, maximization of the cut-off rate with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize the cut-off rate with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. As an example, the rectangular signal set which has the water-filling average energy distribution and the optimum rectangular set are compared.
Introduction to computer data representation
Fenwick, Peter
2014-01-01
Introduction to Computer Data Representation introduces readers to the representation of data within computers. Starting from basic principles of number representation in computers, the book covers the representation of both integer and floating point numbers, and characters or text. It comprehensively explains the main techniques of computer arithmetic and logical manipulation. The book also features chapters covering the less usual topics of basic checksums and 'universal' or variable length representations for integers, with additional coverage of Gray Codes, BCD codes and logarithmic repre