Parametric time-frequency domain spatial audio
Delikaris-Manias, Symeon; Politis, Archontis
2018-01-01
This book provides readers with the principles and best practices in spatial audio signal processing. It describes how sound fields and their perceptual attributes are captured and analyzed within the time-frequency domain, how essential representation parameters are coded, and how such signals are efficiently reproduced for practical applications. The book is split into four parts starting with an overview of the fundamentals. It then goes on to explain the reproduction of spatial sound before offering an examination of signal-dependent spatial filtering. The book finishes with coverage of both current and future applications and the direction that spatial audio research is heading in. Parametric Time-frequency Domain Spatial Audio focuses on applications in entertainment audio, including music, home cinema, and gaming--covering the capturing and reproduction of spatial sound as well as its generation, transduction, representation, transmission, and perception. This book will teach readers the tools needed...
Estimation of modal parameters using bilinear joint time frequency distributions
Roshan-Ghias, A.; Shamsollahi, M. B.; Mobed, M.; Behzad, M.
2007-07-01
In this paper, a new method is proposed for modal parameter estimation using time-frequency representations. Smoothed Pseudo Wigner-Ville distribution which is a member of the Cohen's class distributions is used to decouple vibration modes completely in order to study each mode separately. This distribution reduces cross-terms which are troublesome in Wigner-Ville distribution and retains the resolution as well. The method was applied to highly damped systems, and results were superior to those obtained via other conventional methods.
Aircraft Fault Detection Using Real-Time Frequency Response Estimation
Grauer, Jared A.
2016-01-01
A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.
International Nuclear Information System (INIS)
Xu Chaoyang; Liu Junmin; Fan Yanfang; Ji Guohua
2008-01-01
Joint time-frequency analysis is conducted to construct one joint density function of time and frequency. It can open out one signal's frequency components and their evolvements. It is the new evolvement of Fourier analysis. In this paper, according to the characteristic of seismic signal's noise, one estimation method of seismic signal's first arrival based on triple correlation of joint time-frequency spectrum is introduced, and the results of experiment and conclusion are presented. (authors)
Hu, L; Zhang, Z G; Mouraux, A; Iannetti, G D
2015-05-01
Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical
PHAZE, Parametric Hazard Function Estimation
International Nuclear Information System (INIS)
2002-01-01
1 - Description of program or function: Phaze performs statistical inference calculations on a hazard function (also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking of the model assumptions. 2 - Methods: PHAZE assumes that the failures of a component follow a time-dependent (or non-homogenous) Poisson process and that the failure counts in non-overlapping time intervals are independent. Implicit in the independence property is the assumption that the component is restored to service immediately after any failure, with negligible repair time. The failures of one component are assumed to be independent of those of another component; a proportional hazards model is used. Data for a component are called time censored if the component is observed for a fixed time-period, or plant records covering a fixed time-period are examined, and the failure times are recorded. The number of these failures is random. Data are called failure censored if the component is kept in service until a predetermined number of failures has occurred, at which time the component is removed from service. In this case, the number of failures is fixed, but the end of the observation period equals the final failure time and is random. A typical PHAZE session consists of reading failure data from a file prepared previously, selecting one of the three models, and performing data analysis (i.e., performing the usual statistical inference about the parameters of the model, with special emphasis on the parameter(s) that determine whether the hazard function is increasing). The final goals of the inference are a point estimate
Variance in parametric images: direct estimation from parametric projections
International Nuclear Information System (INIS)
Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.
2000-01-01
Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)
Non-Parametric Estimation of Correlation Functions
DEFF Research Database (Denmark)
Brincker, Rune; Rytter, Anders; Krenk, Steen
In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...
Cai, Jianhua
2017-05-01
The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.
Peláez-Coca, M. D.; Orini, M.; Lázaro, J.; Bailón, R.; Gil, E.
2013-01-01
A methodology that combines information from several nonstationary biological signals is presented. This methodology is based on time-frequency coherence, that quantifies the similarity of two signals in the time-frequency domain. A cross time-frequency analysis method, based on quadratic time-frequency distribution, has been used for combining information of several nonstationary biomedical signals. In order to evaluate this methodology, the respiratory rate from the photoplethysmographic (PPG) signal is estimated. The respiration provokes simultaneous changes in the pulse interval, amplitude, and width of the PPG signal. This suggests that the combination of information from these sources will improve the accuracy of the estimation of the respiratory rate. Another target of this paper is to implement an algorithm which provides a robust estimation. Therefore, respiratory rate was estimated only in those intervals where the features extracted from the PPG signals are linearly coupled. In 38 spontaneous breathing subjects, among which 7 were characterized by a respiratory rate lower than 0.15 Hz, this methodology provided accurate estimates, with the median error {0.00; 0.98} mHz ({0.00; 0.31}%) and the interquartile range error {4.88; 6.59} mHz ({1.60; 1.92}%). The estimation error of the presented methodology was largely lower than the estimation error obtained without combining different PPG features related to respiration. PMID:24363777
Directory of Open Access Journals (Sweden)
M. D. Peláez-Coca
2013-01-01
Full Text Available A methodology that combines information from several nonstationary biological signals is presented. This methodology is based on time-frequency coherence, that quantifies the similarity of two signals in the time-frequency domain. A cross time-frequency analysis method, based on quadratic time-frequency distribution, has been used for combining information of several nonstationary biomedical signals. In order to evaluate this methodology, the respiratory rate from the photoplethysmographic (PPG signal is estimated. The respiration provokes simultaneous changes in the pulse interval, amplitude, and width of the PPG signal. This suggests that the combination of information from these sources will improve the accuracy of the estimation of the respiratory rate. Another target of this paper is to implement an algorithm which provides a robust estimation. Therefore, respiratory rate was estimated only in those intervals where the features extracted from the PPG signals are linearly coupled. In 38 spontaneous breathing subjects, among which 7 were characterized by a respiratory rate lower than 0.15 Hz, this methodology provided accurate estimates, with the median error {0.00; 0.98} mHz ({0.00; 0.31}% and the interquartile range error {4.88; 6.59} mHz ({1.60; 1.92}%. The estimation error of the presented methodology was largely lower than the estimation error obtained without combining different PPG features related to respiration.
Semi-parametric estimation for ARCH models
Directory of Open Access Journals (Sweden)
Raed Alzghool
2018-03-01
Full Text Available In this paper, we conduct semi-parametric estimation for autoregressive conditional heteroscedasticity (ARCH model with Quasi likelihood (QL and Asymptotic Quasi-likelihood (AQL estimation methods. The QL approach relaxes the distributional assumptions of ARCH processes. The AQL technique is obtained from the QL method when the process conditional variance is unknown. We present an application of the methods to a daily exchange rate series. Keywords: ARCH model, Quasi likelihood (QL, Asymptotic Quasi-likelihood (AQL, Martingale difference, Kernel estimator
On Algebraic Approach for MSD Parametric Estimation
Oueslati , Marouene; Thiery , Stéphane; Gibaru , Olivier; Béarée , Richard; Moraru , George
2011-01-01
This article address the identification problem of the natural frequency and the damping ratio of a second order continuous system where the input is a sinusoidal signal. An algebra based approach for identifying parameters of a Mass Spring Damper (MSD) system is proposed and compared to the Kalman-Bucy filter. The proposed estimator uses the algebraic parametric method in the frequency domain yielding exact formula, when placed in the time domain to identify the unknown parameters. We focus ...
Parametric cost estimation for space science missions
Lillie, Charles F.; Thompson, Bruce E.
2008-07-01
Cost estimation for space science missions is critically important in budgeting for successful missions. The process requires consideration of a number of parameters, where many of the values are only known to a limited accuracy. The results of cost estimation are not perfect, but must be calculated and compared with the estimates that the government uses for budgeting purposes. Uncertainties in the input parameters result from evolving requirements for missions that are typically the "first of a kind" with "state-of-the-art" instruments and new spacecraft and payload technologies that make it difficult to base estimates on the cost histories of previous missions. Even the cost of heritage avionics is uncertain due to parts obsolescence and the resulting redesign work. Through experience and use of industry best practices developed in participation with the Aerospace Industries Association (AIA), Northrop Grumman has developed a parametric modeling approach that can provide a reasonably accurate cost range and most probable cost for future space missions. During the initial mission phases, the approach uses mass- and powerbased cost estimating relationships (CER)'s developed with historical data from previous missions. In later mission phases, when the mission requirements are better defined, these estimates are updated with vendor's bids and "bottoms- up", "grass-roots" material and labor cost estimates based on detailed schedules and assigned tasks. In this paper we describe how we develop our CER's for parametric cost estimation and how they can be applied to estimate the costs for future space science missions like those presented to the Astronomy & Astrophysics Decadal Survey Study Committees.
A power filter for the detection of burst events based on time-frequency spectrum estimation
International Nuclear Information System (INIS)
Guidi, G M; Cuoco, E; Vicere, A
2004-01-01
We propose as a statistic for the detection of bursts in a gravitational wave interferometer the 'energy' of the events estimated with a time-dependent calculation of the spectrum. This statistic has an asymptotic Gaussian distribution with known statistical moments, which makes it possible to perform a uniformly most powerful test (McDonough R N and Whalen A D 1995 Detection of Signals in Noise (New York: Academic)) on the energy mean. We estimate the receiver operating characteristic (ROC, from the same book) of this statistic for different levels of the signal-to-noise ratio in the specific case of a simulated noise having the spectral density expected for Virgo, using test signals taken from a library of possible waveforms emitted during the collapse of the core of type II supernovae
2014-06-17
100 0 2 4 Wigner distribution 0 50 100 0 0.5 1 Auto-correlation function 0 50 100 0 2 4 L- Wigner distribution 0 50 100 0 0.5 1 Auto-correlation function ...bilinear or higher order autocorrelation functions will increase the number of missing samples, the analysis shows that accurate instantaneous...frequency estimation can be achieved even if we deal with only few samples, as long as the auto-correlation function is properly chosen to coincide with
Directory of Open Access Journals (Sweden)
Liu KJ Ray
2002-01-01
Full Text Available Orthogonal frequency division multiplexing (OFDM is an effective technique for the future 3G communications because of its great immunity to impulse noise and intersymbol interference. The channel estimation is a crucial aspect in the design of OFDM systems. In this work, we propose a channel estimation algorithm based on a time-frequency polynomial model of the fading multipath channels. The algorithm exploits the correlation of the channel responses in both time and frequency domains and hence reduce more noise than the methods using only time or frequency polynomial model. The estimator is also more robust compared to the existing methods based on Fourier transform. The simulation shows that it has more than improvement in terms of mean-squared estimation error under some practical channel conditions. The algorithm needs little prior knowledge about the delay and fading properties of the channel. The algorithm can be implemented recursively and can adjust itself to follow the variation of the channel statistics.
de-Graft Acquah, Henry
2014-01-01
This paper highlights the sensitivity of technical efficiency estimates to estimation approaches using empirical data. Firm specific technical efficiency and mean technical efficiency are estimated using the non parametric Data Envelope Analysis (DEA) and the parametric Corrected Ordinary Least Squares (COLS) and Stochastic Frontier Analysis (SFA) approaches. Mean technical efficiency is found to be sensitive to the choice of estimation technique. Analysis of variance and Tukeyâ€™s test sugge...
Parametric Cost Estimates for an International Competitive Edge
International Nuclear Information System (INIS)
Murphy, L.T.; Hickey, M.
2006-01-01
This paper summarizes the progress to date by CH2M HILL and the UKAEA in development of a parametric modelling capability for estimating the costs of large nuclear decommissioning projects in the United Kingdom (UK) and Europe. The ability to successfully apply parametric cost estimating techniques will be a key factor to commercial success in the UK and European multi-billion dollar waste management, decommissioning and environmental restoration markets. The most useful parametric models will be those that incorporate individual components representing major elements of work: reactor decommissioning, fuel cycle facility decommissioning, waste management facility decommissioning and environmental restoration. Models must be sufficiently robust to estimate indirect costs and overheads, permit pricing analysis and adjustment, and accommodate the intricacies of international monetary exchange, currency fluctuations and contingency. The development of a parametric cost estimating capability is also a key component in building a forward estimating strategy. The forward estimating strategy will enable the preparation of accurate and cost-effective out-year estimates, even when work scope is poorly defined or as yet indeterminate. Preparation of cost estimates for work outside the organizations current sites, for which detailed measurement is not possible and historical cost data does not exist, will also be facilitated. (authors)
Kernel bandwidth estimation for non-parametric density estimation: a comparative study
CSIR Research Space (South Africa)
Van der Walt, CM
2013-12-01
Full Text Available We investigate the performance of conventional bandwidth estimators for non-parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of these estimators in high...
Estimation of Parametric Fault in Closed-loop Systems
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
2015-01-01
The aim of this paper is to present a method for estimation of parametric faults in closed-loop systems. The key technology applied in this paper is coprime factorization of both the dynamic system as well as the feedback controller. Using the Youla-Jabr-Bongiorno-Kucera (YJBK) parameterization...
Parametric Bayesian Estimation of Differential Entropy and Relative Entropy
Gupta; Srivastava
2010-01-01
Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform, Gaussian, Wishart, and inverse Wishart distributions. Additionally, formulas are given for a log gamma Bregman divergence and the differential entropy and relative entropy for the Wishart and inverse Wishart. The results, as always with Bayesian est...
Parametric estimation for reinforced concrete relief shelter for Aceh cases
Atthaillah; Saputra, Eri; Iqbal, Muhammad
2018-05-01
This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.
International Nuclear Information System (INIS)
Park, Jin Ho; Lee, Jeong Han; Choi, Young Chul; Kim, Chan Joong; Seong, Poong Hyun
2005-01-01
It has been reviewed whether it would be suitable that the application of the time-frequency signal analysis techniques to estimate the location of the impact source in plate structure. The STFT(Short Time Fourier Transform), WVD(Wigner-Ville distribution) and CWT(Continuous Wavelet Transform) methods are introduced and the advantages and disadvantages of those methods are described by using a simulated signal component. The essential of the above proposed techniques is to separate the traveling waves in both time and frequency domains using the dispersion characteristics of the structural waves. These time-frequency methods are expected to be more useful than the conventional time domain analyses for the impact localization problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the location estimation in a noisy environment
Parametric Bayesian Estimation of Differential Entropy and Relative Entropy
Directory of Open Access Journals (Sweden)
Maya Gupta
2010-04-01
Full Text Available Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform, Gaussian, Wishart, and inverse Wishart distributions. Additionally, formulas are given for a log gamma Bregman divergence and the differential entropy and relative entropy for the Wishart and inverse Wishart. The results, as always with Bayesian estimates, depend on the accuracy of the prior parameters, but example simulations show that the performance can be substantially improved compared to maximum likelihood or state-of-the-art nonparametric estimators.
Non-parametric estimation of the individual's utility map
Noguchi, Takao; Sanborn, Adam N.; Stewart, Neil
2013-01-01
Models of risky choice have attracted much attention in behavioural economics. Previous research has repeatedly demonstrated that individuals' choices are not well explained by expected utility theory, and a number of alternative models have been examined using carefully selected sets of choice alternatives. The model performance however, can depend on which choice alternatives are being tested. Here we develop a non-parametric method for estimating the utility map over the wide range of choi...
A novel SURE-based criterion for parametric PSF estimation.
Xue, Feng; Blu, Thierry
2015-02-01
We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.
A non-parametric framework for estimating threshold limit values
Directory of Open Access Journals (Sweden)
Ulm Kurt
2005-11-01
Full Text Available Abstract Background To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. Methods We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. Results In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. Conclusion The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.
DEFF Research Database (Denmark)
Montazeri, Najmeh; Nielsen, Ulrik Dam
2014-01-01
the ship’s wave-induced responses based on different statistical inferences including parametric and non-parametric approaches. This paper considers a concept to improve the estimate obtained by the parametric method for sea state estimation. The idea is illustrated by an analysis made on full-scale...
Parametric estimation of time varying baselines in airborne interferometric SAR
DEFF Research Database (Denmark)
Mohr, Johan Jacob; Madsen, Søren Nørvang
1996-01-01
A method for estimation of time varying spatial baselines in airborne interferometric synthetic aperture radar (SAR) is described. The range and azimuth distortions between two images acquired with a non-linear baseline are derived. A parametric model of the baseline is then, in a least square...... sense, estimated from image shifts obtained by cross correlation of numerous small patches throughout the image. The method has been applied to airborne EMISAR imagery from the 1995 campaign over the Storstrommen Glacier in North East Greenland conducted by the Danish Center for Remote Sensing. This has...... reduced the baseline uncertainties from several meters to the centimeter level in a 36 km scene. Though developed for airborne SAR the method can easily be adopted to satellite data...
Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models
Directory of Open Access Journals (Sweden)
Marius Pesavento
2004-08-01
Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.
Discrete non-parametric kernel estimation for global sensitivity analysis
International Nuclear Information System (INIS)
Senga Kiessé, Tristan; Ventura, Anne
2016-01-01
This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.
Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, J.G.P.W.; Camps-Valls, Gustau; Moreno, José
2015-01-01
Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC),
Linear minimax estimation for random vectors with parametric uncertainty
Bitar, E
2010-06-01
In this paper, we take a minimax approach to the problem of computing a worst-case linear mean squared error (MSE) estimate of X given Y , where X and Y are jointly distributed random vectors with parametric uncertainty in their distribution. We consider two uncertainty models, PA and PB. Model PA represents X and Y as jointly Gaussian whose covariance matrix Λ belongs to the convex hull of a set of m known covariance matrices. Model PB characterizes X and Y as jointly distributed according to a Gaussian mixture model with m known zero-mean components, but unknown component weights. We show: (a) the linear minimax estimator computed under model PA is identical to that computed under model PB when the vertices of the uncertain covariance set in PA are the same as the component covariances in model PB, and (b) the problem of computing the linear minimax estimator under either model reduces to a semidefinite program (SDP). We also consider the dynamic situation where x(t) and y(t) evolve according to a discrete-time LTI state space model driven by white noise, the statistics of which is modeled by PA and PB as before. We derive a recursive linear minimax filter for x(t) given y(t).
Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.
2016-01-01
In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration
Determinant of flexible Parametric Estimation of Mixture Cure ...
African Journals Online (AJOL)
PROF. OLIVER OSUAGWA
2015-12-01
Dec 1, 2015 ... Suitability of four parametric mixture cure models were considered namely; Log .... regression analysis which relies on the ... The parameter of mixture cure fraction model was ..... Stochastic Models of Tumor Latency and Their.
DEFF Research Database (Denmark)
Nielsen, Morten Ø.; Frederiksen, Per Houmann
2005-01-01
In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods. The es...... the time domain parametric methods, and (4) without sufficient trimming of scales the wavelet-based estimators are heavily biased.......In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods....... The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all...
Determinant of flexible Parametric Estimation of Mixture Cure ...
African Journals Online (AJOL)
AIC, mean time to cure), variance and cure fraction (c) were used to determine the flexible Parametric Cure Fraction Model among the considered models. Gastric Cancer data from 76 patients received adjuvant CRT and 125 receiving resection (surgery) alone were used to confirm the suitability of the models. The data was ...
A Study on Parametric Wave Estimation Based on Measured Ship Motions
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Iseki, Toshio
2011-01-01
The paper studies parametric wave estimation based on the ‘wave buoy analogy’, and data and results obtained from the training ship Shioji-maru are compared with estimates of the sea states obtained from other measurements and observations. Furthermore, the estimating characteristics of the param......The paper studies parametric wave estimation based on the ‘wave buoy analogy’, and data and results obtained from the training ship Shioji-maru are compared with estimates of the sea states obtained from other measurements and observations. Furthermore, the estimating characteristics...... of the parametric model are discussed by considering the results of a similar estimation concept based on Bayesian modelling. The purpose of the latter comparison is not to favour the one estimation approach to the other but rather to highlight some of the advantages and disadvantages of the two approaches....
The Effects of Policy Guidance Emphasizing the Use of Parametric Methods in Cost Estimating
National Research Council Canada - National Science Library
Patton, James
1996-01-01
.... As one of many initiatives to improve the DoD acquisition process through use of commercial practices, parametric cost estimating has the potential to be helpful in many applications for which it...
Parametric model to estimate containment loads following an ex-vessel steam spike
International Nuclear Information System (INIS)
Lopez, R.; Hernandez, J.; Huerta, A.
1998-01-01
This paper describes the use of a relatively simple parametric model to estimate containment loads following an ex-vessel steam spike. The study was motivated because several PSAs have identified containment loads accompanying reactor vessel failures as a major contributor to early containment failure. The paper includes a detailed description of the simple but physically sound parametric model which was adopted to estimate containment loads following a steam spike into the reactor cavity. (author)
ROBUST ALGORITHMS OF PARAMETRIC ESTIMATION IN SOME STABILIZATION PROBLEMS
Directory of Open Access Journals (Sweden)
A.A. Vedyakov
2016-07-01
Full Text Available Subject of Research.The tasks of dynamic systems provision in the stable state by means of ensuring of trite solution stability for various dynamic systems in the education regime with the aid of their parameters tuning are considered. Method. The problems are solved by application of ideology of the robust finitely convergent algorithms creation. Main Results. The concepts of parametric algorithmization of stability and steady asymptotic stability are introduced and the results are presented on synthesis of coarsed gradient algorithms solving the proposed tasks for finite number of iterations with the purpose of the posed problems decision. Practical Relevance. The article results may be called for decision of practical stabilization tasks in the process of various engineering constructions and devices operation.
International Nuclear Information System (INIS)
Hanna, Chad; Megevand, Miguel; Palenzuela, Carlos; Ochsner, Evan
2009-01-01
Recent advances in the description of compact binary systems have produced gravitational waveforms that include inspiral, merger and ring-down phases. Comparing results from numerical simulations with those of post-Newtonian, and related, expansions has provided motivation for employing post-Newtonian waveforms in near merger epochs when searching for gravitational waves and has encouraged the development of analytic fits to full numerical waveforms. Until searches employ full waveforms as templates, data analysts can still conduct separate inspiral, merger and ring-down searches. Improved knowledge about the end of the inspiral phase, the beginning of the merger and the ring-down frequencies will increase the efficiency of searches over each phase separately without needing the exact waveform. We will show that knowledge of the final spin, of which there are many theoretical models and analytic fits to simulations, may give an insight into the time-frequency properties of the merger. We also present implications on the ability to probe the tidal disruption of neutron stars through gravitational waves.
Determining input values for a simple parametric model to estimate ...
African Journals Online (AJOL)
Estimating soil evaporation (Es) is an important part of modelling vineyard evapotranspiration for irrigation purposes. Furthermore, quantification of possible soil texture and trellis effects is essential. Daily Es from six topsoils packed into lysimeters was measured under grapevines on slanting and vertical trellises, ...
Parametric change point estimation, testing and confidence interval ...
African Journals Online (AJOL)
In many applications like finance, industry and medicine, it is important to consider that the model parameters may undergo changes at unknown moment in time. This paper deals with estimation, testing and confidence interval of a change point for a univariate variable which is assumed to be normally distributed. To detect ...
Oracle estimation of parametric models under boundary constraints.
Wong, Kin Yau; Goldberg, Yair; Fine, Jason P
2016-12-01
In many classical estimation problems, the parameter space has a boundary. In most cases, the standard asymptotic properties of the estimator do not hold when some of the underlying true parameters lie on the boundary. However, without knowledge of the true parameter values, confidence intervals constructed assuming that the parameters lie in the interior are generally over-conservative. A penalized estimation method is proposed in this article to address this issue. An adaptive lasso procedure is employed to shrink the parameters to the boundary, yielding oracle inference which adapt to whether or not the true parameters are on the boundary. When the true parameters are on the boundary, the inference is equivalent to that which would be achieved with a priori knowledge of the boundary, while if the converse is true, the inference is equivalent to that which is obtained in the interior of the parameter space. The method is demonstrated under two practical scenarios, namely the frailty survival model and linear regression with order-restricted parameters. Simulation studies and real data analyses show that the method performs well with realistic sample sizes and exhibits certain advantages over standard methods. © 2016, The International Biometric Society.
Non-parametric PSF estimation from celestial transit solar images using blind deconvolution
Directory of Open Access Journals (Sweden)
González Adriana
2016-01-01
Full Text Available Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the convolution of an ideal image with a Point Spread Function (PSF. Additionally, the image acquisition process is also contaminated by other sources of noise (read-out, photon-counting. The problem of estimating both the PSF and a denoised image is called blind deconvolution and is ill-posed. Aims: We propose a blind deconvolution scheme that relies on image regularization. Contrarily to most methods presented in the literature, our method does not assume a parametric model of the PSF and can thus be applied to any telescope. Methods: Our scheme uses a wavelet analysis prior model on the image and weak assumptions on the PSF. We use observations from a celestial transit, where the occulting body can be assumed to be a black disk. These constraints allow us to retain meaningful solutions for the filter and the image, eliminating trivial, translated, and interchanged solutions. Under an additive Gaussian noise assumption, they also enforce noise canceling and avoid reconstruction artifacts by promoting the whiteness of the residual between the blurred observations and the cleaned data. Results: Our method is applied to synthetic and experimental data. The PSF is estimated for the SECCHI/EUVI instrument using the 2007 Lunar transit, and for SDO/AIA using the 2012 Venus transit. Results show that the proposed non-parametric blind deconvolution method is able to estimate the core of the PSF with a similar quality to parametric methods proposed in the literature. We also show that, if these parametric estimations are incorporated in the acquisition model, the resulting PSF outperforms both the parametric and non-parametric methods.
International Nuclear Information System (INIS)
Damek, Nawel; Kamoun, Samira
2011-01-01
In this communication, two recursive parametric estimation algorithms are analyzed and applied to an squirrelcage asynchronous machine located at the research ''Unit of Automatic Control'' (UCA) at ENIS. The first algorithm which, use the transfer matrix mathematical model, is based on the gradient principle. The second algorithm, which use the state-space mathematical model, is based on the minimization of the estimation error. These algorithms are applied as a key technique to estimate asynchronous machine with unknown, but constant or timevarying parameters. Stator voltage and current are used as measured data. The proposed recursive parametric estimation algorithms are validated on the experimental data of an asynchronous machine under normal operating condition as full load. The results show that these algorithms can estimate effectively the machine parameters with reliability.
The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models
GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.
2008-01-01
In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.
Non-parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods
DEFF Research Database (Denmark)
Høg, Esben
In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean-reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...
Non-Parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods
DEFF Research Database (Denmark)
Høg, Esben
2003-01-01
In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean--reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...
Joint Parametric Fault Diagnosis and State Estimation Using KF-ML Method
DEFF Research Database (Denmark)
Sun, Zhen; Yang, Zhenyu
2014-01-01
The paper proposes a new method for a kind of parametric fault online diagnosis with state estimation jointly. The considered fault affects not only the deterministic part of the system but also the random circumstance. The proposed method first applies Kalman Filter (KF) and Maximum Likelihood (...
Principles of parametric estimation in modeling language competition.
Zhang, Menghan; Gong, Tao
2013-06-11
It is generally difficult to define reasonable parameters and interpret their values in mathematical models of social phenomena. Rather than directly fitting abstract parameters against empirical data, we should define some concrete parameters to denote the sociocultural factors relevant for particular phenomena, and compute the values of these parameters based upon the corresponding empirical data. Taking the example of modeling studies of language competition, we propose a language diffusion principle and two language inheritance principles to compute two critical parameters, namely the impacts and inheritance rates of competing languages, in our language competition model derived from the Lotka-Volterra competition model in evolutionary biology. These principles assign explicit sociolinguistic meanings to those parameters and calculate their values from the relevant data of population censuses and language surveys. Using four examples of language competition, we illustrate that our language competition model with thus-estimated parameter values can reliably replicate and predict the dynamics of language competition, and it is especially useful in cases lacking direct competition data.
Direct Parametric Reconstruction With Joint Motion Estimation/Correction for Dynamic Brain PET Data.
Jiao, Jieqing; Bousse, Alexandre; Thielemans, Kris; Burgos, Ninon; Weston, Philip S J; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Markiewicz, Pawel; Ourselin, Sebastien
2017-01-01
Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [ 11 C]raclopride data using the Zubal brain phantom and real clinical [ 18 F]florbetapir data of a patient with Alzheimer's disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion.
truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models
Directory of Open Access Journals (Sweden)
Maria Karlsson
2014-05-01
Full Text Available Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and ?nite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.
Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications
Qian, Xuewen; Deng, Honggui; He, Hailang
2017-10-01
Due to wide modulation bandwidth in optical communication, multipath channels may be non-sparse and deteriorate communication performance heavily. Traditional compressive sensing-based channel estimation algorithm cannot be employed in this kind of situation. In this paper, we propose a practical parametric channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based visual light communication (VLC) systems based on modified zero correlation code (ZCC) pair that has the impulse-like correlation property. Simulation results show that the proposed algorithm achieves better performances than existing least squares (LS)-based algorithm in both bit error ratio (BER) and frequency response estimation.
Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.
Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman
2013-10-21
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study
Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation
International Nuclear Information System (INIS)
Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman
2013-01-01
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (∼15–20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate K i and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final K i parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion
Siciliani, Luigi
2006-01-01
Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.
Parametric estimation of the Duffing system by using a modified gradient algorithm
International Nuclear Information System (INIS)
Aguilar-Ibanez, Carlos; Sanchez Herrera, Jorge; Garrido-Moctezuma, Ruben
2008-01-01
The Letter presents a strategy for recovering the unknown parameters of the Duffing oscillator using a measurable output signal. The suggested approach employs the construction of an integral parametrization of one auxiliary output. It is calculated by measuring the difference between the output and its respective delay output. First we estimate the auxiliary output, followed by the application of a modified gradient algorithm, then we adjust the gains of the proposed linear estimator, until this error converges to zero. The convergence of the proposed scheme is shown using Lyapunov method
Kinetic parametric estimation in animal PET molecular imaging based on artificial immune network
International Nuclear Information System (INIS)
Chen Yuting; Ding Hong; Lu Rui; Huang Hongbo; Liu Li
2011-01-01
Objective: To develop an accurate,reliable method without the need of initialization in animal PET modeling for estimation of the tracer kinetic parameters based on the artificial immune network. Methods: The hepatic and left ventricular time activity curves (TACs) were obtained by drawing ROIs of liver tissue and left ventricle on dynamic 18 F-FDG PET imaging of small mice. Meanwhile, the blood TAC was analyzed by sampling the tail vein blood at different time points after injection. The artificial immune network for parametric optimization of pharmacokinetics (PKAIN) was adapted to estimate the model parameters and the metabolic rate of glucose (K i ) was calculated. Results: TACs of liver,left ventricle and tail vein blood were obtained.Based on the artificial immune network, K i in 3 mice was estimated as 0.0024, 0.0417 and 0.0047, respectively. The average weighted residual sum of squares of the output model generated by PKAIN was less than 0.0745 with a maximum standard deviation of 0.0084, which indicated that the proposed PKAIN method can provide accurate and reliable parametric estimation. Conclusion: The PKAIN method could provide accurate and reliable tracer kinetic modeling in animal PET imaging without the need of initialization of model parameters. (authors)
Jacobs, Rianne; Bekker, Andriëtte A; van der Voet, Hilko; Ter Braak, Cajo J F
2015-01-01
Estimating the risk, P(X > Y), in probabilistic environmental risk assessment of nanoparticles is a problem when confronted by potentially small risks and small sample sizes of the exposure concentration X and/or the effect concentration Y. This is illustrated in the motivating case study of aquatic risk assessment of nano-Ag. A non-parametric estimator based on data alone is not sufficient as it is limited by sample size. In this paper, we investigate the maximum gain possible when making strong parametric assumptions as opposed to making no parametric assumptions at all. We compare maximum likelihood and Bayesian estimators with the non-parametric estimator and study the influence of sample size and risk on the (interval) estimators via simulation. We found that the parametric estimators enable us to estimate and bound the risk for smaller sample sizes and small risks. Also, the Bayesian estimator outperforms the maximum likelihood estimators in terms of coverage and interval lengths and is, therefore, preferred in our motivating case study.
International Nuclear Information System (INIS)
Morio, Jerome
2011-01-01
Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.
International Nuclear Information System (INIS)
Coelli, Tim J.; Gautier, Axel; Perelman, Sergio; Saplacan-Pop, Roxana
2013-01-01
The quality of electricity distribution is being more and more scrutinized by regulatory authorities, with explicit reward and penalty schemes based on quality targets having been introduced in many countries. It is then of prime importance to know the cost of improving the quality for a distribution system operator. In this paper, we focus on one dimension of quality, the continuity of supply, and we estimated the cost of preventing power outages. For that, we make use of the parametric distance function approach, assuming that outages enter in the firm production set as an input, an imperfect substitute for maintenance activities and capital investment. This allows us to identify the sources of technical inefficiency and the underlying trade-off faced by operators between quality and other inputs and costs. For this purpose, we use panel data on 92 electricity distribution units operated by ERDF (Electricité de France - Réseau Distribution) in the 2003–2005 financial years. Assuming a multi-output multi-input translog technology, we estimate that the cost of preventing one interruption is equal to 10.7€ for an average DSO. Furthermore, as one would expect, marginal quality improvements tend to be more expensive as quality itself improves. - Highlights: ► We estimate the implicit cost of outages for the main distribution company in France. ► For this purpose, we make use of a parametric distance function approach. ► Marginal quality improvements tend to be more expensive as quality itself improves. ► The cost of preventing one interruption varies from 1.8 € to 69.2 € (2005 prices). ► We estimate that, in average, it lays 33% above the regulated price of quality.
A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain
Directory of Open Access Journals (Sweden)
Ibn-Elhaj E
2009-01-01
Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.
A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain
Directory of Open Access Journals (Sweden)
E. M. Ismaili Aalaoui
2009-02-01
Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.
Donald Gagliasso; Susan Hummel; Hailemariam. Temesgen
2014-01-01
Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...
Directory of Open Access Journals (Sweden)
Meyer Karin
2001-11-01
Full Text Available Abstract A random regression model for the analysis of "repeated" records in animal breeding is described which combines a random regression approach for additive genetic and other random effects with the assumption of a parametric correlation structure for within animal covariances. Both stationary and non-stationary correlation models involving a small number of parameters are considered. Heterogeneity in within animal variances is modelled through polynomial variance functions. Estimation of parameters describing the dispersion structure of such model by restricted maximum likelihood via an "average information" algorithm is outlined. An application to mature weight records of beef cow is given, and results are contrasted to those from analyses fitting sets of random regression coefficients for permanent environmental effects.
Energy Technology Data Exchange (ETDEWEB)
Ray, Jaideep; Lee, Jina; Lefantzi, Sophia; Yadav, Vineet [Carnegie Institution for Science, Stanford, CA; Michalak, Anna M. [Carnegie Institution for Science, Stanford, CA; van Bloemen Waanders, Bart Gustaaf [Sandia National Laboratories, Albuquerque, NM; McKenna, Sean Andrew [IBM Research, Mulhuddart, Dublin 15, Ireland
2013-04-01
The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization. The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.
Recent developments in time-frequency analysis
Loughlin, Patrick
1998-01-01
Recent Developments in Time-Frequency Analysis brings together in one place important contributions and up-to-date research results in this fast moving area. Recent Developments in Time-Frequency Analysis serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Zhu, Yanjie; Peng, Xi; Wu, Yin; Wu, Ed X; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong
2017-02-01
To develop a new model-based method with spatial and parametric constraints (MB-SPC) aimed at accelerating diffusion tensor imaging (DTI) by directly estimating the diffusion tensor from highly undersampled k-space data. The MB-SPC method effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images using an L1-L2 norm and the smoothness of the diffusion tensor using a total variation seminorm. The undersampled k-space datasets were obtained from fully sampled DTI datasets of a simulated phantom and an ex-vivo experimental rat heart with acceleration factors ranging from 2 to 4. The diffusion tensor was directly reconstructed by solving a minimization problem with a nonlinear conjugate gradient descent algorithm. The reconstruction performance was quantitatively assessed using the normalized root mean square error (nRMSE) of the DTI indices. The MB-SPC method achieves acceptable DTI measures at an acceleration factor up to 4. Experimental results demonstrate that the proposed method can estimate the diffusion tensor more accurately than most existing methods operating at higher net acceleration factors. The proposed method can significantly reduce artifact, particularly at higher acceleration factors or lower SNRs. This method can easily be adapted to MR relaxometry parameter mapping and is thus useful in the characterization of biological tissue such as nerves, muscle, and heart tissue. © 2016 American Association of Physicists in Medicine.
Low default credit scoring using two-class non-parametric kernel density estimation
CSIR Research Space (South Africa)
Rademeyer, E
2016-12-01
Full Text Available This paper investigates the performance of two-class classification credit scoring data sets with low default ratios. The standard two-class parametric Gaussian and non-parametric Parzen classifiers are extended, using Bayes’ rule, to include either...
International Nuclear Information System (INIS)
Bachoc, F.
2013-01-01
The parametric estimation of the covariance function of a Gaussian process is studied, in the framework of the Kriging model. Maximum Likelihood and Cross Validation estimators are considered. The correctly specified case, in which the covariance function of the Gaussian process does belong to the parametric set used for estimation, is first studied in an increasing-domain asymptotic framework. The sampling considered is a randomly perturbed multidimensional regular grid. Consistency and asymptotic normality are proved for the two estimators. It is then put into evidence that strong perturbations of the regular grid are always beneficial to Maximum Likelihood estimation. The incorrectly specified case, in which the covariance function of the Gaussian process does not belong to the parametric set used for estimation, is then studied. It is shown that Cross Validation is more robust than Maximum Likelihood in this case. Finally, two applications of the Kriging model with Gaussian processes are carried out on industrial data. For a validation problem of the friction model of the thermal-hydraulic code FLICA 4, where experimental results are available, it is shown that Gaussian process modeling of the FLICA 4 code model error enables to considerably improve its predictions. Finally, for a meta modeling problem of the GERMINAL thermal-mechanical code, the interest of the Kriging model with Gaussian processes, compared to neural network methods, is shown. (author) [fr
Time-frequency analysis of human motion during rhythmic exercises.
Omkar, S N; Vyas, Khushi; Vikranth, H N
2011-01-01
Biomechanical signals due to human movements during exercise are represented in time-frequency domain using Wigner Distribution Function (WDF). Analysis based on WDF reveals instantaneous spectral and power changes during a rhythmic exercise. Investigations were carried out on 11 healthy subjects who performed 5 cycles of sun salutation, with a body-mounted Inertial Measurement Unit (IMU) as a motion sensor. Variance of Instantaneous Frequency (I.F) and Instantaneous Power (I.P) for performance analysis of the subject is estimated using one-way ANOVA model. Results reveal that joint Time-Frequency analysis of biomechanical signals during motion facilitates a better understanding of grace and consistency during rhythmic exercise.
The Linear Time Frequency Analysis Toolbox
DEFF Research Database (Denmark)
Søndergaard, Peter Lempel; Torrésani, Bruno; Balazs, Peter
2011-01-01
The Linear Time Frequency Analysis Toolbox is a Matlab/Octave toolbox for computational time-frequency analysis. It is intended both as an educational and computational tool. The toolbox provides the basic Gabor, Wilson and MDCT transform along with routines for constructing windows (lter...... prototypes) and routines for manipulating coe cients. It also provides a bunch of demo scripts devoted either to demonstrating the main functions of the toolbox, or to exemplify their use in specic signal processing applications. In this paper we describe the used algorithms, their mathematical background...
Brandt, James M.
1999-01-01
Approved for public release; distribution is unlimited With few effective decision-making tools to assess the affordability of major weapon systems, management of total ownership costs is continually misunderstood. Cost analysis provides a quick and reliable assessment of affordability. Because there is no standardized method for calculating reliable estimates of operating and support (O&S) costs (the principal component of total ownership cost), this thesis formulates a parametric cost mo...
Positivity of time-frequency distribution functions
Janssen, A.J.E.M.
1988-01-01
This paper deals with the question how various 'natural' conditions posed on time-frequency distribution functions prevent them to be nonnegative everywhere for all signals. The attention is restricted mainly to distribution functions that involve the signal bilinearly. This paper summarizes and
On positivity of time-frequency distributions.
Janssen, A.J.E.M.; Claasen, T.A.C.M.
1985-01-01
Consideration is given to the problem of how to regard the fundamental impossibility with time-frequency energy distributions of Cohen's class always to be nonnegative and, at the same time, to have correct marginal distributions. It is shown that the Wigner distribution is the only member of a
Parametric fault estimation based on H∞ optimization in a satellite launch vehicle
DEFF Research Database (Denmark)
Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Stoustrup, Jakob
2008-01-01
Correct diagnosis under harsh environmental conditions is crucial for space vehiclespsila health management systems to avoid possible hazardous situations. Consequently, the diagnosis methods are required to be robust toward these conditions. Design of a parametric fault detector, where the fault...... for the satellite launch vehicle and the results are discussed....
A non-parametric estimator for the doubly-periodic Poisson intensity function
R. Helmers (Roelof); I.W. Mangku (Wayan); R. Zitikis
2007-01-01
textabstractIn a series of papers, J. Garrido and Y. Lu have proposed and investigated a doubly-periodic Poisson model, and then applied it to analyze hurricane data. The authors have suggested several parametric models for the underlying intensity function. In the present paper we construct and
On the parallelization of a three-parametric log-logistic estimation algorithm
Asenjo-Plaza, Rafael; Rodríguez, Andrés; Navarro, Ángeles; Fernández-Madrigal, Juan Antonio; Cruz-Martin, Ana Maria
2014-01-01
Networked telerobots transmit data from its sensors to the remote controller. To provide guarantees on the time requirements of these systems it is mandatory to keep the transmission time delays below a given threshold, and to that end we should predict them. In this paper we tackle the parallelization of a procedure that models these stochastic time delays. More precisely, we focus on fitting the time delay signal using a three-parametrical log-logistic distribution. Since, the robot and the...
Moore, Julia L; Remais, Justin V
2014-03-01
Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.
Parametric and Non-Parametric System Modelling
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg
1999-01-01
the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...
Directory of Open Access Journals (Sweden)
I. Foyo-Moreno
2000-11-01
Full Text Available Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l., an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290–385 nm. After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those
Directory of Open Access Journals (Sweden)
I. Foyo-Moreno
Full Text Available Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l., an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290–385 nm. After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those
Parameter Estimation with Entangled Photons Produced by Parametric Down-Conversion
Cable, Hugo; Durkin, Gabriel A.
2010-01-01
We explore the advantages offered by twin light beams produced in parametric down-conversion for precision measurement. The symmetry of these bipartite quantum states, even under losses, suggests that monitoring correlations between the divergent beams permits a high-precision inference of any symmetry-breaking effect, e.g., fiber birefringence. We show that the quantity of entanglement is not the key feature for such an instrument. In a lossless setting, scaling of precision at the ultimate "Heisenberg" limit is possible with photon counting alone. Even as photon losses approach 100% the precision is shot-noise limited, and we identify the crossover point between quantum and classical precision as a function of detected flux. The predicted hypersensitivity is demonstrated with a Bayesian simulation.
Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT
Directory of Open Access Journals (Sweden)
Cunsuo Pang
2016-09-01
Full Text Available This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT’s performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated pulse radar, SAR (Synthetic aperture radar, or ISAR (Inverse synthetic aperture radar, for improving the probability of target recognition.
Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT.
Pang, Cunsuo; Han, Yan; Hou, Huiling; Liu, Shengheng; Zhang, Nan
2016-09-24
This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT) for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method, is effective in reducing the computation load. A multi-order STFRFT time-frequency algorithm is also developed that makes use of the time-frequency feature of each micro-Doppler component signal. This algorithm improves the estimation accuracy of time-frequency curve fitting through multi-order matching. Finally, experiment data were used to demonstrate STFRFT's performance in micro-Doppler time-frequency analysis. The results validated the higher estimate accuracy of the proposed algorithm. It may be applied to an LFM (Linear frequency modulated) pulse radar, SAR (Synthetic aperture radar), or ISAR (Inverse synthetic aperture radar), for improving the probability of target recognition.
Estimation of leakage power and delay in CMOS circuits using parametric variation
Directory of Open Access Journals (Sweden)
Preeti Verma
2016-09-01
Full Text Available With the advent of deep-submicron technologies, leakage power dissipation is a major concern for scaling down portable devices that have burst-mode type integrated circuits. In this paper leakage reduction technique HTLCT (High Threshold Leakage Control Transistor is discussed. Using high threshold transistors at the place of low threshold leakage control transistors, result in more leakage power reduction as compared to LCT (leakage control transistor technique but at the scarifies of area and delay. Further, analysis of effect of parametric variation on leakage current and propagation delay in CMOS circuits is performed. It is found that the leakage power dissipation increases with increasing temperature, supply voltage and aspect ratio. However, opposite pattern is noticed for the propagation delay. Leakage power dissipation for LCT NAND gate increases up to 14.32%, 6.43% and 36.21% and delay decreases by 22.5%, 42% and 9% for variation of temperature, supply voltage and aspect ratio. Maximum peak of equivalent output noise is obtained as 127.531 nV/Sqrt(Hz at 400 mHz.
DEFF Research Database (Denmark)
Petersen, Jørgen Holm
2016-01-01
This paper describes a new approach to the estimation in a logistic regression model with two crossed random effects where special interest is in estimating the variance of one of the effects while not making distributional assumptions about the other effect. A composite likelihood is studied...
Non-parametric estimation of the availability in a general repairable system
International Nuclear Information System (INIS)
Gamiz, M.L.; Roman, Y.
2008-01-01
This work deals with repairable systems with unknown failure and repair time distributions. We focus on the estimation of the instantaneous availability, that is, the probability that the system is functioning at a given time, which we consider as the most significant measure for evaluating the effectiveness of a repairable system. The estimation of the availability function is not, in general, an easy task, i.e., analytical techniques are difficult to apply. We propose a smooth estimation of the availability based on kernel estimator of the cumulative distribution functions (CDF) of the failure and repair times, for which the bandwidth parameters are obtained by bootstrap procedures. The consistency properties of the availability estimator are established by using techniques based on the Laplace transform
Non-parametric estimation of the availability in a general repairable system
Energy Technology Data Exchange (ETDEWEB)
Gamiz, M.L. [Departamento de Estadistica e I.O., Facultad de Ciencias, Universidad de Granada, Granada 18071 (Spain)], E-mail: mgamiz@ugr.es; Roman, Y. [Departamento de Estadistica e I.O., Facultad de Ciencias, Universidad de Granada, Granada 18071 (Spain)
2008-08-15
This work deals with repairable systems with unknown failure and repair time distributions. We focus on the estimation of the instantaneous availability, that is, the probability that the system is functioning at a given time, which we consider as the most significant measure for evaluating the effectiveness of a repairable system. The estimation of the availability function is not, in general, an easy task, i.e., analytical techniques are difficult to apply. We propose a smooth estimation of the availability based on kernel estimator of the cumulative distribution functions (CDF) of the failure and repair times, for which the bandwidth parameters are obtained by bootstrap procedures. The consistency properties of the availability estimator are established by using techniques based on the Laplace transform.
Type I Error Rates and Power Estimates of Selected Parametric and Nonparametric Tests of Scale.
Olejnik, Stephen F.; Algina, James
1987-01-01
Estimated Type I Error rates and power are reported for the Brown-Forsythe, O'Brien, Klotz, and Siegal-Tukey procedures. The effect of aligning the data using deviations from group means or group medians is investigated. (RB)
High-resolution time-frequency representation of EEG data using multi-scale wavelets
Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina
2017-09-01
An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.
On the method of logarithmic cumulants for parametric probability density function estimation.
Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane
2013-10-01
Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.
Directory of Open Access Journals (Sweden)
Jo Nishino
2018-04-01
Full Text Available Genome-wide association studies (GWAS suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1. For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases.
Noise removal in multichannel image data by a parametric maximum noise fraction estimator
DEFF Research Database (Denmark)
Conradsen, Knut; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg
1991-01-01
Some approaches to noise removal in multispectral imagery are presented. The primary contribution of the present work is the establishment of several ways of estimating the noise covariance matrix from image data and a comparison of the noise separation performances. A case study with Landsat MSS...
An estimating equation for parametric shared frailty models with marginal additive hazards
DEFF Research Database (Denmark)
Pipper, Christian Bressen; Martinussen, Torben
2004-01-01
Multivariate failure time data arise when data consist of clusters in which the failure times may be dependent. A popular approach to such data is the marginal proportional hazards model with estimation under the working independence assumption. In some contexts, however, it may be more reasonable...
Sebacher, B.; Hanea, R.G.; Heemink, A.
2013-01-01
In the past years, many applications of historymatching methods in general and ensemble Kalman filter in particular have been proposed, especially in order to estimate fields that provide uncertainty in the stochastic process defined by the dynamical system of hydrocarbon recovery. Such fields can
Essays on parametric and nonparametric modeling and estimation with applications to energy economics
Gao, Weiyu
My dissertation research is composed of two parts: a theoretical part on semiparametric efficient estimation and an applied part in energy economics under different dynamic settings. The essays are related in terms of their applications as well as the way in which models are constructed and estimated. In the first essay, efficient estimation of the partially linear model is studied. We work out the efficient score functions and efficiency bounds under four stochastic restrictions---independence, conditional symmetry, conditional zero mean, and partially conditional zero mean. A feasible efficient estimation method for the linear part of the model is developed based on the efficient score. A battery of specification test that allows for choosing between the alternative assumptions is provided. A Monte Carlo simulation is also conducted. The second essay presents a dynamic optimization model for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from different sources to estimate the oil production cost function and the revenue function. We pay particular attention to the dynamic aspect of the oil production by employing petroleum-engineering software to simulate the interaction between control variables and reservoir state variables. Optimal solutions are studied under different scenarios to account for the possible changes in the exogenous variables and the uncertainty about the forecasts. The third essay examines the effect of oil price volatility on the level of innovation displayed by the U.S. economy. A measure of innovation is calculated by decomposing an output-based Malmquist index. We also construct a nonparametric measure for oil price volatility. Technical change and oil price volatility are then placed in a VAR system with oil price and a variable indicative of monetary policy. The system is estimated and analyzed for significant relationships. We find that oil price volatility displays a significant
Som, Nicholas A.; Goodman, Damon H.; Perry, Russell W.; Hardy, Thomas B.
2016-01-01
Previous methods for constructing univariate habitat suitability criteria (HSC) curves have ranged from professional judgement to kernel-smoothed density functions or combinations thereof. We present a new method of generating HSC curves that applies probability density functions as the mathematical representation of the curves. Compared with previous approaches, benefits of our method include (1) estimation of probability density function parameters directly from raw data, (2) quantitative methods for selecting among several candidate probability density functions, and (3) concise methods for expressing estimation uncertainty in the HSC curves. We demonstrate our method with a thorough example using data collected on the depth of water used by juvenile Chinook salmon (Oncorhynchus tschawytscha) in the Klamath River of northern California and southern Oregon. All R code needed to implement our example is provided in the appendix. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
spa: Semi-Supervised Semi-Parametric Graph-Based Estimation in R
Directory of Open Access Journals (Sweden)
Mark Culp
2011-04-01
Full Text Available In this paper, we present an R package that combines feature-based (X data and graph-based (G data for prediction of the response Y . In this particular case, Y is observed for a subset of the observations (labeled and missing for the remainder (unlabeled. We examine an approach for fitting Y = Xβ + f(G where β is a coefficient vector and f is a function over the vertices of the graph. The procedure is semi-supervised in nature (trained on the labeled and unlabeled sets, requiring iterative algorithms for fitting this estimate. The package provides several key functions for fitting and evaluating an estimator of this type. The package is illustrated on a text analysis data set, where the observations are text documents (papers, the response is the category of paper (either applied or theoretical statistics, the X information is the name of the journal in which the paper resides, and the graph is a co-citation network, with each vertex an observation and each edge the number of times that the two papers cite a common paper. An application involving classification of protein location using a protein interaction graph and an application involving classification on a manifold with part of the feature data converted to a graph are also presented.
Choi, Sae Il
2009-01-01
This study used simulation (a) to compare the kernel equating method to traditional equipercentile equating methods under the equivalent-groups (EG) design and the nonequivalent-groups with anchor test (NEAT) design and (b) to apply the parametric bootstrap method for estimating standard errors of equating. A two-parameter logistic item response…
Directory of Open Access Journals (Sweden)
A. V. Artemyev
2013-04-01
Full Text Available The lifetimes of electrons trapped in Earth's radiation belts can be calculated from quasi-linear pitch-angle diffusion by whistler-mode waves, provided that their frequency spectrum is broad enough and/or their average amplitude is not too large. Extensive comparisons between improved analytical lifetime estimates and full numerical calculations have been performed in a broad parameter range representative of a large part of the magnetosphere from L ~ 2 to 6. The effects of observed very oblique whistler waves are taken into account in both numerical and analytical calculations. Analytical lifetimes (and pitch-angle diffusion coefficients are found to be in good agreement with full numerical calculations based on CRRES and Cluster hiss and lightning-generated wave measurements inside the plasmasphere and Cluster lower-band chorus waves measurements in the outer belt for electron energies ranging from 100 keV to 5 MeV. Comparisons with lifetimes recently obtained from electron flux measurements on SAMPEX, SCATHA, SAC-C and DEMETER also show reasonable agreement.
Karabatsos, George
2017-02-01
Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected
Piovesan, Davide; Pierobon, Alberto; DiZio, Paul; Lackner, James R
2012-01-01
This study presents and validates a Time-Frequency technique for measuring 2-dimensional multijoint arm stiffness throughout a single planar movement as well as during static posture. It is proposed as an alternative to current regressive methods which require numerous repetitions to obtain average stiffness on a small segment of the hand trajectory. The method is based on the analysis of the reassigned spectrogram of the arm's response to impulsive perturbations and can estimate arm stiffness on a trial-by-trial basis. Analytic and empirical methods are first derived and tested through modal analysis on synthetic data. The technique's accuracy and robustness are assessed by modeling the estimation of stiffness time profiles changing at different rates and affected by different noise levels. Our method obtains results comparable with two well-known regressive techniques. We also test how the technique can identify the viscoelastic component of non-linear and higher than second order systems with a non-parametrical approach. The technique proposed here is very impervious to noise and can be used easily for both postural and movement tasks. Estimations of stiffness profiles are possible with only one perturbation, making our method a useful tool for estimating limb stiffness during motor learning and adaptation tasks, and for understanding the modulation of stiffness in individuals with neurodegenerative diseases.
Directory of Open Access Journals (Sweden)
Davide Piovesan
Full Text Available This study presents and validates a Time-Frequency technique for measuring 2-dimensional multijoint arm stiffness throughout a single planar movement as well as during static posture. It is proposed as an alternative to current regressive methods which require numerous repetitions to obtain average stiffness on a small segment of the hand trajectory. The method is based on the analysis of the reassigned spectrogram of the arm's response to impulsive perturbations and can estimate arm stiffness on a trial-by-trial basis. Analytic and empirical methods are first derived and tested through modal analysis on synthetic data. The technique's accuracy and robustness are assessed by modeling the estimation of stiffness time profiles changing at different rates and affected by different noise levels. Our method obtains results comparable with two well-known regressive techniques. We also test how the technique can identify the viscoelastic component of non-linear and higher than second order systems with a non-parametrical approach. The technique proposed here is very impervious to noise and can be used easily for both postural and movement tasks. Estimations of stiffness profiles are possible with only one perturbation, making our method a useful tool for estimating limb stiffness during motor learning and adaptation tasks, and for understanding the modulation of stiffness in individuals with neurodegenerative diseases.
Maximum-likelihood methods for array processing based on time-frequency distributions
Zhang, Yimin; Mu, Weifeng; Amin, Moeness G.
1999-11-01
This paper proposes a novel time-frequency maximum likelihood (t-f ML) method for direction-of-arrival (DOA) estimation for non- stationary signals, and compares this method with conventional maximum likelihood DOA estimation techniques. Time-frequency distributions localize the signal power in the time-frequency domain, and as such enhance the effective SNR, leading to improved DOA estimation. The localization of signals with different t-f signatures permits the division of the time-frequency domain into smaller regions, each contains fewer signals than those incident on the array. The reduction of the number of signals within different time-frequency regions not only reduces the required number of sensors, but also decreases the computational load in multi- dimensional optimizations. Compared to the recently proposed time- frequency MUSIC (t-f MUSIC), the proposed t-f ML method can be applied in coherent environments, without the need to perform any type of preprocessing that is subject to both array geometry and array aperture.
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.
On time-frequence analysis of heart rate variability
H.G. van Steenis (Hugo)
2002-01-01
textabstractThe aim of this research is to develop a time-frequency method suitable to study HRV in greater detail. The following approach was used: • two known time-frequency representations were applied to HRV to understand its advantages and disadvantages in describing HRV in frequency and in
Energy Technology Data Exchange (ETDEWEB)
Constantinescu, C C; Yoder, K K; Normandin, M D; Morris, E D [Department of Radiology, Indiana University School of Medicine, Indianapolis, IN (United States); Kareken, D A [Department of Neurology, Indiana University School of Medicine, Indianapolis, IN (United States); Bouman, C A [Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN (United States); O' Connor, S J [Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN (United States)], E-mail: emorris@iupui.edu
2008-03-07
We previously developed a model-independent technique (non-parametric ntPET) for extracting the transient changes in neurotransmitter concentration from paired (rest and activation) PET studies with a receptor ligand. To provide support for our method, we introduced three hypotheses of validation based on work by Endres and Carson (1998 J. Cereb. Blood Flow Metab. 18 1196-210) and Yoder et al (2004 J. Nucl. Med. 45 903-11), and tested them on experimental data. All three hypotheses describe relationships between the estimated free (synaptic) dopamine curves (F{sup DA}(t)) and the change in binding potential ({delta}BP). The veracity of the F{sup DA}(t) curves recovered by nonparametric ntPET is supported when the data adhere to the following hypothesized behaviors: (1) {delta}BP should decline with increasing DA peak time, (2) {delta}BP should increase as the strength of the temporal correlation between F{sup DA}(t) and the free raclopride (F{sup RAC}(t)) curve increases, (3) {delta}BP should decline linearly with the effective weighted availability of the receptor sites. We analyzed regional brain data from 8 healthy subjects who received two [{sup 11}C]raclopride scans: one at rest, and one during which unanticipated IV alcohol was administered to stimulate dopamine release. For several striatal regions, nonparametric ntPET was applied to recover F{sup DA}(t), and binding potential values were determined. Kendall rank-correlation analysis confirmed that the F{sup DA}(t) data followed the expected trends for all three validation hypotheses. Our findings lend credence to our model-independent estimates of F{sup DA}(t). Application of nonparametric ntPET may yield important insights into how alterations in timing of dopaminergic neurotransmission are involved in the pathologies of addiction and other psychiatric disorders.
A Time-Frequency Auditory Model Using Wavelet Packets
DEFF Research Database (Denmark)
Agerkvist, Finn
1996-01-01
A time-frequency auditory model is presented. The model uses the wavelet packet analysis as the preprocessor. The auditory filters are modelled by the rounded exponential filters, and the excitation is smoothed by a window function. By comparing time-frequency excitation patterns it is shown...... that the change in the time-frequency excitation pattern introduced when a test tone at masked threshold is added to the masker is approximately equal to 7 dB for all types of maskers. The classic detection ratio therefore overrates the detection efficiency of the auditory system....
Automatic traveltime picking using local time-frequency maps
Saragiotis, Christos; Alkhalifah, Tariq Ali; Fomel, Sergey B.
2011-01-01
The arrival times of distinct and sufficiently concentrated signals can be computed using Fourier transforms. In real seis- mograms, however, signals are far from distinct. We use local time-frequency maps of the seismograms and its frequency
Piovesan, Davide; Pierobon, Alberto; DiZio, Paul; Lackner, James R.
2013-01-01
We tested an innovative method to estimate joint stiffness and damping during multijoint unfettered arm movements. The technique employs impulsive perturbations and a time-frequency analysis to estimate the arm's mechanical properties along a reaching trajectory. Each single impulsive perturbation provides a continuous estimation on a single-reach basis, making our method ideal to investigate motor adaptation in the presence of force fields and to study the control of movement in impaired ind...
Time-frequency analysis and harmonic Gaussian functions
International Nuclear Information System (INIS)
Ranaivoson, R.T.R; Raoelina Andriambololona; Hanitriarivo, R.
2013-01-01
A method for time-frequency analysis is given. The approach utilizes properties of Gaussian distribution, properties of Hermite polynomials and Fourier analysis. We begin by the definitions of a set of functions called Harmonic Gaussian Functions. Then these functions are used to define a set of transformations, noted Τ n , which associate to a function ψ, of the time variable t, a set of functions Ψ n which depend on time, frequency and frequency (or time) standard deviation. Some properties of the transformations Τ n and the functions Ψ n are given. It is proved in particular that the square of the modulus of each function Ψ n can be interpreted as a representation of the energy distribution of the signal, represented by the function ψ, in the time-frequency plane for a given value of the frequency (or time) standard deviation. It is also shown that the function ψ can be recovered from the functions Ψ n .
Time-Frequency Analysis of Signals Generated by Rotating Machines
Directory of Open Access Journals (Sweden)
R. Zetik
1999-06-01
Full Text Available This contribution is devoted to the higher order time-frequency analyses of signals. Firstly, time-frequency representations of higher order (TFRHO are defined. Then L-Wigner distribution (LWD is given as a special case of TFRHO. Basic properties of LWD are illustrated based on the analysis of mono-component and multi-component synthetic signals and acoustical signals generated by rotating machine. The obtained results confirm usefulness of LWD application for the purpose of rotating machine condition monitoring.
A time-frequency analysis of wave packet fractional revivals
International Nuclear Information System (INIS)
Ghosh, Suranjana; Banerji, J
2007-01-01
We show that the time-frequency analysis of the autocorrelation function is, in many ways, a more appropriate tool to resolve fractional revivals of a wave packet than the usual time-domain analysis. This advantage is crucial in reconstructing the initial state of the wave packet when its coherent structure is short-lived and decays before it is fully revived. Our calculations are based on the model example of fractional revivals in a Rydberg wave packet of circular states. We end by providing an analytical investigation which fully agrees with our numerical observations on the utility of time-frequency analysis in the study of wave packet fractional revivals
Energy Technology Data Exchange (ETDEWEB)
Bonfrate, A; Farah, J; Sayah, R; Clairand, I [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-roses (France); De Marzi, L; Delacroix, S [Institut Curie Centre de Protontherapie d Orsay (CPO), Orsay (France); Herault, J [Centre Antoine Lacassagne (CAL) Cyclotron biomedical, Nice (France); Lee, C [National Cancer Institute, Rockville, MD (United States); Bolch, W [Univ Florida, Gainesville, FL (United States)
2015-06-15
Purpose: Development of a parametric equation suitable for a daily use in routine clinic to provide estimates of stray neutron doses in proton therapy. Methods: Monte Carlo (MC) calculations using the UF-NCI 1-year-old phantom were exercised to determine the variation of stray neutron doses as a function of irradiation parameters while performing intracranial treatments. This was done by individually changing the proton beam energy, modulation width, collimator aperture and thickness, compensator thickness and the air gap size while their impact on neutron doses were put into a single equation. The variation of neutron doses with distance from the target volume was also included in it. Then, a first step consisted in establishing the fitting coefficients by using 221 learning data which were neutron absorbed doses obtained with MC simulations while a second step consisted in validating the final equation. Results: The variation of stray neutron doses with irradiation parameters were fitted with linear, polynomial, etc. model while a power-law model was used to fit the variation of stray neutron doses with the distance from the target volume. The parametric equation fitted well MC simulations while establishing fitting coefficients as the discrepancies on the estimate of neutron absorbed doses were within 10%. The discrepancy can reach ∼25% for the bladder, the farthest organ from the target volume. Finally, the validation showed results in compliance with MC calculations since the discrepancies were also within 10% for head-and-neck and thoracic organs while they can reach ∼25%, again for pelvic organs. Conclusion: The parametric equation presents promising results and will be validated for other target sites as well as other facilities to go towards a universal method.
Advanced Time-Frequency Representation in Voice Signal Analysis
Directory of Open Access Journals (Sweden)
Dariusz Mika
2018-03-01
Full Text Available The most commonly used time-frequency representation of the analysis in voice signal is spectrogram. This representation belongs in general to Cohen's class, the class of time-frequency energy distributions. From the standpoint of properties of the resolution spectrogram representation is not optimal. In Cohen class representations are known which have a better resolution properties. All of them are created by smoothing the Wigner-Ville'a (WVD distribution characterized by the best resolution, however, the biggest harmful interference. Used smoothing functions decide about a compromise between the properties of resolution and eliminating harmful interference term. Another class of time-frequency energy distributions is the affine class of distributions. From the point of view of readability of analysis the best properties are known so called Redistribution of energy caused by the use of a general methodology referred to as reassignment to any time-frequency representation. Reassigned distributions efficiently combine a reduction of the interference terms provided by a well adapted smoothing kernel and an increased concentration of the signal components.
Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries
DEFF Research Database (Denmark)
Sturm, Bob L.; Christensen, Mads Græsbøll
2010-01-01
We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation...
Hybrid time/frequency domain modeling of nonlinear components
DEFF Research Database (Denmark)
Wiechowski, Wojciech Tomasz; Lykkegaard, Jan; Bak, Claus Leth
2007-01-01
This paper presents a novel, three-phase hybrid time/frequency methodology for modelling of nonlinear components. The algorithm has been implemented in the DIgSILENT PowerFactory software using the DIgSILENT Programming Language (DPL), as a part of the work described in [1]. Modified HVDC benchmark...
DEFF Research Database (Denmark)
Linnet, Kristian
2005-01-01
Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors......Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors...
Pérez Rosas, Osvaldo G.; Rivera Martínez, José L.; Maldonado Cano, Luis A.; López Rodríguez, Mario; Amaya Reyes, Laura M.; Cano Martínez, Elizabeth; García Vázquez, Mireya S.; Ramírez Acosta, Alejandro A.
2017-09-01
The automatic identification and classification of musical genres based on the sound similarities to form musical textures, it is a very active investigation area. In this context it has been created recognition systems of musical genres, formed by time-frequency characteristics extraction methods and by classification methods. The selection of this methods are important for a good development in the recognition systems. In this article they are proposed the Mel-Frequency Cepstral Coefficients (MFCC) methods as a characteristic extractor and Support Vector Machines (SVM) as a classifier for our system. The stablished parameters of the MFCC method in the system by our time-frequency analysis, represents the gamma of Mexican culture musical genres in this article. For the precision of a classification system of musical genres it is necessary that the descriptors represent the correct spectrum of each gender; to achieve this we must realize a correct parametrization of the MFCC like the one we present in this article. With the system developed we get satisfactory detection results, where the least identification percentage of musical genres was 66.67% and the one with the most precision was 100%.
Joint Time-Frequency And Wavelet Analysis - An Introduction
Directory of Open Access Journals (Sweden)
Majkowski Andrzej
2014-12-01
Full Text Available A traditional frequency analysis is not appropriate for observation of properties of non-stationary signals. This stems from the fact that the time resolution is not defined in the Fourier spectrum. Thus, there is a need for methods implementing joint time-frequency analysis (t/f algorithms. Practical aspects of some representative methods of time-frequency analysis, including Short Time Fourier Transform, Gabor Transform, Wigner-Ville Transform and Cone-Shaped Transform are described in this paper. Unfortunately, there is no correlation between the width of the time-frequency window and its frequency content in the t/f analysis. This property is not valid in the case of a wavelet transform. A wavelet is a wave-like oscillation, which forms its own “wavelet window”. Compression of the wavelet narrows the window, and vice versa. Individual wavelet functions are well localized in time and simultaneously in scale (the equivalent of frequency. The wavelet analysis owes its effectiveness to the pyramid algorithm described by Mallat, which enables fast decomposition of a signal into wavelet components.
Directory of Open Access Journals (Sweden)
Krishnan Sridhar
2007-01-01
Full Text Available This paper introduces a novel algorithm to excise single and multicomponent chirp-like interferences in direct sequence spread spectrum (DSSS communications. The excision algorithm consists of two stages: adaptive signal decomposition stage and directional element detection stage based on the Hough-Radon transform (HRT. Initially, the received spread spectrum signal is decomposed into its time-frequency (TF functions using an adaptive signal decomposition algorithm, and the resulting TF functions are mapped onto the TF plane. We then use a line detection algorithm based on the HRT that operates on the image of the TF plane and detects energy varying directional elements that satisfy a parametric constraint. Interference is modeled by reconstructing the corresponding TF functions detected by the HRT, and subtracted from the received signal. The proposed technique has two main advantages: (i it localizes the interferences on the TF plane with no cross-terms, thus facilitating simple filtering techniques based on thresholding of the TF functions, and is an efficient way to excise the interference; (ii it can be used for the detection of any directional interferences that can be parameterized. Simulation results with synthetic models have shown successful performance with linear and quadratic chirp interferences for single and multicomponent interference cases. The proposed method excises the interference even under very low SNR conditions of dB, and the technique could be easily extended to any interferences that could be represented by a parametric equation in the TF plane.
Time-Frequency Analysis of the Dispersion of Lamb Modes
Prosser, W. H.; Seale, Michael D.; Smith, Barry T.
1999-01-01
Accurate knowledge of the velocity dispersion of Lamb modes is important for ultrasonic nondestructive evaluation methods used in detecting and locating flaws in thin plates and in determining their elastic stiffness coefficients. Lamb mode dispersion is also important in the acoustic emission technique for accurately triangulating the location of emissions in thin plates. In this research, the ability to characterize Lamb mode dispersion through a time-frequency analysis (the pseudo Wigner-Ville distribution) was demonstrated. A major advantage of time-frequency methods is the ability to analyze acoustic signals containing multiple propagation modes, which overlap and superimpose in the time domain signal. By combining time-frequency analysis with a broadband acoustic excitation source, the dispersion of multiple Lamb modes over a wide frequency range can be determined from as little as a single measurement. In addition, the technique provides a direct measurement of the group velocity dispersion. The technique was first demonstrated in the analysis of a simulated waveform in an aluminum plate in which the Lamb mode dispersion was well known. Portions of the dispersion curves of the A(sub 0), A(sub 1), S(sub 0), and S(sub 2)Lamb modes were obtained from this one waveform. The technique was also applied for the analysis of experimental waveforms from a unidirectional graphite/epoxy composite plate. Measurements were made both along, and perpendicular to the fiber direction. In this case, the signals contained only the lowest order symmetric and antisymmetric modes. A least squares fit of the results from several source to detector distances was used. Theoretical dispersion curves were calculated and are shown to be in good agreement with experimental results.
A Robust Parametric Technique for Multipath Channel Estimation in the Uplink of a DS-CDMA System
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available The problem of estimating the multipath channel parameters of a new user entering the uplink of an asynchronous direct sequence-code division multiple access (DS-CDMA system is addressed. The problem is described via a least squares (LS cost function with a rich structure. This cost function, which is nonlinear with respect to the time delays and linear with respect to the gains of the multipath channel, is proved to be approximately decoupled in terms of the path delays. Due to this structure, an iterative procedure of 1D searches is adequate for time delays estimation. The resulting method is computationally efficient, does not require any specific pilot signal, and performs well for a small number of training symbols. Simulation results show that the proposed technique offers a better estimation accuracy compared to existing related methods, and is robust to multiple access interference.
DEFF Research Database (Denmark)
Stroe, Ana-Irina; Meng, Jinhao; Stroe, Daniel-Ioan
2018-01-01
to describe the battery dynamics. The SOC estimation method proposed in this paper is based on an Extended Kalman Filter (EKF) and nonlinear battery model which was parameterized using extended laboratory tests performed on several 13 Ah lithium titanate oxide (LTO)-based lithium-ion batteries. The developed......State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered...... a sensitivity analysis it was showed that the SOC and voltage estimation error are only slightly dependent on the variation of the battery model parameters with the SOC....
Time-Frequency Dynamics of Biofuel-Fuel-Food System
Czech Academy of Sciences Publication Activity Database
Vácha, Lukáš; Janda, K.; Krištoufek, Ladislav; Zilberman, D.
2013-01-01
Roč. 40, č. 1 (2013), s. 233-241 ISSN 0140-9883 R&D Projects: GA ČR(CZ) GBP402/12/G097 Grant - others:GA ČR(CZ) GAP402/11/0948 Program:GA Institutional support: RVO:67985556 Keywords : biofuels * correlations * wavelet coherence Subject RIV: AH - Economics Impact factor: 2.580, year: 2013 http://library.utia.cas.cz/separaty/2013/E/vacha-time-frequency dynamics of biofuels-fuels-food system.pdf
Kratochvíla, Jiří; Jiřík, Radovan; Bartoš, Michal; Standara, Michal; Starčuk, Zenon; Taxt, Torfinn
2016-03-01
One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup. © 2015 Wiley Periodicals, Inc.
The Application of Time-Frequency Methods to HUMS
Pryor, Anna H.; Mosher, Marianne; Lewicki, David G.; Norvig, Peter (Technical Monitor)
2001-01-01
This paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels, are analyzed using these methods. The new metric for automatic fault detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the methods on this data set. Analysis with the CWT detects mechanical problems with the test rig not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic fault detection and to develop methods of setting the threshold for the metric.
Environmental Sound Recognition Using Time-Frequency Intersection Patterns
Directory of Open Access Journals (Sweden)
Xuan Guo
2012-01-01
Full Text Available Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we use a multistage perceptron neural network system for environmental sound recognition. The input data is a combination of time-variance pattern of instantaneous powers and frequency-variance pattern with instantaneous spectrum at the power peak, referred to as a time-frequency intersection pattern. Spectra of many environmental sounds change more slowly than those of speech or voice, so the intersectional time-frequency pattern will preserve the major features of environmental sounds but with drastically reduced data requirements. Two experiments were conducted using an original database and an open database created by the RWCP project. The recognition rate for 20 kinds of environmental sounds was 92%. The recognition rate of the new method was about 12% higher than methods using only an instantaneous spectrum. The results are also comparable with HMM-based methods, although those methods need to treat the time variance of an input vector series with more complicated computations.
Energy Technology Data Exchange (ETDEWEB)
Gauthier, Y.
1997-10-20
Geostatistical tools are increasingly used to model permeability fields in subsurface reservoirs, which are considered as a particular random variable development depending of several geostatistical parameters such as variance and correlation length. The first part of the thesis is devoted to the study of relations existing between the transient well pressure (the well test) and the stochastic permeability field, using the apparent permeability concept.The well test performs a moving permeability average over larger and larger volume with increasing time. In the second part, the geostatistical parameters are evaluated using well test data; a Bayesian framework is used and parameters are estimated using the maximum likelihood principle by maximizing the well test data probability density function with respect to these parameters. This method, involving a well test fast evaluation, provides an estimation of the correlation length and the variance over different realizations of a two-dimensional permeability field
Directory of Open Access Journals (Sweden)
J. Bohlin
2012-07-01
Full Text Available The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E. Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean, stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean, with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet showed RMSEs (in percent of the surveyed stand mean of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.
Welch, Stephen M.; White, Jeffrey W.; Thorp, Kelly R.; Bello, Nora M.
2018-01-01
Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP’s) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings at locations across the eastern United States. High performance computing was used to develop a database of 356 million simulated anthesis dates in response to four CERES-Maize model parameters. Although the resulting estimates showed high predictive value (R2 = 0.94), three issues presented serious challenges for use of GSP’s as traits. First (expressivity), the model was unable to express the observed data for 168 to 3,339 lines (depending on the combination of site-years), many of which ended up sharing the same parameter value irrespective of genetics. Second, for 2,254 lines, the model reproduced the data, but multiple parameter sets were equally effective (equifinality). Third, parameter values were highly dependent (p<10−6919) on the sets of environments used to estimate them (instability), calling in to question the assumption that they represent fundamental genetic traits. The issues of expressivity, equifinality and instability must be addressed before the genetic mapping of GSP’s becomes a robust means to help solve the genotype-to-phenotype problem in crops. PMID:29672629
Automatic traveltime picking using local time-frequency maps
Saragiotis, Christos
2011-01-01
The arrival times of distinct and sufficiently concentrated signals can be computed using Fourier transforms. In real seis- mograms, however, signals are far from distinct. We use local time-frequency maps of the seismograms and its frequency derivatives to obtain frequency-dependent (instantaneous) traveltimes. A smooth division is utilized to control the resolution of the instantaneous traveltimes to allow for a trade-off between resolution and stability. We average these traveltimes over the frequency band which is data-dependent. The resulting traveltime attribute is used to isolate different signals in seismic traces. We demonstrate the effectiveness of this automatic method for picking arrivals by applying it on synthetic and real data. © 2011 Society of Exploration Geophysicists.
Fault detection of gearbox using time-frequency method
Widodo, A.; Satrijo, Dj.; Prahasto, T.; Haryanto, I.
2017-04-01
This research deals with fault detection and diagnosis of gearbox by using vibration signature. In this work, fault detection and diagnosis are approached by employing time-frequency method, and then the results are compared with cepstrum analysis. Experimental work has been conducted for data acquisition of vibration signal thru self-designed gearbox test rig. This test-rig is able to demonstrate normal and faulty gearbox i.e., wears and tooth breakage. Three accelerometers were used for vibration signal acquisition from gearbox, and optical tachometer was used for shaft rotation speed measurement. The results show that frequency domain analysis using fast-fourier transform was less sensitive to wears and tooth breakage condition. However, the method of short-time fourier transform was able to monitor the faults in gearbox. Wavelet Transform (WT) method also showed good performance in gearbox fault detection using vibration signal after employing time synchronous averaging (TSA).
Time-Frequency Methods for Structural Health Monitoring
Directory of Open Access Journals (Sweden)
Alexander L. Pyayt
2014-03-01
Full Text Available Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM of flood protection systems (levees, earthen dikes and concrete dams using sensor data. We present a robust data-driven anomaly detection method that combines time-frequency feature extraction, using wavelet analysis and phase shift, with one-sided classification techniques to identify the onset of failure anomalies in real-time sensor measurements. The methodology has been successfully tested at three operational levees. We detected a dam leakage in the retaining dam (Germany and “strange” behaviour of sensors installed in a Boston levee (UK and a Rhine levee (Germany.
Time-frequency analysis of submerged synthetic jet
Kumar, Abhay; Saha, Arun K.; Panigrahi, P. K.
2017-12-01
The coherent structures transport the finite body of fluid mass through rolling which plays an important role in heat transfer, boundary layer control, mixing, cooling, propulsion and other engineering applications. A synthetic jet in the form of a train of vortex rings having coherent structures of different length scales is expected to be useful in these applications. The propagation and sustainability of these coherent structures (vortex rings) in downstream direction characterize the performance of synthetic jet. In the present study, the velocity signal acquired using the S-type hot-film probe along the synthetic jet centerline has been taken for the spectral analysis. One circular and three rectangular orifices of aspect ratio 1, 2 and 4 actuating at 1, 6 and 18 Hz frequency have been used for creating different synthetic jets. The laser induced fluorescence images are used to study the flow structures qualitatively and help in explaining the velocity signal for detection of coherent structures. The study depicts four regions as vortex rollup and suction region (X/D h ≤ 3), steadily translating region (X/D h ≤ 3-8), vortex breakup region (X/Dh ≤ 4-8) and dissipation of small-scale vortices (X/D h ≤ 8-15). The presence of coherent structures localized in physical and temporal domain is analyzed for the characterization of synthetic jet. Due to pulsatile nature of synthetic jet, analysis of velocity time trace or signal in time, frequency and combined time-frequency domain assist in characterizing the signatures of coherent structures. It has been observed that the maximum energy is in the first harmonic of actuation frequency, which decreases slowly in downstream direction at 6 Hz compared to 1 and 18 Hz of actuation.
Applying time-frequency analysis to assess cerebral autoregulation during hypercapnia.
Directory of Open Access Journals (Sweden)
Michał M Placek
Full Text Available Classic methods for assessing cerebral autoregulation involve a transfer function analysis performed using the Fourier transform to quantify relationship between fluctuations in arterial blood pressure (ABP and cerebral blood flow velocity (CBFV. This approach usually assumes the signals and the system to be stationary. Such an presumption is restrictive and may lead to unreliable results. The aim of this study is to present an alternative method that accounts for intrinsic non-stationarity of cerebral autoregulation and the signals used for its assessment.Continuous recording of CBFV, ABP, ECG, and end-tidal CO2 were performed in 50 young volunteers during normocapnia and hypercapnia. Hypercapnia served as a surrogate of the cerebral autoregulation impairment. Fluctuations in ABP, CBFV, and phase shift between them were tested for stationarity using sphericity based test. The Zhao-Atlas-Marks distribution was utilized to estimate the time-frequency coherence (TFCoh and phase shift (TFPS between ABP and CBFV in three frequency ranges: 0.02-0.07 Hz (VLF, 0.07-0.20 Hz (LF, and 0.20-0.35 Hz (HF. TFPS was estimated in regions locally validated by statistically justified value of TFCoh. The comparison of TFPS with spectral phase shift determined using transfer function approach was performed.The hypothesis of stationarity for ABP and CBFV fluctuations and the phase shift was rejected. Reduced TFPS was associated with hypercapnia in the VLF and the LF but not in the HF. Spectral phase shift was also decreased during hypercapnia in the VLF and the LF but increased in the HF. Time-frequency method led to lower dispersion of phase estimates than the spectral method, mainly during normocapnia in the VLF and the LF.The time-frequency method performed no worse than the classic one and yet may offer benefits from lower dispersion of phase shift as well as a more in-depth insight into the dynamic nature of cerebral autoregulation.
International Nuclear Information System (INIS)
Bobrowski, Sebastian; Chen, Hong; Döring, Maik; Jensen, Uwe; Schinköthe, Wolfgang
2015-01-01
In practice manufacturers may have lots of failure data of similar products using the same technology basis under different operating conditions. Thus, one can try to derive predictions for the distribution of the lifetime of newly developed components or new application environments through the existing data using regression models based on covariates. Three categories of such regression models are considered: a parametric, a semiparametric and a nonparametric approach. First, we assume that the lifetime is Weibull distributed, where its parameters are modelled as linear functions of the covariate. Second, the Cox proportional hazards model, well-known in Survival Analysis, is applied. Finally, a kernel estimator is used to interpolate between empirical distribution functions. In particular the last case is new in the context of reliability analysis. We propose a goodness of fit measure (GoF), which can be applied to all three types of regression models. Using this GoF measure we discuss a new model selection procedure. To illustrate this method of reliability prediction, the three classes of regression models are applied to real test data of motor experiments. Further the performance of the approaches is investigated by Monte Carlo simulations. - Highlights: • We estimate the lifetime distribution in the presence of a covariate. • Three types of regression models are considered and compared. • A new nonparametric estimator based on our particular data structure is introduced. • We propose a goodness of fit measure and show a new model selection procedure. • A case study with real data and Monte Carlo simulations are performed
Lenoir, Guillaume; Crucifix, Michel
2018-03-01
Geophysical time series are sometimes sampled irregularly along the time axis. The situation is particularly frequent in palaeoclimatology. Yet, there is so far no general framework for handling the continuous wavelet transform when the time sampling is irregular. Here we provide such a framework. To this end, we define the scalogram as the continuous-wavelet-transform equivalent of the extended Lomb-Scargle periodogram defined in Part 1 of this study (Lenoir and Crucifix, 2018). The signal being analysed is modelled as the sum of a locally periodic component in the time-frequency plane, a polynomial trend, and a background noise. The mother wavelet adopted here is the Morlet wavelet classically used in geophysical applications. The background noise model is a stationary Gaussian continuous autoregressive-moving-average (CARMA) process, which is more general than the traditional Gaussian white and red noise processes. The scalogram is smoothed by averaging over neighbouring times in order to reduce its variance. The Shannon-Nyquist exclusion zone is however defined as the area corrupted by local aliasing issues. The local amplitude in the time-frequency plane is then estimated with least-squares methods. We also derive an approximate formula linking the squared amplitude and the scalogram. Based on this property, we define a new analysis tool: the weighted smoothed scalogram, which we recommend for most analyses. The estimated signal amplitude also gives access to band and ridge filtering. Finally, we design a test of significance for the weighted smoothed scalogram against the stationary Gaussian CARMA background noise, and provide algorithms for computing confidence levels, either analytically or with Monte Carlo Markov chain methods. All the analysis tools presented in this article are available to the reader in the Python package WAVEPAL.
Directory of Open Access Journals (Sweden)
Sridhar Krishnan
2007-07-01
Full Text Available This paper introduces a novel algorithm to excise single and multicomponent chirp-like interferences in direct sequence spread spectrum (DSSS communications. The excision algorithm consists of two stages: adaptive signal decomposition stage and directional element detection stage based on the Hough-Radon transform (HRT. Initially, the received spread spectrum signal is decomposed into its time-frequency (TF functions using an adaptive signal decomposition algorithm, and the resulting TF functions are mapped onto the TF plane. We then use a line detection algorithm based on the HRT that operates on the image of the TF plane and detects energy varying directional elements that satisfy a parametric constraint. Interference is modeled by reconstructing the corresponding TF functions detected by the HRT, and subtracted from the received signal. The proposed technique has two main advantages: (i it localizes the interferences on the TF plane with no cross-terms, thus facilitating simple filtering techniques based on thresholding of the TF functions, and is an efficient way to excise the interference; (ii it can be used for the detection of any directional interferences that can be parameterized. Simulation results with synthetic models have shown successful performance with linear and quadratic chirp interferences for single and multicomponent interference cases. The proposed method excises the interference even under very low SNR conditions of Ã¢ÂˆÂ’10Ã¢Â€Â‰dB, and the technique could be easily extended to any interferences that could be represented by a parametric equation in the TF plane.
LPI Radar Waveform Recognition Based on Time-Frequency Distribution
Directory of Open Access Journals (Sweden)
Ming Zhang
2016-10-01
Full Text Available In this paper, an automatic radar waveform recognition system in a high noise environment is proposed. Signal waveform recognition techniques are widely applied in the field of cognitive radio, spectrum management and radar applications, etc. We devise a system to classify the modulating signals widely used in low probability of intercept (LPI radar detection systems. The radar signals are divided into eight types of classifications, including linear frequency modulation (LFM, BPSK (Barker code modulation, Costas codes and polyphase codes (comprising Frank, P1, P2, P3 and P4. The classifier is Elman neural network (ENN, and it is a supervised classification based on features extracted from the system. Through the techniques of image filtering, image opening operation, skeleton extraction, principal component analysis (PCA, image binarization algorithm and Pseudo–Zernike moments, etc., the features are extracted from the Choi–Williams time-frequency distribution (CWD image of the received data. In order to reduce the redundant features and simplify calculation, the features selection algorithm based on mutual information between classes and features vectors are applied. The superiority of the proposed classification system is demonstrated by the simulations and analysis. Simulation results show that the overall ratio of successful recognition (RSR is 94.7% at signal-to-noise ratio (SNR of −2 dB.
Sparse time-frequency decomposition based on dictionary adaptation.
Hou, Thomas Y; Shi, Zuoqiang
2016-04-13
In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. © 2016 The Author(s).
Transformation Algorithm of Dielectric Response in Time-Frequency Domain
Directory of Open Access Journals (Sweden)
Ji Liu
2014-01-01
Full Text Available A transformation algorithm of dielectric response from time domain to frequency domain is presented. In order to shorten measuring time of low or ultralow frequency dielectric response characteristics, the transformation algorithm is used in this paper to transform the time domain relaxation current to frequency domain current for calculating the low frequency dielectric dissipation factor. In addition, it is shown from comparing the calculation results with actual test data that there is a coincidence for both results over a wide range of low frequencies. Meanwhile, the time domain test data of depolarization currents in dry and moist pressboards are converted into frequency domain results on the basis of the transformation. The frequency domain curves of complex capacitance and dielectric dissipation factor at the low frequency range are obtained. Test results of polarization and depolarization current (PDC in pressboards are also given at the different voltage and polarization time. It is demonstrated from the experimental results that polarization and depolarization current are affected significantly by moisture contents of the test pressboards, and the transformation algorithm is effective in ultralow frequency of 10−3 Hz. Data analysis and interpretation of the test results conclude that analysis of time-frequency domain dielectric response can be used for assessing insulation system in power transformer.
Time-frequency Representations Application in Psychological Testing
Directory of Open Access Journals (Sweden)
REIZ Romulus
2015-10-01
Full Text Available A psychological test is a test that is designed to measure one aspect of human behavior. These tests are usually designed to evaluate a person’s ability to complete tasks that were individual's performance on certain tasks that have usually been requested in advance. Usually a test score is used to compare with other results to measure the individual’s performance regarding cognitive ability, aptitude, personality, etc. One such test is the so called “finger tapping” test, designed to measure the integrity of the neuromuscular system and examine motor control. There are several ways to perform such a test. The purpose of this paper isn’t to study the finger tapping test which is well documented in the literature, but to develop if possible a simple way of performing such a test. Using the method presented in the paper a nonstationary signal was obtained and it was analyzed using the Short-time Fourier time frequency representation to obtain the signals frequency and its variation in time. The results presented in the paper show that this method can be used to perform the test and the frequency and spatial amplitude of the obtained tapping signal can be determined easily.
Mode Identification of Guided Ultrasonic Wave using Time- Frequency Algorithm
International Nuclear Information System (INIS)
Yoon, Byung Sik; Yang, Seung Han; Cho, Yong Sang; Kim, Yong Sik; Lee, Hee Jong
2007-01-01
The ultrasonic guided waves are waves whose propagation characteristics depend on structural thickness and shape such as those in plates, tubes, rods, and embedded layers. If the angle of incidence or the frequency of sound is adjusted properly, the reflected and refracted energy within the structure will constructively interfere, thereby launching the guided wave. Because these waves penetrate the entire thickness of the tube and propagate parallel to the surface, a large portion of the material can be examined from a single transducer location. The guided ultrasonic wave has various merits like above. But various kind of modes are propagating through the entire thickness, so we don't know the which mode is received. Most of applications are limited from mode selection and mode identification. So the mode identification is very important process for guided ultrasonic inspection application. In this study, various time-frequency analysis methodologies are developed and compared for mode identification tool of guided ultrasonic signal. For this study, a high power tone-burst ultrasonic system set up for the generation and receive of guided waves. And artificial notches were fabricated on the Aluminum plate for the experiment on the mode identification
Time-frequency analysis of band-limited EEG with BMFLC and Kalman filter for BCI applications
2013-01-01
Background Time-Frequency analysis of electroencephalogram (EEG) during different mental tasks received significant attention. As EEG is non-stationary, time-frequency analysis is essential to analyze brain states during different mental tasks. Further, the time-frequency information of EEG signal can be used as a feature for classification in brain-computer interface (BCI) applications. Methods To accurately model the EEG, band-limited multiple Fourier linear combiner (BMFLC), a linear combination of truncated multiple Fourier series models is employed. A state-space model for BMFLC in combination with Kalman filter/smoother is developed to obtain accurate adaptive estimation. By virtue of construction, BMFLC with Kalman filter/smoother provides accurate time-frequency decomposition of the bandlimited signal. Results The proposed method is computationally fast and is suitable for real-time BCI applications. To evaluate the proposed algorithm, a comparison with short-time Fourier transform (STFT) and continuous wavelet transform (CWT) for both synthesized and real EEG data is performed in this paper. The proposed method is applied to BCI Competition data IV for ERD detection in comparison with existing methods. Conclusions Results show that the proposed algorithm can provide optimal time-frequency resolution as compared to STFT and CWT. For ERD detection, BMFLC-KF outperforms STFT and BMFLC-KS in real-time applicability with low computational requirement. PMID:24274109
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.
Time frequency analysis of olfactory induced EEG-power change.
Directory of Open Access Journals (Sweden)
Valentin Alexander Schriever
Full Text Available The objective of the present study was to investigate the usefulness of time-frequency analysis (TFA of olfactory-induced EEG change with a low-cost, portable olfactometer in the clinical investigation of smell function.A total of 78 volunteers participated. The study was composed of three parts where olfactory stimuli were presented using a custom-built olfactometer. Part I was designed to optimize the stimulus as well as the recording conditions. In part II EEG-power changes after olfactory/trigeminal stimulation were compared between healthy participants and patients with olfactory impairment. In Part III the test-retest reliability of the method was evaluated in healthy subjects.Part I indicated that the most effective paradigm for stimulus presentation was cued stimulus, with an interstimulus interval of 18-20s at a stimulus duration of 1000ms with each stimulus quality presented 60 times in blocks of 20 stimuli each. In Part II we found that central processing of olfactory stimuli analyzed by TFA differed significantly between healthy controls and patients even when controlling for age. It was possible to reliably distinguish patients with olfactory impairment from healthy individuals at a high degree of accuracy (healthy controls vs anosmic patients: sensitivity 75%; specificity 89%. In addition we could show a good test-retest reliability of TFA of chemosensory induced EEG-power changes in Part III.Central processing of olfactory stimuli analyzed by TFA reliably distinguishes patients with olfactory impairment from healthy individuals at a high degree of accuracy. Importantly this can be achieved with a simple olfactometer.
Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study.
Ergen, Burhan; Tatar, Yetkin; Gulcur, Halil Ozcan
2012-01-01
Analysis of phonocardiogram (PCG) signals provides a non-invasive means to determine the abnormalities caused by cardiovascular system pathology. In general, time-frequency representation (TFR) methods are used to study the PCG signal because it is one of the non-stationary bio-signals. The continuous wavelet transform (CWT) is especially suitable for the analysis of non-stationary signals and to obtain the TFR, due to its high resolution, both in time and in frequency and has recently become a favourite tool. It decomposes a signal in terms of elementary contributions called wavelets, which are shifted and dilated copies of a fixed mother wavelet function, and yields a joint TFR. Although the basic characteristics of the wavelets are similar, each type of the wavelets produces a different TFR. In this study, eight real types of the most known wavelets are examined on typical PCG signals indicating heart abnormalities in order to determine the best wavelet to obtain a reliable TFR. For this purpose, the wavelet energy and frequency spectrum estimations based on the CWT and the spectra of the chosen wavelets were compared with the energy distribution and the autoregressive frequency spectra in order to determine the most suitable wavelet. The results show that Morlet wavelet is the most reliable wavelet for the time-frequency analysis of PCG signals.
Directory of Open Access Journals (Sweden)
Naranjo Valery
2010-01-01
Full Text Available Signal processing is an essential tool in nondestructive material characterization. Pulse-echo inspection with ultrasonic energy provides signals (A-scans that can be processed in order to obtain parameters which are related to physical properties of inspected materials. Conventional techniques are based on the use of a short-term frequency analysis of the A-scan, obtaining a time-frequency response (TFR, to isolate the evolution of the different frequency-dependent parameters. The application of geometrical estimators to TFRs provides an innovative way to complement conventional techniques based on the one-dimensional evolution of an A-scan extracted parameter (central or centroid frequency, bandwidth, etc.. This technique also provides an alternative method of obtaining similar meaning and less variance estimators. A comparative study of conventional versus new proposed techniques is presented in this paper. The comparative study shows that working with binarized TFRs and the use of shape descriptors provide estimates with lower bias and variance than conventional techniques. Real scattering materials, with different scatterer sizes, have been measured in order to demonstrate the usefulness of the proposed estimators to distinguish among scattering soft tissues. Superior results, using the proposed estimators in real measures, were obtained when classifying according to mean scatterer size.
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
DEFF Research Database (Denmark)
Göçmen Bozkurt, Tuhfe; Giebel, Gregor; Poulsen, Niels Kjølstad
2014-01-01
With increasing installed capacity, wind farms are requested to downregulate more frequently, especially in the offshore environment. Determination and verification of possible (or available) power of downregulated offshore wind farms are the aims of the PossPOW project (see PossPOW.dtu.dk). Two ...... period. The re-calibrated model has to be further parametrized to include dynamic effects such as wind direction variability and meandering also considering different averaging time scales before implemented in full scale wind farms....
Optimal parametric modelling of measured short waves
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
the importance of selecting a suitable sampling interval for better estimates of parametric modelling and also for better statistical representation. Implementation of the above algorithms in a structural monitoring system has the potential advantage of storing...
Blind Time-Frequency Analysis for Source Discrimination in Multisensor Array Processing
National Research Council Canada - National Science Library
Amin, Moeness
1999-01-01
.... We have clearly demonstrated, through analysis and simulations, the offerings of time-frequency distributions in solving key problems in sensor array processing, including direction finding, source...
Masking of Time-Frequency Patterns in Applications of Passive Underwater Target Detection
Directory of Open Access Journals (Sweden)
Jüri Sildam
2010-01-01
Full Text Available Spectrogram analysis of acoustical sounds for underwater target classification is utilized when loud nonstationary interference sources overlap with a signal of interest in time but can be separated in time-frequency (TF domain. We propose a signal masking method which in a TF plane combines local statistical and morphological features of the signal of interest. A dissimilarity measure D of adjacent TF cells is used for local estimation of entropy H, followed by estimation of ΔH=Htc−Hfc entropy difference, where Hfc is calculated along the time axis at a mean frequency fc and Htc is calculated along the frequency axis at a mean time tc of the TF window, respectively. Due to a limited number of points used in ΔH estimation, the number of possible ΔH values, which define a primary mask, is also limited. A secondary mask is defined using morphological operators applied to, for example, H and ΔH. We demonstrate how primary and secondary masks can be used for signal detection and discrimination, respectively. We also show that the proposed approach can be generalized within the framework of Genetic Programming.
Directory of Open Access Journals (Sweden)
Zisheng Wang
2018-02-01
Full Text Available We propose a novel adaptive joint time frequency algorithm combined with the neural network (AJTF-NN to focus the distorted inverse synthetic aperture radar (ISAR image. In this paper, a coefficient estimator based on the artificial neural network (ANN is firstly developed to solve the time-consuming rotational motion compensation (RMC polynomial phase coefficient estimation problem. The training method, the cost function and the structure of ANN are comprehensively discussed. In addition, we originally propose a method to generate training dataset sourcing from the ISAR signal models with randomly chosen motion characteristics. Then, prediction results of the ANN estimator is used to directly compensate the ISAR image, or to provide a more accurate initial searching range to the AJTF for possible low-performance scenarios. Finally, some simulation models including the ideal point scatterers and a realistic Airbus A380 are employed to comprehensively investigate properties of the AJTF-NN, such as the stability and the efficiency under different signal-to-noise ratios (SNRs. Results show that the proposed method is much faster than other prevalent improved searching methods, the acceleration ratio are even up to 424 times without the deterioration of compensated image quality. Therefore, the proposed method is potential to the real-time application in the RMC problem of the ISAR imaging.
On Parametric (and Non-Parametric Variation
Directory of Open Access Journals (Sweden)
Neil Smith
2009-11-01
Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.
Linear and Nonlinear Time-Frequency Analysis for Parameter Estimation of Resident Space Objects
2017-02-22
Vector Machines”, IEEE Trans. on Neural Networks , vol. 13(2), March 2002. [11] T. M. Mitchell, “Machine Learning”, McGraw-Hill, 1997 76DISTRIBUTION A...by the observer is given by: L = n∑ j=1 S(µ, µ0, α)ρjaj (31) where S is the scattering law (or Bidirectional Reflectance Distribution Function, BRDF...vector ma- chine learning”, Adv. Neural Information Processing Systems (NIPS*2000), Cambridge, MA, MIT Press, vol.13, 2001. [9] J., Wetson, and C
A Parametric k-Means Algorithm
Tarpey, Thaddeus
2007-01-01
Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692
Assessing pupil and school performance by non-parametric and parametric techniques
de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.
2010-01-01
This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall
High-Resolution Time-Frequency Spectrum-Based Lung Function Test from a Smartphone Microphone
Directory of Open Access Journals (Sweden)
Tharoeun Thap
2016-08-01
Full Text Available In this paper, a smartphone-based lung function test, developed to estimate lung function parameters using a high-resolution time-frequency spectrum from a smartphone built-in microphone is presented. A method of estimation of the forced expiratory volume in 1 s divided by forced vital capacity (FEV1/FVC based on the variable frequency complex demodulation method (VFCDM is first proposed. We evaluated our proposed method on 26 subjects, including 13 healthy subjects and 13 chronic obstructive pulmonary disease (COPD patients, by comparing with the parameters clinically obtained from pulmonary function tests (PFTs. For the healthy subjects, we found that an absolute error (AE and a root mean squared error (RMSE of the FEV1/FVC ratio were 4.49% ± 3.38% and 5.54%, respectively. For the COPD patients, we found that AE and RMSE from COPD patients were 10.30% ± 10.59% and 14.48%, respectively. For both groups, we compared the results using the continuous wavelet transform (CWT and short-time Fourier transform (STFT, and found that VFCDM was superior to CWT and STFT. Further, to estimate other parameters, including forced vital capacity (FVC, forced expiratory volume in 1 s (FEV1, and peak expiratory flow (PEF, regression analysis was conducted to establish a linear transformation. However, the parameters FVC, FEV1, and PEF had correlation factor r values of 0.323, 0.275, and −0.257, respectively, while FEV1/FVC had an r value of 0.814. The results obtained suggest that only the FEV1/FVC ratio can be accurately estimated from a smartphone built-in microphone. The other parameters, including FVC, FEV1, and PEF, were subjective and dependent on the subject’s familiarization with the test and performance of forced exhalation toward the microphone.
Directory of Open Access Journals (Sweden)
Yang Yu
2016-01-01
Full Text Available Establishing high-speed and reliable underwater acoustic networks among multiunmanned underwater vehicles (UUVs is basic to realize cooperative and intelligent control among different UUVs. Nevertheless, different from terrestrial network, the propagation speed of the underwater acoustic network is 1500 m/s, which makes the design of the underwater acoustic network MAC protocols a big challenge. In accordance with multichannel MAC protocols, data packets and control packets are transferred through different channels, which lowers the adverse effect of acoustic network and gradually becomes the popular issues of underwater acoustic networks MAC protocol research. In this paper, we proposed a control packet collision avoidance algorithm utilizing time-frequency masking to deal with the control packets collision in the control channel. This algorithm is based on the scarcity of the noncoherent underwater acoustic communication signals, which regards collision avoiding as separation of the mixtures of communication signals from different nodes. We first measure the W-Disjoint Orthogonality of the MFSK signals and the simulation result demonstrates that there exists time-frequency mask which can separate the source signals from the mixture of the communication signals. Then we present a pairwise hydrophones separation system based on deep networks and the location information of the nodes. Consequently, the time-frequency mask can be estimated.
Directory of Open Access Journals (Sweden)
Selin Aviyente
2010-01-01
Full Text Available Joint time-frequency representations offer a rich representation of event related potentials (ERPs that cannot be obtained through individual time or frequency domain analysis. This representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to experimentally relevant components are essential. In this paper, we present a method that reduces the large volume of ERP time-frequency data into a few significant time-frequency parameters. The proposed method is based on applying the widely used matching pursuit (MP approach, with a Gabor dictionary, to principal components extracted from the time-frequency domain. The proposed PCA-Gabor decomposition is compared with other time-frequency data reduction methods such as the time-frequency PCA approach alone and standard matching pursuit methods using a Gabor dictionary for both simulated and biological data. The results show that the proposed PCA-Gabor approach performs better than either the PCA alone or the standard MP data reduction methods, by using the smallest amount of ERP data variance to produce the strongest statistical separation between experimental conditions.
Low velocity target detection based on time-frequency image for high frequency ground wave radar
Institute of Scientific and Technical Information of China (English)
YAN Songhua; WU Shicai; WEN Biyang
2007-01-01
The Doppler spectral broadening resulted from non-stationary movement of target and radio-frequency interference will decrease the veracity of target detection by high frequency ground wave(HEGW)radar.By displaying the change of signal energy on two dimensional time-frequency images based on time-frequency analysis,a new mathematical morphology method to distinguish target from nonlinear time-frequency curves is presented.The analyzed results from the measured data verify that with this new method the target can be detected correctly from wide Doppler spectrum.
Continuous-variable quantum computing in optical time-frequency modes using quantum memories.
Humphreys, Peter C; Kolthammer, W Steven; Nunn, Joshua; Barbieri, Marco; Datta, Animesh; Walmsley, Ian A
2014-09-26
We develop a scheme for time-frequency encoded continuous-variable cluster-state quantum computing using quantum memories. In particular, we propose a method to produce, manipulate, and measure two-dimensional cluster states in a single spatial mode by exploiting the intrinsic time-frequency selectivity of Raman quantum memories. Time-frequency encoding enables the scheme to be extremely compact, requiring a number of memories that are a linear function of only the number of different frequencies in which the computational state is encoded, independent of its temporal duration. We therefore show that quantum memories can be a powerful component for scalable photonic quantum information processing architectures.
Time-Frequency Distribution of Music based on Sparse Wavelet Packet Representations
DEFF Research Database (Denmark)
Endelt, Line Ørtoft
We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found using...... the minimization methods basis pursuit and best orthogonal basis. Visualizations of the time-frequency distribution are constructed based on a simplified energy distribution in the wavelet packet decomposition. The time-frequency distributions emphasizes structured musical content, including non-stationary content...
Cooperative Orthogonal Space-Time-Frequency Block Codes over a MIMO-OFDM Frequency Selective Channel
Directory of Open Access Journals (Sweden)
M. Rezaei
2016-03-01
Full Text Available In this paper, a cooperative algorithm to improve the orthogonal space-timefrequency block codes (OSTFBC in frequency selective channels for 2*1, 2*2, 4*1, 4*2 MIMO-OFDM systems, is presented. The algorithm of three node, a source node, a relay node and a destination node is formed, and is implemented in two stages. During the first stage, the destination and the relay antennas receive the symbols sent by the source antennas. The destination node and the relay node obtain the decision variables employing time-space-frequency decoding process by the received signals. During the second stage, the relay node transmits decision variables to the destination node. Due to the increasing diversity in the proposed algorithm, decision variables in the destination node are increased to improve system performance. The bit error rate of the proposed algorithm at high SNR is estimated by considering the BPSK modulation. The simulation results show that cooperative orthogonal space-time-frequency block coding, improves system performance and reduces the BER in a frequency selective channel.
Parametric resonance in an expanding universe
International Nuclear Information System (INIS)
Zlatev, I.; Huey, G.; Steinhardt, P.J.
1998-01-01
Parametric resonance has been discussed as a mechanism for copious particle production following inflation. Here we present a simple and intuitive calculational method for estimating the efficiency of parametric amplification as a function of parameters. This is important for determining whether resonant amplification plays an important role in the reheating process. We find that significant amplification occurs only for a limited range of couplings and interactions. copyright 1998 The American Physical Society
Time-frequency analysis : mathematical analysis of the empirical mode decomposition.
2009-01-01
Invented over 10 years ago, empirical mode : decomposition (EMD) provides a nonlinear : time-frequency analysis with the ability to successfully : analyze nonstationary signals. Mathematical : Analysis of the Empirical Mode Decomposition : is a...
Sun, Wenxiu; Liu, Guoqiang; Xia, Hui; Xia, Zhengwu
2018-03-01
Accurate acquisition of the detection signal travel time plays a very important role in cross-hole tomography. The experimental platform of aluminum plate under the perpendicular magnetic field is established and the bilinear time-frequency analysis methods, Wigner-Ville Distribution (WVD) and the pseudo-Wigner-Ville distribution (PWVD), are applied to analyse the Lamb wave signals detected by electromagnetic acoustic transducer (EMAT). By extracting the same frequency component of the time-frequency spectrum as the excitation frequency, the travel time information can be obtained. In comparison with traditional linear time-frequency analysis method such as short-time Fourier transform (STFT), the bilinear time-frequency analysis method PWVD is more appropriate in extracting travel time and recognizing patterns of Lamb wave.
Time-Frequency Analysis of Terahertz Radar Signals for Rapid Heart and Breath Rate Detection
National Research Council Canada - National Science Library
Massar, Melody L
2008-01-01
We develop new time-frequency analytic techniques which facilitate the detection of a person's heart and breath rates from the Doppler shift the movement of their body induces in a terahertz radar signal...
Molecular quantum control landscapes in von Neumann time-frequency phase space
Ruetzel, Stefan; Stolzenberger, Christoph; Fechner, Susanne; Dimler, Frank; Brixner, Tobias; Tannor, David J.
2010-10-01
Recently we introduced the von Neumann representation as a joint time-frequency description for femtosecond laser pulses and suggested its use as a basis for pulse shaping experiments. Here we use the von Neumann basis to represent multidimensional molecular control landscapes, providing insight into the molecular dynamics. We present three kinds of time-frequency phase space scanning procedures based on the von Neumann formalism: variation of intensity, time-frequency phase space position, and/or the relative phase of single subpulses. The shaped pulses produced are characterized via Fourier-transform spectral interferometry. Quantum control is demonstrated on the laser dye IR140 elucidating a time-frequency pump-dump mechanism.
Blind Time-Frequency Analysis for Source Discrimination in Multisensor Array Processing
National Research Council Canada - National Science Library
Amin, Moeness
2001-01-01
.... We pioneered the development of multi-sensor receivers based on quadratic time-frequency and joint-variable distributions, and have provided the theoretical framework for solving direction finding...
Use of Quadratic Time-Frequency Representations to Analyze Cetacean Mammal Sounds
National Research Council Canada - National Science Library
Papandreou-Suppappola, Antonia
2001-01-01
.... Analysis of the group delay structure of the mammalian vocal communication signals was matched to the appropriate quadratic time-frequency class for proper signal processing with minimal skewing of the results...
Joint time-frequency domain proportional fair scheduler with HARQ for 3GPP LTE systems
Beh, KC; Doufexi, A; Armour, SMD
2008-01-01
This paper explores the potential gain of joint diversity in both frequency domain and time domain which can be exploited to achieve spectral efficiency gains whilst simultaneously facilitating QoS/ fairness in an OFDMA system particularly in 3GPP Long Term Evolution (LTE)). The performance of several joint time-frequency schedulers is investigated. Simulation results show that joint time frequency schedulers achieve significantly superior performance compared to a more conventional time doma...
Damage Detection Based on Cross-Term Extraction from Bilinear Time-Frequency Distributions
Directory of Open Access Journals (Sweden)
Ma Yuchao
2014-01-01
Full Text Available Abundant damage information is implicated in the bilinear time-frequency distribution of structural dynamic signals, which could provide effective support for structural damage identification. Signal time-frequency analysis methods are reviewed, and the characters of linear time-frequency distribution and bilinear time-frequency distribution typically represented by the Wigner-Ville distribution are compared. The existence of the cross-term and its application in structural damage detection are demonstrated. A method of extracting the dominant term is proposed, which combines the short-time Fourier spectrum and Wigner-Ville distribution; then two-dimensional time-frequency transformation matrix is constructed and the complete cross-term is extracted finally. The distribution character of which could be applied to the structural damage identification. Through theoretical analysis, model experiment and numerical simulation of the girder structure, the change rate of cross-term amplitude is validated to identify the damage location and degree. The effectiveness of the cross-term of bilinear time-frequency distribution for damage detection is confirmed and the analytical method of damage identification used in structural engineering is available.
Gear fault diagnosis based on the structured sparsity time-frequency analysis
Sun, Ruobin; Yang, Zhibo; Chen, Xuefeng; Tian, Shaohua; Xie, Yong
2018-03-01
Over the last decade, sparse representation has become a powerful paradigm in mechanical fault diagnosis due to its excellent capability and the high flexibility for complex signal description. The structured sparsity time-frequency analysis (SSTFA) is a novel signal processing method, which utilizes mixed-norm priors on time-frequency coefficients to obtain a fine match for the structure of signals. In order to extract the transient feature from gear vibration signals, a gear fault diagnosis method based on SSTFA is proposed in this work. The steady modulation components and impulsive components of the defective gear vibration signals can be extracted simultaneously by choosing different time-frequency neighborhood and generalized thresholding operators. Besides, the time-frequency distribution with high resolution is obtained by piling different components in the same diagram. The diagnostic conclusion can be made according to the envelope spectrum of the impulsive components or by the periodicity of impulses. The effectiveness of the method is verified by numerical simulations, and the vibration signals registered from a gearbox fault simulator and a wind turbine. To validate the efficiency of the presented methodology, comparisons are made among some state-of-the-art vibration separation methods and the traditional time-frequency analysis methods. The comparisons show that the proposed method possesses advantages in separating feature signals under strong noise and accounting for the inner time-frequency structure of the gear vibration signals.
Directory of Open Access Journals (Sweden)
Jaeyun Lee
2016-01-01
Full Text Available We developed a method to distinguish bursts and suppressions for EEG burst suppression from the treatments of status epilepticus, employing the joint time-frequency domain. We obtained the feature used in the proposed method from the joint use of the time and frequency domains, and we estimated the decision as to whether the measured EEG was a burst segment or suppression segment by the maximum likelihood estimation. We evaluated the performance of the proposed method in terms of its accordance with the visual scores and estimation of the burst suppression ratio. The accuracy was higher than the sole use of the time or frequency domains, as well as conventional methods conducted in the time domain. In addition, probabilistic modeling provided a more simplified optimization than conventional methods. Burst suppression quantification necessitated precise burst suppression segmentation with an easy optimization; therefore, the excellent discrimination and the easy optimization of burst suppression by the proposed method appear to be beneficial.
Motivations of parametric studies
International Nuclear Information System (INIS)
Birac, C.
1988-01-01
The paper concerns the motivations of parametric studies in connection with the Programme for the Inspection of Steel Components PISC II. The objective of the PISC II exercise is to evaluate the effectiveness of current and advanced NDT techniques for inspection of reactor pressure vessel components. The parametric studies were initiated to determine the influence of some parameters on defect detection and dimensioning, and to increase the technical bases of the Round Robin Tests. A description is given of the content of the parametric studies including:- the effect of the defects' characteristics, the effect of equipment characteristics, the effect of cladding, and possible use of electromagnetic techniques. (U.K.)
Study on Fault Diagnosis of Rolling Bearing Based on Time-Frequency Generalized Dimension
Directory of Open Access Journals (Sweden)
Yu Yuan
2015-01-01
Full Text Available The condition monitoring technology and fault diagnosis technology of mechanical equipment played an important role in the modern engineering. Rolling bearing is the most common component of mechanical equipment which sustains and transfers the load. Therefore, fault diagnosis of rolling bearings has great significance. Fractal theory provides an effective method to describe the complexity and irregularity of the vibration signals of rolling bearings. In this paper a novel multifractal fault diagnosis approach based on time-frequency domain signals was proposed. The method and numerical algorithm of Multi-fractal analysis in time-frequency domain were provided. According to grid type J and order parameter q in algorithm, the value range of J and the cut-off condition of q were optimized based on the effect on the dimension calculation. Simulation experiments demonstrated that the effective signal identification could be complete by multifractal method in time-frequency domain, which is related to the factors such as signal energy and distribution. And the further fault diagnosis experiments of bearings showed that the multifractal method in time-frequency domain can complete the fault diagnosis, such as the fault judgment and fault types. And the fault detection can be done in the early stage of fault. Therefore, the multifractal method in time-frequency domain used in fault diagnosis of bearing is a practicable method.
Digital spectral analysis parametric, non-parametric and advanced methods
Castanié, Francis
2013-01-01
Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a
Zhang, Shengli; Tang, Jiong
2016-04-01
Gearbox is one of the most vulnerable subsystems in wind turbines. Its healthy status significantly affects the efficiency and function of the entire system. Vibration based fault diagnosis methods are prevalently applied nowadays. However, vibration signals are always contaminated by noise that comes from data acquisition errors, structure geometric errors, operation errors, etc. As a result, it is difficult to identify potential gear failures directly from vibration signals, especially for the early stage faults. This paper utilizes synchronous averaging technique in time-frequency domain to remove the non-synchronous noise and enhance the fault related time-frequency features. The enhanced time-frequency information is further employed in gear fault classification and identification through feature extraction algorithms including Kernel Principal Component Analysis (KPCA), Multilinear Principal Component Analysis (MPCA), and Locally Linear Embedding (LLE). Results show that the LLE approach is the most effective to classify and identify different gear faults.
Time-Frequency Analysis and Hermite Projection Method Applied to Swallowing Accelerometry Signals
Directory of Open Access Journals (Sweden)
Ervin Sejdić
2010-01-01
Full Text Available Fast Hermite projections have been often used in image-processing procedures such as image database retrieval, projection filtering, and texture analysis. In this paper, we propose an innovative approach for the analysis of one-dimensional biomedical signals that combines the Hermite projection method with time-frequency analysis. In particular, we propose a two-step approach to characterize vibrations of various origins in swallowing accelerometry signals. First, by using time-frequency analysis we obtain the energy distribution of signal frequency content in time. Second, by using fast Hermite projections we characterize whether the analyzed time-frequency regions are associated with swallowing or other phenomena (vocalization, noise, bursts, etc.. The numerical analysis of the proposed scheme clearly shows that by using a few Hermite functions, vibrations of various origins are distinguishable. These results will be the basis for further analysis of swallowing accelerometry to detect swallowing difficulties.
Rock, N. M. S.
ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures
Nonlinear system identification NARMAX methods in the time, frequency, and spatio-temporal domains
Billings, Stephen A
2013-01-01
Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by
Directory of Open Access Journals (Sweden)
Sabyasachi Guharay
2017-07-01
Full Text Available Value-at-Risk (VaR is a well-accepted risk metric in modern quantitative risk management (QRM. The classical Monte Carlo simulation (MCS approach, denoted henceforth as the classical approach, assumes the independence of loss severity and loss frequency. In practice, this assumption does not always hold true. Through mathematical analyses, we show that the classical approach is prone to significant biases when the independence assumption is violated. This is also corroborated by studying both simulated and real-world datasets. To overcome the limitations and to more accurately estimate VaR, we develop and implement the following two approaches for VaR estimation: the data-driven partitioning of frequency and severity (DPFS using clustering analysis, and copula-based parametric modeling of frequency and severity (CPFS. These two approaches are verified using simulation experiments on synthetic data and validated on five publicly available datasets from diverse domains; namely, the financial indices data of Standard & Poor’s 500 and the Dow Jones industrial average, chemical loss spills as tracked by the US Coast Guard, Australian automobile accidents, and US hurricane losses. The classical approach estimates VaR inaccurately for 80% of the simulated data sets and for 60% of the real-world data sets studied in this work. Both the DPFS and the CPFS methodologies attain VaR estimates within 99% bootstrap confidence interval bounds for both simulated and real-world data. We provide a process flowchart for risk practitioners describing the steps for using the DPFS versus the CPFS methodology for VaR estimation in real-world loss datasets.
Huart, C; Rombaux, Ph; Hummel, T; Mouraux, A
2013-09-01
The clinical usefulness of olfactory event-related brain potentials (OERPs) to assess olfactory function is limited by the relatively low signal-to-noise ratio of the responses identified using conventional time-domain averaging. Recently, it was shown that time-frequency analysis of the obtained EEG signals can markedly improve the signal-to-noise ratio of OERPs in healthy controls, because it enhances both phase-locked and non phase-locked EEG responses. The aim of the present study was to investigate the clinical usefulness of this approach and evaluate its feasibility in a clinical setting. We retrospectively analysed EEG recordings obtained from 45 patients (15 anosmic, 15 hyposmic and 15 normos- mic). The responses to olfactory stimulation were analysed using conventional time-domain analysis and joint time-frequency analysis. The ability of the two methods to discriminate between anosmic, hyposmic and normosmic patients was assessed using a Receiver Operating Characteristic analysis. The discrimination performance of OERPs identified using conventional time-domain averaging was poor. In contrast, the discrimination performance of the EEG response identified in the time-frequency domain was relatively high. Furthermore, we found a significant correlation between the magnitude of this response and the psychophysical olfactory score. Time-frequency analysis of the EEG responses to olfactory stimulation could be used as an effective and reliable diagnostic tool for the objective clinical evaluation of olfactory function in patients.
Overcomplete Blind Source Separation by Combining ICA and Binary Time-Frequency Masking
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan
2005-01-01
a novel method for over-complete blind source separation. Two powerful source separation techniques have been combined, independent component analysis and binary time-frequency masking. Hereby, it is possible to iteratively extract each speech signal from the mixture. By using merely two microphones we...
On the locus and spread of pseudo-density functions in the time-frequency plane
Janssen, A.J.E.M.
1982-01-01
Various time-frequency pseudo-density functions used in signal analysis are compared with respect to spread. Among the members of Cohen's class of pseudo-density functions satisfying the finite support property as well as Moyal's formula, the Wigner distribution is the most well-behaved one in the
Synchronization and matched filtering in time-frequency using the sunflower spiral
Korevaar, C.W.; Kokkeler, Andre B.J.; de Boer, Pieter-Tjerk; Smit, Gerardus Johannes Maria
2012-01-01
Synchronization and matched filtering of signals in time dispersive, frequency dispersive and time-frequency dispersive channels are addressed in this paper. The ‘eigenfunctions’ of these channels form the signal sets under investigation. While using channel-eigenfunctions is a first requirement for
Vibration sensor data denoising using a time-frequency manifold for machinery fault diagnosis.
He, Qingbo; Wang, Xiangxiang; Zhou, Qiang
2013-12-27
Vibration sensor data from a mechanical system are often associated with important measurement information useful for machinery fault diagnosis. However, in practice the existence of background noise makes it difficult to identify the fault signature from the sensing data. This paper introduces the time-frequency manifold (TFM) concept into sensor data denoising and proposes a novel denoising method for reliable machinery fault diagnosis. The TFM signature reflects the intrinsic time-frequency structure of a non-stationary signal. The proposed method intends to realize data denoising by synthesizing the TFM using time-frequency synthesis and phase space reconstruction (PSR) synthesis. Due to the merits of the TFM in noise suppression and resolution enhancement, the denoised signal would have satisfactory denoising effects, as well as inherent time-frequency structure keeping. Moreover, this paper presents a clustering-based statistical parameter to evaluate the proposed method, and also presents a new diagnostic approach, called frequency probability time series (FPTS) spectral analysis, to show its effectiveness in fault diagnosis. The proposed TFM-based data denoising method has been employed to deal with a set of vibration sensor data from defective bearings, and the results verify that for machinery fault diagnosis the method is superior to two traditional denoising methods.
Enhanced Performance by Time-Frequency-Phase Feature for EEG-Based BCI Systems
Directory of Open Access Journals (Sweden)
Baolei Xu
2014-01-01
Full Text Available We introduce a new motor parameter imagery paradigm using clench speed and clench force motor imagery. The time-frequency-phase features are extracted from mu rhythm and beta rhythms, and the features are optimized using three process methods: no-scaled feature using “MIFS” feature selection criterion, scaled feature using “MIFS” feature selection criterion, and scaled feature using “mRMR” feature selection criterion. Support vector machines (SVMs and extreme learning machines (ELMs are compared for classification between clench speed and clench force motor imagery using the optimized feature. Our results show that no significant difference in the classification rate between SVMs and ELMs is found. The scaled feature combinations can get higher classification accuracy than the no-scaled feature combinations at significant level of 0.01, and the “mRMR” feature selection criterion can get higher classification rate than the “MIFS” feature selection criterion at significant level of 0.01. The time-frequency-phase feature can improve the classification rate by about 20% more than the time-frequency feature, and the best classification rate between clench speed motor imagery and clench force motor imagery is 92%. In conclusion, the motor parameter imagery paradigm has the potential to increase the direct control commands for BCI control and the time-frequency-phase feature has the ability to improve BCI classification accuracy.
PARAMETRIC DRAWINGS VS. AUTOLISP
Directory of Open Access Journals (Sweden)
PRUNĂ Liviu
2015-06-01
Full Text Available In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed by the drawing, in the idea to construct outlines or blocks which can be used in the projection process.
PARAMETRIC DRAWINGS VS. AUTOLISP
PRUNĂ Liviu; SLONOVSCHI Andrei
2015-01-01
In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed...
Applying Parametric Fault Detection to a Mechanical System
DEFF Research Database (Denmark)
Felício, P.; Stoustrup, Jakob; Niemann, H.
2002-01-01
A way of doing parametric fault detection is described. It is based on the representation of parameter changes as linear fractional transformations (lfts). We describe a model with parametric uncertainty. Then a stabilizing controller is chosen and its robustness properties are studied via mu. Th....... The parameter changes (faults) are estimated based on estimates of the fictitious signals that enter the delta block in the lft. These signal estimators are designed by H-infinity techniques. The chosen example is an inverted pendulum....
Statistical prediction of parametric roll using FORM
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher; Choi, Ju-hyuck; Nielsen, Ulrik Dam
2017-01-01
Previous research has shown that the First Order Reliability Method (FORM) can be an efficient method for estimation of outcrossing rates and extreme value statistics for stationary stochastic processes. This is so also for bifurcation type of processes like parametric roll of ships. The present...
International Nuclear Information System (INIS)
Bizarro, Joao P.S.; Figueiredo, Antonio C.A.
2008-01-01
Performing a time-frequency (t-f) analysis on actual magnetic pick-up coil data from the JET tokamak, a comparison is presented between the spectrogram and the Wigner and Choi-Williams distributions. Whereas the former, which stems from the short-time Fourier transform and has been the work-horse for t-f signal processing, implies an unavoidable trade-off between time and frequency resolutions, the latter two belong to a later generation of distributions that yield better, if not optimal joint t-f localization. Topics addressed include signal representation in the t-f plane, frequency identification and evolution, instantaneous-frequency estimation, and amplitude tracking
Universal parametrization for quark and lepton substructure
International Nuclear Information System (INIS)
Akama, Keiichi; Terazawa, Hidezumi.
1994-01-01
A universal parametrization for possible quark and lepton substructure is advocated in terms of quark and lepton form factors. It is emphasized that the lower bounds on compositeness scale, Λ c , to be determined experimentally strongly depend on their definitions in composite models. From the recent HERA data, it is estimated to be Λ c > 50 GeV, 0.4 TeV and 10 TeV, depending on the parametrizations with a single-pole form factor, a contact interaction and a logarithmic form factor, respectively. (author)
Controlling Parametric Resonance
DEFF Research Database (Denmark)
Galeazzi, Roberto; Pettersen, Kristin Ytterstad
2012-01-01
the authors review the conditions for the onset of parametric resonance, and propose a nonlinear control strategy in order to both induce the resonant oscillations and to stabilize the unstable motion. Lagrange’s theory is used to derive the dynamics of the system and input–output feedback linearization...
Ecological prediction with nonlinear multivariate time-frequency functional data models
Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.
2013-01-01
Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.
International Nuclear Information System (INIS)
Jin Jing; Wei Biao; Feng Peng; Tang Yuelin; Zhou Mi
2010-01-01
Based on the interdependent relationship between fission neutrons ( 252 Cf) and fission chain ( 235 U system), the paper presents the time-frequency feature analysis and recognition in fission neutron signal based on support vector machine (SVM) through the analysis on signal characteristics and the measuring principle of the 252 Cf fission neutron signal. The time-frequency characteristics and energy features of the fission neutron signal are extracted by using wavelet decomposition and de-noising wavelet packet decomposition, and then applied to training and classification by means of support vector machine based on statistical learning theory. The results show that, it is effective to obtain features of nuclear signal via wavelet decomposition and de-noising wavelet packet decomposition, and the latter can reflect the internal characteristics of the fission neutron system better. With the training accomplished, the SVM classifier achieves an accuracy rate above 70%, overcoming the lack of training samples, and verifying the effectiveness of the algorithm. (authors)
Features of the use of time-frequency distributions for controlling the mixture-producing aggregate
Fedosenkov, D. B.; Simikova, A. A.; Fedosenkov, B. A.
2018-05-01
The paper submits and argues the information on filtering properties of the mixing unit as a part of the mixture-producing aggregate. Relevant theoretical data concerning a channel transfer function of the mixing unit and multidimensional material flow signals are adduced here. Note that ordinary one-dimensional material flow signals are defined in terms of time-frequency distributions of Cohen’s class representations operating with Gabor wavelet functions. Two time-frequencies signal representations are written about in the paper to show how one can solve controlling problems as applied to mixture-producing systems: they are the so-called Rihaczek and Wigner-Ville distributions. In particular, the latter illustrates low-pass filtering properties that are practically available in any of low-pass elements of a physical system.
Efficient coding schemes with power allocation using space-time-frequency spreading
Institute of Scientific and Technical Information of China (English)
Jiang Haining; Luo Hanwen; Tian Jifeng; Song Wentao; Liu Xingzhao
2006-01-01
An efficient space-time-frequency (STF) coding strategy for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is presented for high bit rate data transmission over frequency selective fading channels. The proposed scheme is a new approach to space-time-frequency coded OFDM (COFDM) that combines OFDM with space-time coding, linear precoding and adaptive power allocation to provide higher quality of transmission in terms of the bit error rate performance and power efficiency. In addition to exploiting the maximum diversity gain in frequency, time and space, the proposed scheme enjoys high coding advantages and low-complexity decoding. The significant performance improvement of our design is confirmed by corroborating numerical simulations.
International Nuclear Information System (INIS)
Lee, Sang Kee; Nam, Ki Woo; Kang, Chang Yong; Do, Jae Yoon
2000-01-01
On this study, the fatigue crack propagation of super duplex stainless steel is investigated in conditions of various volume fraction of austenite phase by changing heat treatment temperature. And we analysed acoustic emission signals during the fatigue test by time-frequency analysis methods. As the temperature of heat treatment increased, volume fraction of austenite decreased and coarse grain was obtained. The specimen heat treated at 1200 deg. C had longer fatigue life and slower rate of crack growth. As a result of time-frequency analyze of acoustic emission signals during fatigue test, main frequency was 200∼300 kHz having no correlation with heat treatment and crack length, and 500 kHz was obtained by dimple and separate of inclusion
Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise
Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En
2018-01-01
In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method. PMID:29565288
Directory of Open Access Journals (Sweden)
Howard A. Gaberson
1995-01-01
Full Text Available This article discusses time frequency analysis of machinery diagnostic vibration signals. The short time Fourier transform, the Wigner, and the Choi–Williams distributions are explained and illustrated with test cases. Examples of Choi—Williams analyses of machinery vibration signals are presented. The analyses detect discontinuities in the signals and their timing, amplitude and frequency modulation, and the presence of different components in a vibration signal.
Bearing performance degradation assessment based on time-frequency code features and SOM network
International Nuclear Information System (INIS)
Zhang, Yan; Tang, Baoping; Han, Yan; Deng, Lei
2017-01-01
Bearing performance degradation assessment and prognostics are extremely important in supporting maintenance decision and guaranteeing the system’s reliability. To achieve this goal, this paper proposes a novel feature extraction method for the degradation assessment and prognostics of bearings. Features of time-frequency codes (TFCs) are extracted from the time-frequency distribution using a hybrid procedure based on short-time Fourier transform (STFT) and non-negative matrix factorization (NMF) theory. An alternative way to design the health indicator is investigated by quantifying the similarity between feature vectors using a self-organizing map (SOM) network. On the basis of this idea, a new health indicator called time-frequency code quantification error (TFCQE) is proposed to assess the performance degradation of the bearing. This indicator is constructed based on the bearing real-time behavior and the SOM model that is previously trained with only the TFC vectors under the normal condition. Vibration signals collected from the bearing run-to-failure tests are used to validate the developed method. The comparison results demonstrate the superiority of the proposed TFCQE indicator over many other traditional features in terms of feature quality metrics, incipient degradation identification and achieving accurate prediction. Highlights • Time-frequency codes are extracted to reflect the signals’ characteristics. • SOM network served as a tool to quantify the similarity between feature vectors. • A new health indicator is proposed to demonstrate the whole stage of degradation development. • The method is useful for extracting the degradation features and detecting the incipient degradation. • The superiority of the proposed method is verified using experimental data. (paper)
Classification rates: non‐parametric verses parametric models using ...
African Journals Online (AJOL)
This research sought to establish if non parametric modeling achieves a higher correct classification ratio than a parametric model. The local likelihood technique was used to model fit the data sets. The same sets of data were modeled using parametric logit and the abilities of the two models to correctly predict the binary ...
Blind Separation of Nonstationary Sources Based on Spatial Time-Frequency Distributions
Directory of Open Access Journals (Sweden)
Zhang Yimin
2006-01-01
Full Text Available Blind source separation (BSS based on spatial time-frequency distributions (STFDs provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localized in the time-frequency (t-f domain. In this paper, we propose the use of STFD matrices for both whitening and recovery of the mixing matrix, which are two stages commonly required in many BSS methods, to provide robust BSS performance to noise. In addition, a simple method is proposed to select the auto- and cross-term regions of time-frequency distribution (TFD. To further improve the BSS performance, t-f grouping techniques are introduced to reduce the number of signals under consideration, and to allow the receiver array to separate more sources than the number of array sensors, provided that the sources have disjoint t-f signatures. With the use of one or more techniques proposed in this paper, improved performance of blind separation of nonstationary signals can be achieved.
Directory of Open Access Journals (Sweden)
Filippo Molinari
2010-01-01
Full Text Available Near-infrared spectroscopy (NIRS is a noninvasive system for the real-time monitoring of the concentration of oxygenated (O2Hb and reduced (HHb hemoglobin in the brain cortex. O2Hb and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20–40 mHz and of the low frequencies (LF: 40–140 mHz. Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.
Directory of Open Access Journals (Sweden)
Liboni William
2010-01-01
Full Text Available Abstract Near-infrared spectroscopy (NIRS is a noninvasive system for the real-time monitoring of the concentration of oxygenated ( and reduced (HHb hemoglobin in the brain cortex. and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20–40 mHz and of the low frequencies (LF: 40–140 mHz. Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.
Analysis of muscle fatigue conditions using time-frequency images and GLCM features
Directory of Open Access Journals (Sweden)
Karthick P.A.
2016-09-01
Full Text Available In this work, an attempt has been made to differentiate muscle non-fatigue and fatigue conditions using sEMG signals and texture representation of the time-frequency images. The sEMG signals are recorded from the biceps brachii muscle of 25 healthy adult volunteers during dynamic fatiguing contraction. The first and last curls of these signals are considered as the non-fatigue and fatigue zones, respectively. These signals are preprocessed and the time-frequency spectrum is computed using short time fourier transform (STFT. Gray-Level Co-occurrence Matrix (GLCM is extracted from low (15–45 Hz, medium (46–95 Hz and high (96–150 Hz frequency bands of the time-frequency images. Further, the features such as contrast, correlation, energy and homogeneity are calculated from the resultant matrices. The results show that the high frequency band based features are able to differentiate non-fatigue and fatigue conditions. The features such as correlation, contrast and homogeneity extracted at angles 0°, 45°, 90°, and 135° are found to be distinct with high statistical significance (p < 0.0001. Hence, this framework can be used for analysis of neuromuscular disorders.
Towards Stabilizing Parametric Active Contours
DEFF Research Database (Denmark)
Liu, Jinchao; Fan, Zhun; Olsen, Søren Ingvor
2014-01-01
Numerical instability often occurs in evolving of parametric active contours. This is mainly due to the undesired change of parametrization during evolution. In this paper, we propose a new tangential diffusion term to compensate this undesired change. As a result, the parametrization will converge...
MEMS digital parametric loudspeaker
Carreno, Armando Arpys Arevalo
2016-03-23
This paper reports on the design and fabrication of MEMS actuator arrays suitable for Digital Sound reconstruction and Parametric Directional Loudspeakers. Two distinct versions of the device were fabricated: one using the electrostatic principle actuation and the other one, the piezoelectric principle. Both versions used similar membrane dimensions, with a diameter of 500 μm. These devices are the smallest Micro-Machined Ultrasound Transducer (MUT) arrays that can be operated for both modes: Digital Sound Reconstruction and Parametric Loudspeaker. The chips consist of an array with 256 transducers, in a footprint of 12 mm by 12 mm. The total single chip size is: 2.3 cm by 2.3 cm, including the contact pads. © 2016 IEEE.
Parametric Explosion Spectral Model
Energy Technology Data Exchange (ETDEWEB)
Ford, S R; Walter, W R
2012-01-19
Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. Explosion spectra can be fit with similar spectral models whose parameters are then correlated with near-source geology and containment conditions. We observe a correlation of high gas-porosity (low-strength) with increased spectral slope. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.
MEMS digital parametric loudspeaker
Carreno, Armando Arpys Arevalo; Castro, David; Conchouso Gonzalez, David; Kosel, Jü rgen; Foulds, Ian G.
2016-01-01
This paper reports on the design and fabrication of MEMS actuator arrays suitable for Digital Sound reconstruction and Parametric Directional Loudspeakers. Two distinct versions of the device were fabricated: one using the electrostatic principle actuation and the other one, the piezoelectric principle. Both versions used similar membrane dimensions, with a diameter of 500 μm. These devices are the smallest Micro-Machined Ultrasound Transducer (MUT) arrays that can be operated for both modes: Digital Sound Reconstruction and Parametric Loudspeaker. The chips consist of an array with 256 transducers, in a footprint of 12 mm by 12 mm. The total single chip size is: 2.3 cm by 2.3 cm, including the contact pads. © 2016 IEEE.
Macromechanical Parametric Amplification
DEFF Research Database (Denmark)
Neumeyer, Stefan
between the two peaks can be altered. The first experimental bistable amplified steady-state responses are also reported. The derived analytical models and experimental setups can readily be extended to investigate other factors. Some of the results are also applicable to the more general field of systems...... for energy harvesting. Using analytical, numerical, and experimental methods, the thesis focuses on superthreshold pumping (above the systems parametric instability threshold), nonlinear effects, frequency response backbones, and frequency detuning effects for parametric amplifiers. Part one of the thesis...... covers superthreshold pumping and nonlinear effects. Superthresh-old pumping produces some useful characteristics. For instance, strong superthreshold pumping yields a high gain even though nonlinear effects tend to reduce it. In addition, a narrower excitation phase range is realized for which...
Energy Technology Data Exchange (ETDEWEB)
Castillo Escario, Y.; Blanco Almazan, D.; Camara Vazquez, M.A.; Jane Campos, R.
2016-07-01
Obstructive sleep apnea (OSA) is a highly prevalent chronic disease, especially in elderly and obese population. Despite constituting a huge health and economic problem, most patients remain undiagnosed due to limitations in current strategies. Therefore, it is essential to find cost-effective diagnostic alternatives. One of these novel approaches is the analysis of acoustic snoring signals. Snoring is an early symptom of OSA which carries pathophysiological information of high diagnostic value. For this reason, the main objective of this work is to study the characteristics of single snores of different types, from healthy and OSA subjects. To do that, we analyzed snoring signals from previous databases and developed an experimental protocol to record simulated OSA-related sounds and characterize the response of two commercial tracheal microphones. Automatic programs for filtering, downsampling, event detection and time-frequency analysis were built in MATLAB. We found that time-frequency maps and spectral parameters (central, mean and peak frequency and energy in the 100-500 Hz band) allow distinguishing regular snores of healthy subjects from non-regular snores and snores of OSA subjects. Regarding the two commercial microphones, we found that one of them was a suitable snoring sensor, while the other had a too restricted frequency response. Future work shall include a higher number of episodes and subjects, but our study has contributed to show how important the differences between regular and non-regular snores can be for OSA diagnosis, and how much clinically relevant information can be extracted from time-frequency maps and spectral parameters of single snores. (Author)
Parametric Resonance in Dynamical Systems
Nijmeijer, Henk
2012-01-01
Parametric Resonance in Dynamical Systems discusses the phenomenon of parametric resonance and its occurrence in mechanical systems,vehicles, motorcycles, aircraft and marine craft, and micro-electro-mechanical systems. The contributors provide an introduction to the root causes of this phenomenon and its mathematical equivalent, the Mathieu-Hill equation. Also included is a discussion of how parametric resonance occurs on ships and offshore systems and its frequency in mechanical and electrical systems. This book also: Presents the theory and principles behind parametric resonance Provides a unique collection of the different fields where parametric resonance appears including ships and offshore structures, automotive vehicles and mechanical systems Discusses ways to combat, cope with and prevent parametric resonance including passive design measures and active control methods Parametric Resonance in Dynamical Systems is ideal for researchers and mechanical engineers working in application fields such as MEM...
Cardiovascular response to acute stress in freely moving rats: time-frequency analysis.
Loncar-Turukalo, Tatjana; Bajic, Dragana; Japundzic-Zigon, Nina
2008-01-01
Spectral analysis of cardiovascular series is an important tool for assessing the features of the autonomic control of the cardiovascular system. In this experiment Wistar rats ecquiped with intraarterial catheter for blood pressure (BP) recording were exposed to stress induced by blowing air. The problem of non stationary data was overcomed applying the Smoothed Pseudo Wigner Villle (SPWV) time-frequency distribution. Spectral analysis was done before stress, during stress, immediately after stress and later in recovery. The spectral indices were calculated for both systolic blood pressure (SBP) and pulse interval (PI) series. The time evolution of spectral indices showed perturbed sympathovagal balance.
Carbon financial markets: A time-frequency analysis of CO2 prices
Sousa, Rita; Aguiar-Conraria, Luís; Soares, Maria Joana
2014-11-01
We characterize the interrelation of CO2 prices with energy prices (electricity, gas and coal), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.
Spectrally Efficient OFDMA Lattice Structure via Toroidal Waveforms on the Time-Frequency Plane
Directory of Open Access Journals (Sweden)
Sultan Aldirmaz
2010-01-01
Full Text Available We investigate the performance of frequency division multiplexed (FDM signals, where multiple orthogonal Hermite-Gaussian carriers are used to increase the bandwidth efficiency. Multiple Hermite-Gaussian functions are modulated by a data set as a multicarrier modulation scheme in a single time-frequency region constituting toroidal waveform in a rectangular OFDMA system. The proposed work outperforms in the sense of bandwidth efficiency compared to the transmission scheme where only single Gaussian pulses are used as the transmission base. We investigate theoretical and simulation results of the proposed methods.
Time-frequency analysis with temporal and spectral resolution as the human auditory system
DEFF Research Database (Denmark)
Agerkvist, Finn T.
1992-01-01
The human perception of sound is a suitable area for the application of a simultaneous time-frequency analysis, since the ear is selective in both domains. A perfect reconstruction filter bank with bandwidths approximating the critical bands is presented. The orthogonality of the filter makes...... it possible to examine the masking effect with realistic signals. The tree structure of the filter bank makes it difficult to obtain well-attenuated stop-bands. The use of filters of different length solves this problem...
Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution
Zoladz, T. F.; Jones, J. H.; Jong, J.
1992-01-01
A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.
The Real-time Frequency Spectrum Analysis of Neutron Pulse Signal Series
International Nuclear Information System (INIS)
Tang Yuelin; Ren Yong; Wei Biao; Feng Peng; Mi Deling; Pan Yingjun; Li Jiansheng; Ye Cenming
2009-01-01
The frequency spectrum analysis of neutron pulse signal is a very important method in nuclear stochastic signal processing Focused on the special '0' and '1' of neutron pulse signal series, this paper proposes new rotation-table and realizes a real-time frequency spectrum algorithm under 1G Hz sample rate based on PC with add, address and SSE. The numerical experimental results show that under the count rate of 3X10 6 s -1 , this algorithm is superior to FFTW in time-consumption and can meet the real-time requirement of frequency spectrum analysis. (authors)
Melkonian, D; Korner, A; Meares, R; Bahramali, H
2012-10-01
A novel method of the time-frequency analysis of non-stationary heart rate variability (HRV) is developed which introduces the fragmentary spectrum as a measure that brings together the frequency content, timing and duration of HRV segments. The fragmentary spectrum is calculated by the similar basis function algorithm. This numerical tool of the time to frequency and frequency to time Fourier transformations accepts both uniform and non-uniform sampling intervals, and is applicable to signal segments of arbitrary length. Once the fragmentary spectrum is calculated, the inverse transform recovers the original signal and reveals accuracy of spectral estimates. Numerical experiments show that discontinuities at the boundaries of the succession of inter-beat intervals can cause unacceptable distortions of the spectral estimates. We have developed a measure that we call the "RR deltagram" as a form of the HRV data that minimises spectral errors. The analysis of the experimental HRV data from real-life and controlled breathing conditions suggests transient oscillatory components as functionally meaningful elements of highly complex and irregular patterns of HRV. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Using non-parametric methods in econometric production analysis
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
2012-01-01
by investigating the relationship between the elasticity of scale and the farm size. We use a balanced panel data set of 371~specialised crop farms for the years 2004-2007. A non-parametric specification test shows that neither the Cobb-Douglas function nor the Translog function are consistent with the "true......Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify a functional form of the production function of which the Cobb...... parameter estimates, but also in biased measures which are derived from the parameters, such as elasticities. Therefore, we propose to use non-parametric econometric methods. First, these can be applied to verify the functional form used in parametric production analysis. Second, they can be directly used...
Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling
Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng
2016-01-01
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974
IP Controller Design for Uncertain Two-Mass Torsional System Using Time-Frequency Analysis
Directory of Open Access Journals (Sweden)
Jing Cui
2018-01-01
Full Text Available With the development of industrial production, drive systems are demanded for larger inertias of motors and load machines, whereas shafts should be lightweight. In this situation, it will excite mechanical vibrations in load side, which is harmful for industrial production when the motor works. Because of the complexity of the flexible shaft, it is often difficult to calculate stiffness coefficient of the flexible shaft. Furthermore, only the velocity of driving side could be measured, whereas the driving torque, the load torque, and the velocity of load side are immeasurable. Therefore, it is inconvenient to design the controller for the uncertain system. In this paper, a low-order IP controller is designed for an uncertain two-mass torsional system based on polynomial method and time-frequency analysis (TFA. IP controller parameters are calculated by inertias of driving side and load side as well as the resonant frequency based on polynomial method. Therein, the resonant frequency is identified using the time-frequency analysis (TFA of the velocity step response of the driving side under the open-loop system state, which can not only avoid harmful persistent start-stop excitation signal of the traditional method, but also obtain high recognition accuracy under the condition of weak vibration signal submerged in noise. The effectiveness of the designed IP controller is verified by groups of experiments. Experimental results show that good performance for vibration suppression is obtained for uncertain two-mass torsional system in a medium-low shaft stiffness condition.
Mitchell, Patrick; Krotish, Debra; Shin, Yong-June; Hirth, Victor
2010-12-01
The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.
Study on time-frequency analysis method of very fast transient overvoltage
Li, Shuai; Liu, Shiming; Huang, Qiyan; Fu, Chuanshun
2018-04-01
The operation of the disconnector in the gas insulated substation (GIS) may produce very fast transient overvoltage (VFTO), which has the characteristics of short rise time, short duration, high amplitude and rich frequency components. VFTO can cause damage to GIS and secondary equipment, and the frequency components contained in the VFTO can cause resonance overvoltage inside the transformer, so it is necessary to study the spectral characteristics of the VFTO. From the perspective of signal processing, VFTO is a kind of non-stationary signal, the traditional Fourier transform is difficult to describe its frequency which changes with time, so it is necessary to use time-frequency analysis to analyze VFTO spectral characteristics. In this paper, we analyze the performance of short time Fourier transform (STFT), Wigner-Ville distribution (WVD), pseudo Wigner-Ville distribution (PWVD) and smooth pseudo Wigner-Ville distribution (SPWVD). The results show that SPWVD transform is the best. The time-frequency aggregation of SPWVD is higher than STFT, and it does not have cross-interference terms, which can meet the requirements of VFTO spectrum analysis.
Application of Time-Frequency Domain Transform to Three-Dimensional Interpolation of Medical Images.
Lv, Shengqing; Chen, Yimin; Li, Zeyu; Lu, Jiahui; Gao, Mingke; Lu, Rongrong
2017-11-01
Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm. What is more, the characteristics of wavelet transform and Sobel operator are used. They deal with the sub-images of wavelet decomposition separately. Sobel edge detection 3D matching interpolation method is used in low-frequency sub-images under the circumstances of ensuring high frequency undistorted. Through wavelet reconstruction, it can get the target interpolation image. In this article, we make 3D interpolation of the real computed tomography (CT) images. Compared with other interpolation methods, our proposed method is verified to be effective and superior.
Aurally-adequate time-frequency analysis for scattered sound in auditoria
Norris, Molly K.; Xiang, Ning; Kleiner, Mendel
2005-04-01
The goal of this work was to apply an aurally-adequate time-frequency analysis technique to the analysis of sound scattering effects in auditoria. Time-frequency representations were developed as a motivated effort that takes into account binaural hearing, with a specific implementation of interaural cross-correlation process. A model of the human auditory system was implemented in the MATLAB platform based on two previous models [A. Härmä and K. Palomäki, HUTear, Espoo, Finland; and M. A. Akeroyd, A. Binaural Cross-correlogram Toolbox for MATLAB (2001), University of Sussex, Brighton]. These stages include proper frequency selectivity, the conversion of the mechanical motion of the basilar membrane to neural impulses, and binaural hearing effects. The model was then used in the analysis of room impulse responses with varying scattering characteristics. This paper discusses the analysis results using simulated and measured room impulse responses. [Work supported by the Frank H. and Eva B. Buck Foundation.
Quantitative analysis of sleep EEG microstructure in the time-frequency domain.
De Carli, Fabrizio; Nobili, Lino; Beelke, Manolo; Watanabe, Tsuyoshi; Smerieri, Arianna; Parrino, Liborio; Terzano, Mario Giovanni; Ferrillo, Franco
2004-06-30
A number of phasic events influence sleep quality and sleep macrostructure. The detection of arousals and the analysis of cyclic alternating patterns (CAP) support the evaluation of sleep fragmentation and instability. Sixteen polygraphic overnight recordings were visually inspected for conventional Rechtscaffen and Kales scoring, while arousals were detected following the criteria of the American Sleep Disorders Association (ASDA). Three electroencephalograph (EEG) segments were associated to each event, corresponding to background activity, pre-arousal period and arousal. The study was supplemented by the analysis of time-frequency distribution of EEG within each subtype of phase A in the CAP. The arousals were characterized by the increase of alpha and beta power with regard to background. Within NREM sleep most of the arousals were preceded by a transient increase of delta power. The time-frequency evolution of the phase A of the CAP sequence showed a strong prevalence of delta activity during the whole A1, but high amplitude delta waves were found also in the first 2/3 s of A2 and A3, followed by desynchronization. Our results underline the strict relationship between the ASDA arousals, and the subtype A2 and A3 within the CAP: in both the association between a short sequence of transient slow waves and the successive increase of frequency and decrease of amplitude characterizes the arousal response.
Directory of Open Access Journals (Sweden)
Gannon Stromquist-LeVoir
2018-01-01
Full Text Available A feasibility study was conducted to develop a novel method to determine the temporal changes of tensile forces in bridge suspender cables using time-frequency analysis of ambient vibration measurements. An analytical model of the suspender cables was developed to evaluate the power spectral density (PSD function of a cable with consideration of cable flexural stiffness. Discrete-time, short-time Fourier transform (STFT was utilized to analyze the recorded acceleration histories in both time and frequency domains. A mathematical convolution of the analytical PSD function and time-frequency data was completed to evaluate changes in cable tension force over time. The method was implemented using acceleration measurements collected from an in-service steel arch bridge with a suspended deck to calculate the temporal variation in cable forces from the vibration measurements. The observations served as proof of concept that the proposed method may be used for cable fatigue life calculations and bridge weigh-in-motion studies.
Brownian parametric oscillators
Zerbe, Christine; Jung, Peter; Hänggi, Peter
1994-05-01
We discuss the stochastic dynamics of dissipative, white-noise-driven Floquet oscillators, characterized by a time-periodic stiffness. Thus far, little attention has been paid to these exactly solvable nonstationary systems, although they carry a rich potential for several experimental applications. Here, we calculate and discuss the mean values and variances, as well as the correlation functions and the Floquet spectrum. As one main result, we find for certain parameter values that the fluctuations of the position coordinate are suppressed as compared to the equilibrium value of a harmonic oscillator (parametric squeezing).
Parametric inference for discretely sampled stochastic differential equations
DEFF Research Database (Denmark)
Sørensen, Michael
A review is given of parametric estimation methods for discretely sampled mul- tivariate diffusion processes. The main focus is on estimating functions and asymp- totic results. Maximum likelihood estimation is briefly considered, but the emphasis is on computationally less demanding martingale...
A parametric reconstruction of the deceleration parameter
Energy Technology Data Exchange (ETDEWEB)
Al Mamon, Abdulla [Manipal University, Manipal Centre for Natural Sciences, Manipal (India); Visva-Bharati, Department of Physics, Santiniketan (India); Das, Sudipta [Visva-Bharati, Department of Physics, Santiniketan (India)
2017-07-15
The present work is based on a parametric reconstruction of the deceleration parameter q(z) in a model for the spatially flat FRW universe filled with dark energy and non-relativistic matter. In cosmology, the parametric reconstruction technique deals with an attempt to build up a model by choosing some specific evolution scenario for a cosmological parameter and then estimate the values of the parameters with the help of different observational datasets. In this paper, we have proposed a logarithmic parametrization of q(z) to probe the evolution history of the universe. Using the type Ia supernova, baryon acoustic oscillation and the cosmic microwave background datasets, the constraints on the arbitrary model parameters q{sub 0} and q{sub 1} are obtained (within 1σ and 2σ confidence limits) by χ{sup 2}-minimization technique. We have then reconstructed the deceleration parameter, the total EoS parameter ω{sub tot}, the jerk parameter and have compared the reconstructed results of q(z) with other well-known parametrizations of q(z). We have also shown that two model selection criteria (namely, the Akaike information criterion and Bayesian information criterion) provide a clear indication that our reconstructed model is well consistent with other popular models. (orig.)
Parametric Linear Dynamic Logic
Directory of Open Access Journals (Sweden)
Peter Faymonville
2014-08-01
Full Text Available We introduce Parametric Linear Dynamic Logic (PLDL, which extends Linear Dynamic Logic (LDL by temporal operators equipped with parameters that bound their scope. LDL was proposed as an extension of Linear Temporal Logic (LTL that is able to express all ω-regular specifications while still maintaining many of LTL's desirable properties like an intuitive syntax and a translation into non-deterministic Büchi automata of exponential size. But LDL lacks capabilities to express timing constraints. By adding parameterized operators to LDL, we obtain a logic that is able to express all ω-regular properties and that subsumes parameterized extensions of LTL like Parametric LTL and PROMPT-LTL. Our main technical contribution is a translation of PLDL formulas into non-deterministic Büchi word automata of exponential size via alternating automata. This yields a PSPACE model checking algorithm and a realizability algorithm with doubly-exponential running time. Furthermore, we give tight upper and lower bounds on optimal parameter values for both problems. These results show that PLDL model checking and realizability are not harder than LTL model checking and realizability.
Applications of hybrid time-frequency methods in nonlinear structural dynamics
International Nuclear Information System (INIS)
Politopoulos, I.; Piteau, Ph.; Borsoi, L.; Antunes, J.
2014-01-01
This paper presents a study on methods which may be used to compute the nonlinear response of systems whose linear properties are determined in the frequency or Laplace domain. Typically, this kind of situation may arise in soil-structure and fluid-structure interaction problems. In particular three methods are investigated: (a) the hybrid time-frequency method, (b) the computation of the convolution integral which requires an inverse Fourier or Laplace transform of the system's transfer function, and (c) the identification of an equivalent system defined in the time domain which may be solved with classical time integration methods. These methods are illustrated by their application to some simple, one degree of freedom, non-linear systems and their advantages and drawbacks are highlighted. (authors)
Hardware architecture design of image restoration based on time-frequency domain computation
Wen, Bo; Zhang, Jing; Jiao, Zipeng
2013-10-01
The image restoration algorithms based on time-frequency domain computation is high maturity and applied widely in engineering. To solve the high-speed implementation of these algorithms, the TFDC hardware architecture is proposed. Firstly, the main module is designed, by analyzing the common processing and numerical calculation. Then, to improve the commonality, the iteration control module is planed for iterative algorithms. In addition, to reduce the computational cost and memory requirements, the necessary optimizations are suggested for the time-consuming module, which include two-dimensional FFT/IFFT and the plural calculation. Eventually, the TFDC hardware architecture is adopted for hardware design of real-time image restoration system. The result proves that, the TFDC hardware architecture and its optimizations can be applied to image restoration algorithms based on TFDC, with good algorithm commonality, hardware realizability and high efficiency.
Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application
Directory of Open Access Journals (Sweden)
Molina Gary N Garcia
2003-01-01
Full Text Available Brain-computer interface is a growing field of interest in human-computer interaction with diverse applications ranging from medicine to entertainment. In this paper, we present a system which allows for classification of mental tasks based on a joint time-frequency-space decorrelation, in which mental tasks are measured via electroencephalogram (EEG signals. The efficiency of this approach was evaluated by means of real-time experimentations on two subjects performing three different mental tasks. To do so, a number of protocols for visualization, as well as training with and without feedback, were also developed. Obtained results show that it is possible to obtain good classification of simple mental tasks, in view of command and control, after a relatively small amount of training, with accuracies around 80%, and in real time.
Time-Frequency (Wigner Analysis of Linear and Nonlinear Pulse Propagation in Optical Fibers
Directory of Open Access Journals (Sweden)
José Azaña
2005-06-01
Full Text Available Time-frequency analysis, and, in particular, Wigner analysis, is applied to the study of picosecond pulse propagation through optical fibers in both the linear and nonlinear regimes. The effects of first- and second-order group velocity dispersion (GVD and self-phase modulation (SPM are first analyzed separately. The phenomena resulting from the interplay between GVD and SPM in fibers (e.g., soliton formation or optical wave breaking are also investigated in detail. Wigner analysis is demonstrated to be an extremely powerful tool for investigating pulse propagation dynamics in nonlinear dispersive systems (e.g., optical fibers, providing a clearer and deeper insight into the physical phenomena that determine the behavior of these systems.
Aesthetic appreciation: event-related field and time-frequency analyses.
Munar, Enric; Nadal, Marcos; Castellanos, Nazareth P; Flexas, Albert; Maestú, Fernando; Mirasso, Claudio; Cela-Conde, Camilo J
2011-01-01
Improvements in neuroimaging methods have afforded significant advances in our knowledge of the cognitive and neural foundations of aesthetic appreciation. We used magnetoencephalography (MEG) to register brain activity while participants decided about the beauty of visual stimuli. The data were analyzed with event-related field (ERF) and Time-Frequency (TF) procedures. ERFs revealed no significant differences between brain activity related with stimuli rated as "beautiful" and "not beautiful." TF analysis showed clear differences between both conditions 400 ms after stimulus onset. Oscillatory power was greater for stimuli rated as "beautiful" than those regarded as "not beautiful" in the four frequency bands (theta, alpha, beta, and gamma). These results are interpreted in the frame of synchronization studies.
Fault diagnosis for analog circuits utilizing time-frequency features and improved VVRKFA
He, Wei; He, Yigang; Luo, Qiwu; Zhang, Chaolong
2018-04-01
This paper proposes a novel scheme for analog circuit fault diagnosis utilizing features extracted from the time-frequency representations of signals and an improved vector-valued regularized kernel function approximation (VVRKFA). First, the cross-wavelet transform is employed to yield the energy-phase distribution of the fault signals over the time and frequency domain. Since the distribution is high-dimensional, a supervised dimensionality reduction technique—the bilateral 2D linear discriminant analysis—is applied to build a concise feature set from the distributions. Finally, VVRKFA is utilized to locate the fault. In order to improve the classification performance, the quantum-behaved particle swarm optimization technique is employed to gradually tune the learning parameter of the VVRKFA classifier. The experimental results for the analog circuit faults classification have demonstrated that the proposed diagnosis scheme has an advantage over other approaches.
Time-frequency analysis of the restricted three-body problem: transport and resonance transitions
International Nuclear Information System (INIS)
Vela-Arevalo, Luz V; Marsden, Jerrold E
2004-01-01
A method of time-frequency analysis based on wavelets is applied to the problem of transport between different regions of the solar system, using the model of the circular restricted three-body problem in both the planar and the spatial versions of the problem. The method is based on the extraction of instantaneous frequencies from the wavelet transform of numerical solutions. Time-varying frequencies provide a good diagnostic tool to discern chaotic trajectories from regular ones, and we can identify resonance islands that greatly affect the dynamics. Good accuracy in the calculation of time-varying frequencies allows us to determine resonance trappings of chaotic trajectories and resonance transitions. We show the relation between resonance transitions and transport in different regions of the phase space
Time-Scale and Time-Frequency Analyses of Irregularly Sampled Astronomical Time Series
Directory of Open Access Journals (Sweden)
S. Roques
2005-09-01
Full Text Available We evaluate the quality of spectral restoration in the case of irregular sampled signals in astronomy. We study in details a time-scale method leading to a global wavelet spectrum comparable to the Fourier period, and a time-frequency matching pursuit allowing us to identify the frequencies and to control the error propagation. In both cases, the signals are first resampled with a linear interpolation. Both results are compared with those obtained using Lomb's periodogram and using the weighted waveletZ-transform developed in astronomy for unevenly sampled variable stars observations. These approaches are applied to simulations and to light variations of four variable stars. This leads to the conclusion that the matching pursuit is more efficient for recovering the spectral contents of a pulsating star, even with a preliminary resampling. In particular, the results are almost independent of the quality of the initial irregular sampling.
Combined Approach of PNN and Time-Frequency as the Classifier for Power System Transient Problems
Directory of Open Access Journals (Sweden)
Aslam Pervez Memon
2013-04-01
Full Text Available The transients in power system cause serious disturbances in the reliability, safety and economy of the system. The transient signals possess the nonstationary characteristics in which the frequency as well as varying time information is compulsory for the analysis. Hence, it is vital, first to detect and classify the type of transient fault and then to mitigate them. This article proposes time-frequency and FFNN (Feedforward Neural Network approach for the classification of power system transients problems. In this work it is suggested that all the major categories of transients are simulated, de-noised, and decomposed with DWT (Discrete Wavelet and MRA (Multiresolution Analysis algorithm and then distinctive features are extracted to get optimal vector as input for training of PNN (Probabilistic Neural Network classifier. The simulation results of proposed approach prove their simplicity, accurateness and effectiveness for the automatic detection and classification of PST (Power System Transient types
Time-frequency analysis of railway bridge response in forced vibration
Cantero, Daniel; Ülker-Kaustell, Mahir; Karoumi, Raid
2016-08-01
This paper suggests the use of the Continuous Wavelet Transform in combination with the Modified Littlewood-Paley basis to analyse bridge responses exited by traversing trains. The analysis provides an energy distribution map in the time-frequency domain that offers a better resolution compared to previous published studies. This is demonstrated with recorded responses of the Skidträsk Bridge, a 36 m long composite bridge located in Sweden. It is shown to be particularly useful to understand the evolution of the energy content during a vehicle crossing event. With this information it is possible to distinguish the effect of several of the governing factors involved in the dynamic response including vehicle's speed and axle configuration as well as non-linear behaviour of the structure.
A new time-frequency method for identification and classification of ball bearing faults
Attoui, Issam; Fergani, Nadir; Boutasseta, Nadir; Oudjani, Brahim; Deliou, Adel
2017-06-01
In order to fault diagnosis of ball bearing that is one of the most critical components of rotating machinery, this paper presents a time-frequency procedure incorporating a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a new feature extraction technique based on the selection of the most impulsive frequency bands. In the proposed procedure, firstly, as a pre-processing step, the most impulsive frequency bands are selected at different bearing conditions using a combination between Fast-Fourier-Transform FFT and Short-Frequency Energy SFE algorithms. Secondly, once the most impulsive frequency bands are selected, the measured machinery vibration signals are decomposed into different frequency sub-bands by using discrete Wavelet Packet Decomposition WPD technique to maximize the detection of their frequency contents and subsequently the most useful sub-bands are represented in the time-frequency domain by using Short Time Fourier transform STFT algorithm for knowing exactly what the frequency components presented in those frequency sub-bands are. Once the proposed feature vector is obtained, three feature dimensionality reduction techniques are employed using Linear Discriminant Analysis LDA, a feedback wrapper method and Locality Sensitive Discriminant Analysis LSDA. Lastly, the Adaptive Neuro-Fuzzy Inference System ANFIS algorithm is used for instantaneous identification and classification of bearing faults. In order to evaluate the performances of the proposed method, different testing data set to the trained ANFIS model by using different conditions of healthy and faulty bearings under various load levels, fault severities and rotating speed. The conclusion resulting from this paper is highlighted by experimental results which prove that the proposed method can serve as an intelligent bearing fault diagnosis system.
A soft double regularization approach to parametric blind image deconvolution.
Chen, Li; Yap, Kim-Hui
2005-05-01
This paper proposes a blind image deconvolution scheme based on soft integration of parametric blur structures. Conventional blind image deconvolution methods encounter a difficult dilemma of either imposing stringent and inflexible preconditions on the problem formulation or experiencing poor restoration results due to lack of information. This paper attempts to address this issue by assessing the relevance of parametric blur information, and incorporating the knowledge into the parametric double regularization (PDR) scheme. The PDR method assumes that the actual blur satisfies up to a certain degree of parametric structure, as there are many well-known parametric blurs in practical applications. Further, it can be tailored flexibly to include other blur types if some prior parametric knowledge of the blur is available. A manifold soft parametric modeling technique is proposed to generate the blur manifolds, and estimate the fuzzy blur structure. The PDR scheme involves the development of the meaningful cost function, the estimation of blur support and structure, and the optimization of the cost function. Experimental results show that it is effective in restoring degraded images under different environments.
Directory of Open Access Journals (Sweden)
Yubo Wang
2017-06-01
Full Text Available It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC. In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976 ratio and outperforms existing methods such as short-time Fourier transfrom (STFT, continuous Wavelet transform (CWT and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
Wang, Yubo; Veluvolu, Kalyana C
2017-06-14
It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
of specifying an unsuitable functional form and thus, model misspecification and biased parameter estimates. Given these problems of the DEA and the SFA, Fan, Li and Weersink (1996) proposed a semi-parametric stochastic frontier model that estimates the production function (frontier) by non......), Kumbhakar et al. (2007), and Henningsen and Kumbhakar (2009). The aim of this paper and its main contribution to the existing literature is the estimation semi-parametric stochastic frontier models using a different non-parametric estimation technique: spline regression (Ma et al. 2011). We apply...... efficiency of Polish dairy farms contributes to the insight into this dynamic process. Furthermore, we compare and evaluate the results of this spline-based semi-parametric stochastic frontier model with results of other semi-parametric stochastic frontier models and of traditional parametric stochastic...
基于FrFT-MUSIC的空时频算法%Space-time-frequency Algorithm Based on FrFT-MUSIC
Institute of Scientific and Technical Information of China (English)
张声杰; 刘梅
2011-01-01
针对传统时频分析方法难以对星载分布式合成孔径雷达(SAR)系统中地面目标速度进行准确估计的问题,提出了分数阶傅里叶变换(FrFT)-多重信号分类(MUSIC)空时频方法.利用FrFT获得信号向量并构造空时频分布矩阵；应用该分布矩阵替代传统MUSIC算法中的协方差矩阵,从而求得FrFT- MUSIC空时频谱,通过对谱函数进行搜索估计目标速度.仿真实验表明,该方法的目标速度估计精度高,抗噪声能力强.%The fractional Fourier transform (FrFT)-multipIe signal classification (MUSIC) space-time-frequency algorithm is proposed to solve the problem that it is difficult for the traditional time-frequency analysis method to accurately estimate the ground targets' azimuth speed which is coupled with spaceborne distributed synthetic aperture radar" (SAR). The signal vector is obtained and the space-time-frequency distribution matrix is formed by FrFT. Then, this distribution matrix is used instead of the traditional MUSIC covariance matrix to construct FrFT- MUSIC spectral function. Target speed is estimated by searching. Simulation results show that this algorithm has a high accuracy of parameter estimation and strong resistance to noise.
Nanoscale electromechanical parametric amplifier
Aleman, Benjamin Jose; Zettl, Alexander
2016-09-20
This disclosure provides systems, methods, and apparatus related to a parametric amplifier. In one aspect, a device includes an electron source electrode, a counter electrode, and a pumping electrode. The electron source electrode may include a conductive base and a flexible conductor. The flexible conductor may have a first end and a second end, with the second end of the flexible conductor being coupled to the conductive base. A cross-sectional dimension of the flexible conductor may be less than about 100 nanometers. The counter electrode may be disposed proximate the first end of the flexible conductor and spaced a first distance from the first end of the flexible conductor. The pumping electrode may be disposed proximate a length of the flexible conductor and spaced a second distance from the flexible conductor.
Parametric Room Acoustic Workflows
DEFF Research Database (Denmark)
Parigi, Dario; Svidt, Kjeld; Molin, Erik
2017-01-01
The paper investigates and assesses different room acoustics software and the opportunities they offer to engage in parametric acoustics workflow and to influence architectural designs. The first step consists in the testing and benchmarking of different tools on the basis of accuracy, speed...... and interoperability with Grasshopper 3d. The focus will be placed to the benchmarking of three different acoustic analysis tools based on raytracing. To compare the accuracy and speed of the acoustic evaluation across different tools, a homogeneous set of acoustic parameters is chosen. The room acoustics parameters...... included in the set are reverberation time (EDT, RT30), clarity (C50), loudness (G), and definition (D50). Scenarios are discussed for determining at different design stages the most suitable acoustic tool. Those scenarios are characterized, by the use of less accurate but fast evaluation tools to be used...
DEFF Research Database (Denmark)
Herzog, Dennis
adapt the primitives to the actual appearance of the tracked motion, since the appearance of actions depends on the object locations. From the recognition perspective, it is necessary to recognize a performed action, but the understanding requires also the recovery of the action parameters, which can......The thesis aims at the learning of action primitives and their application on the perceptive side (tracking/recognition) and the generative side (synthesizing for robot control). A motivation is to use a unified primitive representation applicable on both sides. The thesis considers arm actions...... with an investigation of PHMM training methods and structures to utilize the PHMM as a unified representation of parametric primitives, which is adequate for recognition and for synthesis. This is evaluated on a large motion data set. Main contributions of the thesis are the development and evaluation of approaches...
Parametric Cost Models for Space Telescopes
Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtney
2010-01-01
Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.
Parametric cost models for space telescopes
Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtnay
2017-11-01
Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.
System identification through nonstationary data using Time-Frequency Blind Source Separation
Guo, Yanlin; Kareem, Ahsan
2016-06-01
Classical output-only system identification (SI) methods are based on the assumption of stationarity of the system response. However, measured response of buildings and bridges is usually non-stationary due to strong winds (e.g. typhoon, and thunder storm etc.), earthquakes and time-varying vehicle motions. Accordingly, the response data may have time-varying frequency contents and/or overlapping of modal frequencies due to non-stationary colored excitation. This renders traditional methods problematic for modal separation and identification. To address these challenges, a new SI technique based on Time-Frequency Blind Source Separation (TFBSS) is proposed. By selectively utilizing "effective" information in local regions of the time-frequency plane, where only one mode contributes to energy, the proposed technique can successfully identify mode shapes and recover modal responses from the non-stationary response where the traditional SI methods often encounter difficulties. This technique can also handle response with closely spaced modes which is a well-known challenge for the identification of large-scale structures. Based on the separated modal responses, frequency and damping can be easily identified using SI methods based on a single degree of freedom (SDOF) system. In addition to the exclusive advantage of handling non-stationary data and closely spaced modes, the proposed technique also benefits from the absence of the end effects and low sensitivity to noise in modal separation. The efficacy of the proposed technique is demonstrated using several simulation based studies, and compared to the popular Second-Order Blind Identification (SOBI) scheme. It is also noted that even some non-stationary response data can be analyzed by the stationary method SOBI. This paper also delineates non-stationary cases where SOBI and the proposed scheme perform comparably and highlights cases where the proposed approach is more advantageous. Finally, the performance of the
Qidwai, Uvais; Costa, Antonio H.; Chen, C. H.
2000-05-01
The ultrasonic wave, generated by a piezoelectric transducer coupled to the test specimen, propagates through the material and part of its energy is reflected when it encounters an non-homogeneity or discontinuity in its path, while the remainder is reflected by the back surface of the test specimen. Defect echo signals are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic wave, and are corrupted by additive noise. This leads to difficulties in comparing and analyzing signals, particularly in automated defect identification systems employing different transducers. Further, the multi-component nature of material defects can add to the complexity of the defect identification criteria. With many one-dimensional (1-D) approaches, the multi-component defects can not be detected. Another drawback is that these techniques are not very robust for sharp ultrasonic peaks especially in a very hazardous environment. This paper proposes a technique based on the time-frequency representations (TFRs) of the real defect signals corresponding to artificially produced defects of various geometries in metals. Cohen's class (quadratic) TFRs with Gaussian kernels are then used to represent the signals in the time-frequency (TF) plane. Once the TFR is obtained, various image processing morphological techniques are applied to the TFR (e.g. region of interest masking, edge detection, and profile separation). Based on the results of these operations, a binary image is produced which, in turn, leads to a novel set of features. Using these new features, defects have not only been detected but also classified as flat-cut, angular-cut, and circular-drills. Moreover, with some modifications of the threshold levels of the TFR kernel design, our technique can be used in relatively hostile environments with SNRs as low as 0 dB. Another important characteristic of our approach is the detection of multiple defects. This consists of detection of
Using non-parametric methods in econometric production analysis
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb...... results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used...
Multichannel interictal spike activity detection using time-frequency entropy measure.
Thanaraj, Palani; Parvathavarthini, B
2017-06-01
Localization of interictal spikes is an important clinical step in the pre-surgical assessment of pharmacoresistant epileptic patients. The manual selection of interictal spike periods is cumbersome and involves a considerable amount of analysis workload for the physician. The primary focus of this paper is to automate the detection of interictal spikes for clinical applications in epilepsy localization. The epilepsy localization procedure involves detection of spikes in a multichannel EEG epoch. Therefore, a multichannel Time-Frequency (T-F) entropy measure is proposed to extract features related to the interictal spike activity. Least squares support vector machine is used to train the proposed feature to classify the EEG epochs as either normal or interictal spike period. The proposed T-F entropy measure, when validated with epilepsy dataset of 15 patients, shows an interictal spike classification accuracy of 91.20%, sensitivity of 100% and specificity of 84.23%. Moreover, the area under the curve of Receiver Operating Characteristics plot of 0.9339 shows the superior classification performance of the proposed T-F entropy measure. The results of this paper show a good spike detection accuracy without any prior information about the spike morphology.
EEG biometric identification: a thorough exploration of the time-frequency domain
DelPozo-Banos, Marcos; Travieso, Carlos M.; Weidemann, Christoph T.; Alonso, Jesús B.
2015-10-01
Objective. Although interest in using electroencephalogram (EEG) activity for subject identification has grown in recent years, the state of the art still lacks a comprehensive exploration of the discriminant information within it. This work aims to fill this gap, and in particular, it focuses on the time-frequency representation of the EEG. Approach. We executed qualitative and quantitative analyses of six publicly available data sets following a sequential experimentation approach. This approach was divided in three blocks analysing the configuration of the power spectrum density, the representation of the data and the properties of the discriminant information. A total of ten experiments were applied. Main results. Results show that EEG information below 40 Hz is unique enough to discriminate across subjects (a maximum of 100 subjects were evaluated here), regardless of the recorded cognitive task or the sensor location. Moreover, the discriminative power of rhythms follows a W-like shape between 1 and 40 Hz, with the central peak located at the posterior rhythm (around 10 Hz). This information is maximized with segments of around 2 s, and it proved to be moderately constant across montages and time. Significance. Therefore, we characterize how EEG activity differs across individuals and detail the optimal conditions to detect subject-specific information. This work helps to clarify the results of previous studies and to solve some unanswered questions. Ultimately, it will serve as guide for the design of future biometric systems.
Mostafapour, A; Davoodi, S; Ghareaghaji, M
2014-12-01
In this study, the theories of wavelet transform and cross-time frequency spectrum (CTFS) are used to locate AE source with frequency-varying wave velocity in plate-type structures. A rectangular array of four sensors is installed on the plate. When an impact is generated by an artificial AE source such as Hsu-Nielsen method of pencil lead breaking (PLB) at any position of the plate, the AE signals will be detected by four sensors at different times. By wavelet packet decomposition, a packet of signals with frequency range of 0.125-0.25MHz is selected. The CTFS is calculated by the short-time Fourier transform of the cross-correlation between considered packets captured by AE sensors. The time delay is calculated when the CTFS reaches the maximum value and the corresponding frequency is extracted per this maximum value. The resulting frequency is used to calculate the group velocity of wave velocity in combination with dispersive curve. The resulted locating error shows the high precision of proposed algorithm. Copyright © 2014 Elsevier B.V. All rights reserved.
Efficient Offline Waveform Design Using Quincunx/Hexagonal Time-Frequency Lattices
Directory of Open Access Journals (Sweden)
Raouia Ayadi
2017-01-01
Full Text Available Conventional orthogonal frequency division multiplexing (OFDM may turn to be inappropriate for future wireless cellular systems services, because of extreme natural and artificial impairments they are expected to generate. Natural impairments result from higher Doppler and delay spreads, while artificial impairments result from multisource transmissions and synchronization relaxation for closed-loop signaling overhead reduction. These severe impairments induce a dramatic loss in orthogonality between subcarriers and OFDM symbols and lead to a strong increase in intercarrier interference (ICI and intersymbol interference (ISI. To fight against these impairments, we propose here an optimization of the transmit/receive waveforms for filter-bank multicarrier (FBMC systems, with hexagonal time-frequency (TF lattices, operating over severe doubly dispersive channels. For this, we exploit the Ping-pong Optimized Pulse Shaping (POPS paradigm, recently applied to rectangular TF lattices, to design waveforms maximizing the signal-to-interference-plus-noise ratio (SINR for hexagonal TF lattices. We show that FBMC, with hexagonal lattices, offers a strong improvement in SINR with respect to conventional OFDM and an improvement of around 1 dB with respect to POPS-FBMC, with rectangular lattices. Furthermore, we show that hexagonal POPS-FBMC brings more robustness to frequency synchronization errors and offers a 10 dB reduction in out-of-band (OOB emissions, with respect to rectangular POPS-FBMC.
Cardiorespiratory dynamic response to mental stress: a multivariate time-frequency analysis.
Widjaja, Devy; Orini, Michele; Vlemincx, Elke; Van Huffel, Sabine
2013-01-01
Mental stress is a growing problem in our society. In order to deal with this, it is important to understand the underlying stress mechanisms. In this study, we aim to determine how the cardiorespiratory interactions are affected by mental arithmetic stress and attention. We conduct cross time-frequency (TF) analyses to assess the cardiorespiratory coupling. In addition, we introduce partial TF spectra to separate variations in the RR interval series that are linearly related to respiration from RR interval variations (RRV) that are not related to respiration. The performance of partial spectra is evaluated in two simulation studies. Time-varying parameters, such as instantaneous powers and frequencies, are derived from the computed spectra. Statistical analysis is carried out continuously in time to evaluate the dynamic response to mental stress and attention. The results show an increased heart and respiratory rate during stress and attention, compared to a resting condition. Also a fast reduction in vagal activity is noted. The partial TF analysis reveals a faster reduction of RRV power related to (3 s) than unrelated to (30 s) respiration, demonstrating that the autonomic response to mental stress is driven by mechanisms characterized by different temporal scales.
Wavelet time-frequency analysis of accelerating and decelerating flows in a tube bank
International Nuclear Information System (INIS)
Indrusiak, M.L.S.; Goulart, J.V.; Olinto, C.R.; Moeller, S.V.
2005-01-01
In the present work, the steady approximation for accelerating and decelerating flows through tube banks is discussed. With this purpose, the experimental study of velocity and pressure fluctuations of transient turbulent cross-flow in a tube bank with square arrangement and a pitch-to-diameter ratio of 1.26 is performed. The Reynolds number at steady-state flow, computed with the tube diameter and the flow velocity in the narrow gap between the tubes, is 8 x 10 4 . Air is the working fluid. The accelerating and decelerating transients are obtained by means of start and stop of the centrifugal blower. Wavelet and wavelet packet multiresolution analysis were applied to decompose the signal in frequency intervals, using Daubechies 20 wavelet and scale functions, thus allowing the analysis of phenomena in a time-frequency domain. The continuous wavelet transform was also applied, using the Morlet function. The signals in the steady state, which presented a bistable behavior, were separated in two modes and analyzed with usual statistic tools. The results were compared with the steady-state assumption, demonstrating the ability of wavelets for analyzing time varying signals
SEMIPARAMETRIC VERSUS PARAMETRIC CLASSIFICATION MODELS - AN APPLICATION TO DIRECT MARKETING
BULT, [No Value
In this paper we are concerned with estimation of a classification model using semiparametric and parametric methods. Benefits and limitations of semiparametric models in general, and of Manski's maximum score method in particular, are discussed. The maximum score method yields consistent estimates
Parametric Mass Reliability Study
Holt, James P.
2014-01-01
The International Space Station (ISS) systems are designed based upon having redundant systems with replaceable orbital replacement units (ORUs). These ORUs are designed to be swapped out fairly quickly, but some are very large, and some are made up of many components. When an ORU fails, it is replaced on orbit with a spare; the failed unit is sometimes returned to Earth to be serviced and re-launched. Such a system is not feasible for a 500+ day long-duration mission beyond low Earth orbit. The components that make up these ORUs have mixed reliabilities. Components that make up the most mass-such as computer housings, pump casings, and the silicon board of PCBs-typically are the most reliable. Meanwhile components that tend to fail the earliest-such as seals or gaskets-typically have a small mass. To better understand the problem, my project is to create a parametric model that relates both the mass of ORUs to reliability, as well as the mass of ORU subcomponents to reliability.
Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming
2018-06-01
With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.
Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli.
Directory of Open Access Journals (Sweden)
Thibaud Necciari
Full Text Available Many audio applications perform perception-based time-frequency (TF analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1 with standard model parameters (i.e. without efferents, (2 with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using
Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli.
Necciari, Thibaud; Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard
2016-01-01
Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally
Directory of Open Access Journals (Sweden)
Koivistoinen Teemu
2007-01-01
Full Text Available As we know, singular value decomposition (SVD is designed for computing singular values (SVs of a matrix. Then, if it is used for finding SVs of an -by-1 or 1-by- array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD.'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal. This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs for ballistocardiogram (BCG data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.
Directory of Open Access Journals (Sweden)
Alpo Värri
2007-01-01
Full Text Available As we know, singular value decomposition (SVD is designed for computing singular values (SVs of a matrix. Then, if it is used for finding SVs of an m-by-1 or 1-by-m array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ‘‘time-frequency moments singular value decomposition (TFM-SVD.’’ In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal. This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs for ballistocardiogram (BCG data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.
Akhbardeh, Alireza; Junnila, Sakari; Koivuluoma, Mikko; Koivistoinen, Teemu; Värri, Alpo
2006-12-01
As we know, singular value decomposition (SVD) is designed for computing singular values (SVs) of a matrix. Then, if it is used for finding SVs of an [InlineEquation not available: see fulltext.]-by-1 or 1-by- [InlineEquation not available: see fulltext.] array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD).'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal). This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs) for ballistocardiogram (BCG) data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.
Perceptual Coding of Audio Signals Using Adaptive Time-Frequency Transform
Directory of Open Access Journals (Sweden)
Umapathy Karthikeyan
2007-01-01
Full Text Available Wide band digital audio signals have a very high data-rate associated with them due to their complex nature and demand for high-quality reproduction. Although recent technological advancements have significantly reduced the cost of bandwidth and miniaturized storage facilities, the rapid increase in the volume of digital audio content constantly compels the need for better compression algorithms. Over the years various perceptually lossless compression techniques have been introduced, and transform-based compression techniques have made a significant impact in recent years. In this paper, we propose one such transform-based compression technique, where the joint time-frequency (TF properties of the nonstationary nature of the audio signals were exploited in creating a compact energy representation of the signal in fewer coefficients. The decomposition coefficients were processed and perceptually filtered to retain only the relevant coefficients. Perceptual filtering (psychoacoustics was applied in a novel way by analyzing and performing TF specific psychoacoustics experiments. An added advantage of the proposed technique is that, due to its signal adaptive nature, it does not need predetermined segmentation of audio signals for processing. Eight stereo audio signal samples of different varieties were used in the study. Subjective (mean opinion score—MOS listening tests were performed and the subjective difference grades (SDG were used to compare the performance of the proposed coder with MP3, AAC, and HE-AAC encoders. Compression ratios in the range of 8 to 40 were achieved by the proposed technique with subjective difference grades (SDG ranging from –0.53 to –2.27.
Perceptual Coding of Audio Signals Using Adaptive Time-Frequency Transform
Directory of Open Access Journals (Sweden)
Karthikeyan Umapathy
2007-08-01
Full Text Available Wide band digital audio signals have a very high data-rate associated with them due to their complex nature and demand for high-quality reproduction. Although recent technological advancements have significantly reduced the cost of bandwidth and miniaturized storage facilities, the rapid increase in the volume of digital audio content constantly compels the need for better compression algorithms. Over the years various perceptually lossless compression techniques have been introduced, and transform-based compression techniques have made a significant impact in recent years. In this paper, we propose one such transform-based compression technique, where the joint time-frequency (TF properties of the nonstationary nature of the audio signals were exploited in creating a compact energy representation of the signal in fewer coefficients. The decomposition coefficients were processed and perceptually filtered to retain only the relevant coefficients. Perceptual filtering (psychoacoustics was applied in a novel way by analyzing and performing TF specific psychoacoustics experiments. An added advantage of the proposed technique is that, due to its signal adaptive nature, it does not need predetermined segmentation of audio signals for processing. Eight stereo audio signal samples of different varieties were used in the study. Subjective (mean opinion scoreÃ¢Â€Â”MOS listening tests were performed and the subjective difference grades (SDG were used to compare the performance of the proposed coder with MP3, AAC, and HE-AAC encoders. Compression ratios in the range of 8 to 40 were achieved by the proposed technique with subjective difference grades (SDG ranging from Ã¢Â€Â“0.53 to Ã¢Â€Â“2.27.
Processing grounded-wire TEM signal in time-frequency-pseudo-seismic domain: A new paradigm
Khan, M. Y.; Xue, G. Q.; Chen, W.; Huasen, Z.
2017-12-01
Grounded-wire TEM has received great attention in mineral, hydrocarbon and hydrogeological investigations for the last several years. Conventionally, TEM soundings have been presented as apparent resistivity curves as function of time. With development of sophisticated computational algorithms, it became possible to extract more realistic geoelectric information by applying inversion programs to 1-D & 3-D problems. Here, we analyze grounded-wire TEM data by carrying out analysis in time, frequency and pseudo-seismic domain supported by borehole information. At first, H, K, A & Q type geoelectric models are processed using a proven inversion program (1-D Occam inversion). Second, time-to-frequency transformation is conducted from TEM ρa(t) curves to magneto telluric MT ρa(f) curves for the same models based on all-time apparent resistivity curves. Third, 1-D Bostick's algorithm was applied to the transformed resistivity. Finally, EM diffusion field is transformed into propagating wave field obeying the standard wave equation using wavelet transformation technique and constructed pseudo-seismic section. The transformed seismic-like wave indicates that some reflection and refraction phenomena appear when the EM wave field interacts with geoelectric interface at different depth intervals due to contrast in resistivity. The resolution of the transformed TEM data is significantly improved in comparison to apparent resistivity plots. A case study illustrates the successful hydrogeophysical application of proposed approach in recovering water-filled mined-out area in a coal field located in Ye county, Henan province, China. The results support the introduction of pseudo-seismic imaging technology in short-offset version of TEM which can also be an useful aid if integrated with seismic reflection technique to explore possibilities for high resolution EM imaging in future.
Comparison of parametric and bootstrap method in bioequivalence test.
Ahn, Byung-Jin; Yim, Dong-Seok
2009-10-01
The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.
Directory of Open Access Journals (Sweden)
Hui Chen
2018-06-01
Full Text Available According to the fact that high frequency will be abnormally attenuated when seismic signals travel across reservoirs, a new method, which is named high-precision time-frequency entropy based on synchrosqueezing generalized S-transform, is proposed for hydrocarbon reservoir detection in this paper. First, the proposed method obtains the time-frequency spectra by synchrosqueezing generalized S-transform (SSGST, which are concentrated around the real instantaneous frequency of the signals. Then, considering the characteristics and effects of noises, we give a frequency constraint condition to calculate the entropy based on time-frequency spectra. The synthetic example verifies that the entropy will be abnormally high when seismic signals have an abnormal attenuation. Besides, comparing with the GST time-frequency entropy and the original SSGST time-frequency entropy in field data, the results of the proposed method show higher precision. Moreover, the proposed method can not only accurately detect and locate hydrocarbon reservoirs, but also effectively suppress the impact of random noises.
Planar Parametrization in Isogeometric Analysis
DEFF Research Database (Denmark)
Gravesen, Jens; Evgrafov, Anton; Nguyen, Dang-Manh
2012-01-01
Before isogeometric analysis can be applied to solving a partial differential equation posed over some physical domain, one needs to construct a valid parametrization of the geometry. The accuracy of the analysis is affected by the quality of the parametrization. The challenge of computing...... and maintaining a valid geometry parametrization is particularly relevant in applications of isogemetric analysis to shape optimization, where the geometry varies from one optimization iteration to another. We propose a general framework for handling the geometry parametrization in isogeometric analysis and shape...... are suitable for our framework. The non-linear methods we consider are based on solving a constrained optimization problem numerically, and are divided into two classes, geometry-oriented methods and analysis-oriented methods. Their performance is illustrated through a few numerical examples....
Parametric FEM for geometric biomembranes
Bonito, Andrea; Nochetto, Ricardo H.; Sebastian Pauletti, M.
2010-05-01
We consider geometric biomembranes governed by an L2-gradient flow for bending energy subject to area and volume constraints (Helfrich model). We give a concise derivation of a novel vector formulation, based on shape differential calculus, and corresponding discretization via parametric FEM using quadratic isoparametric elements and a semi-implicit Euler method. We document the performance of the new parametric FEM with a number of simulations leading to dumbbell, red blood cell and toroidal equilibrium shapes while exhibiting large deformations.
Space-time-frequency analysis of rainfall, runoff and temperature in ...
African Journals Online (AJOL)
drinie
2002-07-03
Jul 3, 2002 ... from two upstream stations were used to develop a procedure for estimating runoff from the annual .... parts: the basin network under tidal influence and the continental ... Using the power transformation method (Chander.
Parametric Portfolio Policies with Common Volatility Dynamics
DEFF Research Database (Denmark)
Ergemen, Yunus Emre; Taamouti, Abderrahim
A parametric portfolio policy function is considered that incorporates common stock volatility dynamics to optimally determine portfolio weights. Reducing dimension of the traditional portfolio selection problem significantly, only a number of policy parameters corresponding to first- and second......-order characteristics are estimated based on a standard method-of-moments technique. The method, allowing for the calculation of portfolio weight and return statistics, is illustrated with an empirical application to 30 U.S. industries to study the economic activity before and after the recent financial crisis....
Incorporating parametric uncertainty into population viability analysis models
McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.
2011-01-01
Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.
International Nuclear Information System (INIS)
Baker, C.
1994-10-01
The Department of Energy's (DOE) Hanford site near Richland, Washington is being cleaned up after 50 years of nuclear materials production. One of the most serious problems at the site is the waste stored in single-shell underground storage tanks. There are 149 of these tanks containing the spent fuel residue remaining after the fuel is dissolved in acid and the desired materials (primarily plutonium and uranium) are separated out. The tanks are upright cylinders 75 ft. in diameter with domed tops. They are made of reinforced concrete, have steel liners, and each tank is buried under 7--12 ft. of overburden. The tanks are up to 40-ft. high, and have capacities of 500,000, 750,000, or 1,000,000 gallons of waste. As many as one-third of these tanks are known or suspected to leak. The waste form contained in the tanks varies in consistency from liquid supernatant to peanut-butter-like gels and sludges to hard salt cake (perhaps as hard as low-grade concrete). The current waste retrieval plan is to insert a large long-reach manipulator through a hole cut in the top of the tank, and use a variety of end-effectors to mobilize the waste and remove it from the tank. PNL has, with the assistance of Deneb robotics employees, developed a means of using the IGRIP code to perform parametric design of mechanical systems. This method requires no modifications to the IGRIP code, and all design data are stored in the IGRIP workcell. The method is presented in the context of development of a passive articulated mechanism that is used to deliver down-arm services to a gantry robot. The method is completely general, however, and could be used to design a fully articulated manipulator. Briefly, the method involves using IGCALC expressions to control manipulator joint angles, and IGCALC variables to allow user control of link lengths and offsets. This paper presents the method in detail, with examples drawn from PNL's experience with the gantry robot service-providing mechanism
Examples in parametric inference with R
Dixit, Ulhas Jayram
2016-01-01
This book discusses examples in parametric inference with R. Combining basic theory with modern approaches, it presents the latest developments and trends in statistical inference for students who do not have an advanced mathematical and statistical background. The topics discussed in the book are fundamental and common to many fields of statistical inference and thus serve as a point of departure for in-depth study. The book is divided into eight chapters: Chapter 1 provides an overview of topics on sufficiency and completeness, while Chapter 2 briefly discusses unbiased estimation. Chapter 3 focuses on the study of moments and maximum likelihood estimators, and Chapter 4 presents bounds for the variance. In Chapter 5, topics on consistent estimator are discussed. Chapter 6 discusses Bayes, while Chapter 7 studies some more powerful tests. Lastly, Chapter 8 examines unbiased and other tests. Senior undergraduate and graduate students in statistics and mathematics, and those who have taken an introductory cou...
International Nuclear Information System (INIS)
Seleghim, Paulo
1996-01-01
This work concerns the development of a methodology which objective is to characterize and diagnose two-phase flow regime transitions. The approach is based on the fundamental assumption that a transition flow is less stationary than a flow with an established regime. In a first time, the efforts focused on: 1) the design and construction of an experimental loop, allowing to reproduce the main horizontal two-phase flow patterns, in a stable and controlled way, 2) the design and construction of an electrical impedance probe, providing an imaged information of the spatial phase distribution in the pipe, the systematic study of the joint time-frequency and time-scale analysis methods, which permitted to define an adequate parameter quantifying the un-stationary degree. In a second time, in order to verify the fundamental assumption, a series of experiments were conducted, which objective was to demonstrate the correlation between un-stationary and regime transition. The un-stationary degree was quantified by calculating the Gabor's transform time-frequency covariance of the impedance probe signals. Furthermore, the phenomenology of each transition was characterized by the joint moments and entropy. The results clearly show that the regime transitions are correlated with local-time frequency covariance peaks, which demonstrates that these regime transitions are characterized by a loss of stationarity. Consequently, the time-frequency covariance constitutes an objective two-phase flow regime transition indicator. (author) [fr
Directory of Open Access Journals (Sweden)
Paulo Antonio Delgado-Arredondo
2015-01-01
Full Text Available Induction motors are critical components for most industries and the condition monitoring has become necessary to detect faults. There are several techniques for fault diagnosis of induction motors and analyzing the startup transient vibration signals is not as widely used as other techniques like motor current signature analysis. Vibration analysis gives a fault diagnosis focused on the location of spectral components associated with faults. Therefore, this paper presents a comparative study of different time-frequency analysis methodologies that can be used for detecting faults in induction motors analyzing vibration signals during the startup transient. The studied methodologies are the time-frequency distribution of Gabor (TFDG, the time-frequency Morlet scalogram (TFMS, multiple signal classification (MUSIC, and fast Fourier transform (FFT. The analyzed vibration signals are one broken rotor bar, two broken bars, unbalance, and bearing defects. The obtained results have shown the feasibility of detecting faults in induction motors using the time-frequency spectral analysis applied to vibration signals, and the proposed methodology is applicable when it does not have current signals and only has vibration signals. Also, the methodology has applications in motors that are not fed directly to the supply line, in such cases the analysis of current signals is not recommended due to poor current signal quality.
STATCAT, Statistical Analysis of Parametric and Non-Parametric Data
International Nuclear Information System (INIS)
David, Hugh
1990-01-01
1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required
Ionospheric modification and parametric instabilities
International Nuclear Information System (INIS)
Fejer, J.A.
1979-01-01
Thresholds and linear growth rates for stimulated Brillouin and Raman scattering and for the parametric decay instability are derived by using arguments of energy transfer. For this purpose an expression for the ponderomotive force is derived. Conditions under which the partial pressure force due to differential dissipation exceeds the ponderomotive force are also discussed. Stimulated Brillouin and Raman scattering are weakly excited by existing incoherent backscatter radars. The parametric decay instability is strongly excited in ionospheric heating experiments. Saturation theories of the parametric decay instability are therefore described. After a brief discussion of the purely growing instability the effect of using several pumps is discussed as well as the effects of inhomogenicity. Turning to detailed theories of ionospheric heating, artificial spread F is discussed in terms of a purely growing instability where the nonlinearity is due to dissipation. Field-aligned short-scale striations are explained in terms of dissipation of the parametrically excited Langmuir waves (plasma oscillations): they might be further amplified by an explosive instability (except the magnetic equator). Broadband absorption is probably responsible for the 'overshoot' effect: the initially observed level of parametrically excited Langmuir waves is much higher than the steady state level
Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.
2011-03-01
Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.
Watts, Adreanna T M; Tootell, Anne V; Fix, Spencer T; Aviyente, Selin; Bernat, Edward M
2018-04-29
The neurophysiological mechanisms involved in the evaluation of performance feedback have been widely studied in the ERP literature over the past twenty years, but understanding has been limited by the use of traditional time-domain amplitude analytic approaches. Gambling outcome valence has been identified as an important factor modulating event-related potential (ERP) components, most notably the feedback negativity (FN). Recent work employing time-frequency analysis has shown that processes indexed by the FN are confounded in the time-domain and can be better represented as separable feedback-related processes in the theta (3-7 Hz) and delta (0-3 Hz) frequency bands. In addition to time-frequency amplitude analysis, phase synchrony measures have begun to further our understanding of performance evaluation by revealing how feedback information is processed within and between various brain regions. The current study aimed to provide an integrative assessment of time-frequency amplitude, inter-trial phase synchrony, and inter-channel phase synchrony changes following monetary feedback in a gambling task. Results revealed that time-frequency amplitude activity explained separable loss and gain processes confounded in the time-domain. Furthermore, phase synchrony measures explained unique variance above and beyond amplitude measures and demonstrated enhanced functional integration between medial prefrontal and bilateral frontal, motor, and occipital regions for loss relative to gain feedback. These findings demonstrate the utility of assessing time-frequency amplitude, inter-trial phase synchrony, and inter-channel phase synchrony together to better elucidate the neurophysiology of feedback processing. Copyright © 2017. Published by Elsevier B.V.
Time-Frequency Analysis Using Warped-Based High-Order Phase Modeling
Directory of Open Access Journals (Sweden)
Ioana Cornel
2005-01-01
Full Text Available The high-order ambiguity function (HAF was introduced for the estimation of polynomial-phase signals (PPS embedded in noise. Since the HAF is a nonlinear operator, it suffers from noise-masking effects and from the appearance of undesired cross-terms when multicomponents PPS are analyzed. In order to improve the performances of the HAF, the multi-lag HAF concept was proposed. Based on this approach, several advanced methods (e.g., product high-order ambiguity function (PHAF have been recently proposed. Nevertheless, performances of these new methods are affected by the error propagation effect which drastically limits the order of the polynomial approximation. This phenomenon acts especially when a high-order polynomial modeling is needed: representation of the digital modulation signals or the acoustic transient signals. This effect is caused by the technique used for polynomial order reduction, common for existing approaches: signal multiplication with the complex conjugated exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We will prove that this method reduces considerably the effect of error propagation. Namely, with this order reduction method, the estimation error at a given order will depend only on the performances of the estimation method.
Parametric Thinking in Urban Design
DEFF Research Database (Denmark)
Steinø, Nicolai
2010-01-01
The paper states that most applications of parametric mod- elling to architecture and urban design fall into one of two strands of either form for form’s sake, or the negotiation of environmental con- cerns, while approaches which allow scenarios to be easily tested and modified without the appli...... of the paper. The pros and cons of this simple approach is discussed, and the paper con- cludes, that while it does not represent a suitable solution in all cases, it fills a gap among the existing approaches to parametric urban de- sign.......The paper states that most applications of parametric mod- elling to architecture and urban design fall into one of two strands of either form for form’s sake, or the negotiation of environmental con- cerns, while approaches which allow scenarios to be easily tested and modified without...
Heart Sound Localization and Reduction in Tracheal Sounds by Gabor Time-Frequency Masking
SAATCI, Esra; Akan, Aydın
2018-01-01
Background and aim: Respiratorysounds, i.e. tracheal and lung sounds, have been of great interest due to theirdiagnostic values as well as the potential of their use in the estimation ofthe respiratory dynamics (mainly airflow). Thus the aim of the study is topresent a new method to filter the heart sound interference from the trachealsounds. Materials and methods: Trachealsounds and airflow signals were collected by using an accelerometer from 10 healthysubjects. Tracheal sounds were then pr...
Optimal Design of Experiments for Parametric Identification of Civil Engineering Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning
Optimal Systems of experiments for parametric identification of civil engineering structures is investigated. Design of experiments for parametric identification of dynamic systems is usually done by minimizing a scalar measure, e.g the determinant, the trace ect., of an estimated parameter...
Entanglement in a parametric converter
Energy Technology Data Exchange (ETDEWEB)
Lee, Su-Yong; Qamar, Shahid; Lee, Hai-Woong; Zubairy, M Suhail [Center for Quantum Physics, COMSATS Institute of Information Technology, Islamabad (Pakistan)], E-mail: shahid_qamar@pieas.edu.pk, E-mail: zubairy@physics.tamu.edu
2008-07-28
In this paper, we consider a parametric converter as a source of entangled radiation. We examine recently derived conditions (Hillery and Zubairy 2006 Phys. Rev. Lett. 96 050503, Duan et al 2000 Phys. Rev. Lett. 84 2722) for determining when the two output modes in a parametric converter are entangled. We show that for different initial field states, the two criteria give different conditions that ensure that the output states are entangled. We also present an input-output calculation for the entanglement of the output field.
Non-Parametric Analysis of Rating Transition and Default Data
DEFF Research Database (Denmark)
Fledelius, Peter; Lando, David; Perch Nielsen, Jens
2004-01-01
We demonstrate the use of non-parametric intensity estimation - including construction of pointwise confidence sets - for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move b...
Parametrization of contrails in a comprehensive climate model
Energy Technology Data Exchange (ETDEWEB)
Ponater, M; Brinkop, S; Sausen, R; Schumann, U [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere
1998-12-31
A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.
Parametrization of contrails in a comprehensive climate model
Energy Technology Data Exchange (ETDEWEB)
Ponater, M.; Brinkop, S.; Sausen, R.; Schumann, U. [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere
1997-12-31
A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.
PARAMETRIC MODEL OF LUMBAR VERTEBRA
Directory of Open Access Journals (Sweden)
CAPPETTI Nicola
2010-11-01
Full Text Available The present work proposes the realization of a parametric/variational CAD model of a normotype lumbar vertebra, which could be used for improving the effectiveness of actual imaging techniques in informational augmentation of the orthopaedic and traumatological diagnosis. In addition it could be used for ergonomic static and dynamical analysis of the lumbar region and vertebral column.
Parametric programming of industrial robots
Directory of Open Access Journals (Sweden)
Szulczyński Paweł
2015-06-01
Full Text Available This article proposes the use of parametric design software, commonly used by architects, in order to obtain complex trajectory and program code for industrial robots. The paper describes the drawbacks of existing solutions and proposes a new script to obtain a correct program. The result of the algorithm was verified experimentally.
Relational Parametricity and Separation Logic
DEFF Research Database (Denmark)
Birkedal, Lars; Yang, Hongseok
2008-01-01
Separation logic is a recent extension of Hoare logic for reasoning about programs with references to shared mutable data structures. In this paper, we provide a new interpretation of the logic for a programming language with higher types. Our interpretation is based on Reynolds's relational...... parametricity, and it provides a formal connection between separation logic and data abstraction. Udgivelsesdato: 2008...
International Nuclear Information System (INIS)
Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe
2014-01-01
An improved Hilbert-Huang transform method is developed to the time-frequency analysis of non-stationary signals in tokamak plasmas. Maximal overlap discrete wavelet packet transform rather than wavelet packet transform is proposed as a preprocessor to decompose a signal into various narrow-band components. Then, a correlation coefficient based selection method is utilized to eliminate the irrelevant intrinsic mode functions obtained from empirical mode decomposition of those narrow-band components. Subsequently, a time varying vector autoregressive moving average model instead of Hilbert spectral analysis is performed to compute the Hilbert spectrum, i.e., a three-dimensional time-frequency distribution of the signal. The feasibility and effectiveness of the improved Hilbert-Huang transform method is demonstrated by analyzing a non-stationary simulated signal and actual experimental signals in fusion plasmas
Testorf, M. E.; Jobst, B. C.; Kleen, J. K.; Titiz, A.; Guillory, S.; Scott, R.; Bujarski, K. A.; Roberts, D. W.; Holmes, G. L.; Lenck-Santini, P.-P.
2012-10-01
Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.
Jan, Shau-Shiun; Sun, Chih-Cheng
2010-01-01
The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.
Nam, Ki-Woo; Kang, Chang-Yong; Do, Jae-Yoon; Ahn, Seok-Hwan; Lee, Sang-Kee
2001-06-01
The fatigue crack propagation of super duplex stainless steel was investigated for the effect of various volume fractions of the austenite phase by changing the heat treatment temperature. We also analyzed acoustic emission signals obtained during the fatigue crack propagation by the time-frequency analysis method. As the temperature of the heat treatment increased, the volume fraction of austenite decreased and coarse grain was obtained. The specimen treated at 1200 had a longer fatigue life and slower rate of crack growth. Results of time-frequency analysis of acoustic emission signals during the fatigue test showed the main frequency of 200-300 kHz to have no correlation with heat treatment and crack length, and the 500 kHz signal to be due to dimples and separation of inclusion.
Agounad, Said; Aassif, El Houcein; Khandouch, Younes; Maze, Gérard; Décultot, Dominique
2018-01-01
The time and frequency analyses of the acoustic scattering by an elastic cylindrical shell in bistatic method show that the arrival times of the echoes and the resonance frequencies of the elastic waves propagating in and around the cylindrical shell are a function of the bistatic angle, β, between the emitter and receiver transducers. The aim of this work is to explain the observed results in time and frequency domains using time-frequency analysis and graphical interpretations. The performance of four widely used time-frequency representations, the Smoothed Pseudo Wigner-Ville (SPWV), the Spectrogram (SP), the reassignment SPWV, and the reassignment SP, are studied. The investigation into the evolution of the time-frequency plane as a function of the bistatic angle β shows that there are the waves propagating in counter-clockwise direction (labeled wave+) and the waves which propagate in clockwise direction (labeled waves-). In this paper the A, S0, and A1 circumferential waves are investigated. The graphical interpretations are used to explain the formation mechanism of these waves and the acoustic scattering in monostatic and bistatic configurations. The delay between the echoes of the waves+ and those of the waves- is expressed in the case of the circumnavigating wave (Scholte-Stoneley wave). This study shows that the observed waves at β = 0 ° and β = 18 0 ° are the result of the constructive interferences between the waves+ and the waves-. A comparative study of the physical properties (group velocity dispersion and cut-off frequency) of the waves+, the waves- and the waves observed in monostatic configuration is conducted. Furthermore, it is shown that the ability of the time-frequency representation to highlight the waves+ and the waves- is very useful, for example, for the detection and the localization of defaults, the classification purposes, etc.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.; Zhao, W. [State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China)
2016-05-15
The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.
International Nuclear Information System (INIS)
Zhang, Y.; Huang, S. L.; Wang, S.; Zhao, W.
2016-01-01
The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.
Zhang, Y; Huang, S L; Wang, S; Zhao, W
2016-05-01
The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert-Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of wave detection signals.
International Nuclear Information System (INIS)
Clapson, Andre-Claude; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Leroy, Nicolas; Varvella, Monica
2008-01-01
The detection of burst-type events in the output of ground gravitational wave detectors is particularly challenging. The potential variety of astrophysical waveforms, as proposed by simulations and analytic studies in general relativity and the discrimination of actual signals from instrumental noise both are critical issues. Robust methods that achieve reasonable detection performances over a wide range of signals are required. We present here a hybrid burst-detection pipeline related to time-frequency transforms while based on matched filtering to provide robustness against noise characteristics. Studies on simulated noise show that the algorithm has a detection efficiency similar to other methods over very different waveforms and particularly good timing even for low amplitude signals: no bias for most tested waveforms and an average accuracy of 1.1 ms (down to 0.1 ms in the best case). Time-frequency-type parameters, useful for event classification, are also derived for noise spectral densities unfavourable to standard time-frequency algorithms
Energy Technology Data Exchange (ETDEWEB)
Clapson, Andre-Claude; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Leroy, Nicolas; Varvella, Monica [LAL, Universite Paris-Sud 11, BP 34, 91898 Orsay (France)
2008-02-07
The detection of burst-type events in the output of ground gravitational wave detectors is particularly challenging. The potential variety of astrophysical waveforms, as proposed by simulations and analytic studies in general relativity and the discrimination of actual signals from instrumental noise both are critical issues. Robust methods that achieve reasonable detection performances over a wide range of signals are required. We present here a hybrid burst-detection pipeline related to time-frequency transforms while based on matched filtering to provide robustness against noise characteristics. Studies on simulated noise show that the algorithm has a detection efficiency similar to other methods over very different waveforms and particularly good timing even for low amplitude signals: no bias for most tested waveforms and an average accuracy of 1.1 ms (down to 0.1 ms in the best case). Time-frequency-type parameters, useful for event classification, are also derived for noise spectral densities unfavourable to standard time-frequency algorithms.
Towards a parametrization of multiparticle hadronic reactions
International Nuclear Information System (INIS)
Giffon, M.; Hama, Y.; Predazzi, E.
1979-11-01
An explicit parametrization of high energy exclusive production cross-sections is shown to give a reasonable account of inclusive data. This is a first step towards a phenomenological parametrization of multiparticle hadronic amplitudes
Bianchi surfaces: integrability in an arbitrary parametrization
International Nuclear Information System (INIS)
Nieszporski, Maciej; Sym, Antoni
2009-01-01
We discuss integrability of normal field equations of arbitrarily parametrized Bianchi surfaces. A geometric definition of the Bianchi surfaces is presented as well as the Baecklund transformation for the normal field equations in an arbitrarily chosen surface parametrization.
Parametric uncertainty in optical image modeling
Potzick, James; Marx, Egon; Davidson, Mark
2006-10-01
Optical photomask feature metrology and wafer exposure process simulation both rely on optical image modeling for accurate results. While it is fair to question the accuracies of the available models, model results also depend on several input parameters describing the object and imaging system. Errors in these parameter values can lead to significant errors in the modeled image. These parameters include wavelength, illumination and objective NA's, magnification, focus, etc. for the optical system, and topography, complex index of refraction n and k, etc. for the object. In this paper each input parameter is varied over a range about its nominal value and the corresponding images simulated. Second order parameter interactions are not explored. Using the scenario of the optical measurement of photomask features, these parametric sensitivities are quantified by calculating the apparent change of the measured linewidth for a small change in the relevant parameter. Then, using reasonable values for the estimated uncertainties of these parameters, the parametric linewidth uncertainties can be calculated and combined to give a lower limit to the linewidth measurement uncertainty for those parameter uncertainties.
Kotasidis, F. A.; Mehranian, A.; Zaidi, H.
2016-01-01
Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from
Time-Frequency-Wavenumber Analysis of Surface Waves Using the Continuous Wavelet Transform
Poggi, V.; Fäh, D.; Giardini, D.
2013-03-01
A modified approach to surface wave dispersion analysis using active sources is proposed. The method is based on continuous recordings, and uses the continuous wavelet transform to analyze the phase velocity dispersion of surface waves. This gives the possibility to accurately localize the phase information in time, and to isolate the most significant contribution of the surface waves. To extract the dispersion information, then, a hybrid technique is applied to the narrowband filtered seismic recordings. The technique combines the flexibility of the slant stack method in identifying waves that propagate in space and time, with the resolution of f- k approaches. This is particularly beneficial for higher mode identification in cases of high noise levels. To process the continuous wavelet transform, a new mother wavelet is presented and compared to the classical and widely used Morlet type. The proposed wavelet is obtained from a raised-cosine envelope function (Hanning type). The proposed approach is particularly suitable when using continuous recordings (e.g., from seismological-like equipment) since it does not require any hardware-based source triggering. This can be subsequently done with the proposed method. Estimation of the surface wave phase delay is performed in the frequency domain by means of a covariance matrix averaging procedure over successive wave field excitations. Thus, no record stacking is necessary in the time domain and a large number of consecutive shots can be used. This leads to a certain simplification of the field procedures. To demonstrate the effectiveness of the method, we tested it on synthetics as well on real field data. For the real case we also combine dispersion curves from ambient vibrations and active measurements.
Detection of Parametric Roll on Ships
DEFF Research Database (Denmark)
Galeazzi, Roberto; Blanke, Mogens; Poulsen, Niels Kjølstad
2012-01-01
phenomenon could make the navigator change ship’s speed and heading, and these remedial actions could make the vessel escape the bifurcation. This chapter proposes non-parametric methods to detect the onset of parametric roll resonance. Theoretical conditions for parametric resonance are re...... on experimental data from towing tank tests and data from a container ship passing an Atlantic storm....
Interactive Dimensioning of Parametric Models
Kelly, T.
2015-06-22
We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.
Parametric Optimization of Hospital Design
DEFF Research Database (Denmark)
Holst, Malene Kirstine; Kirkegaard, Poul Henning; Christoffersen, L.D.
2013-01-01
Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements...... and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences....
Parametric decay of the curvaton
International Nuclear Information System (INIS)
Enqvist, K; Nurmi, S; Rigopoulos, G I
2008-01-01
We argue that the curvaton decay takes place most naturally by way of a broad parametric resonance. The mechanism is analogous to resonant inflaton decay but does not require any tuning of the curvaton coupling strength to other scalar fields. For low scale inflation and a correspondingly low mass scale for the curvaton, we speculate on observable consequences including the possibility of stochastic gravitational waves
A Transformational Approach to Parametric Accumulated-Cost Static Profiling
DEFF Research Database (Denmark)
Haemmerlé, Rémy; López García, Pedro; Liqat, Umer
2016-01-01
Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound...... of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based...... on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource...
Parametric Fires for Structural Design
DEFF Research Database (Denmark)
Hertz, Kristian
2012-01-01
The authorities, the construction association, and a number of companies in Denmark have supported the author writing a guide for design of building structures for parametric fires. The guide is published by the ministry as a supplement to the building regulations. However, consultants and contra......The authorities, the construction association, and a number of companies in Denmark have supported the author writing a guide for design of building structures for parametric fires. The guide is published by the ministry as a supplement to the building regulations. However, consultants...... and contractors have asked for a reference in English in order to make the guide-lines and the background for them available internationally. The paper therefore presents recommendations from the design guide especially concerning how to assess parametric design fires based on the opening factor method for large...... compartments. Findings leading to the guide-lines are discussed, and it is indicated what a safe design fire model means for structural design and how it differs from a safe design fire model for evacuation. Furthermore, the paper includes some experiences from the application of the design guide in practise...
Liu, Su; Sha, Zhiyi; Sencer, Altay; Aydoseli, Aydin; Bebek, Nerse; Abosch, Aviva; Henry, Thomas; Gurses, Candan; Ince, Nuri Firat
2016-04-01
High frequency oscillations (HFOs) in intracranial electroencephalography (iEEG) recordings are considered as promising clinical biomarkers of epileptogenic regions in the brain. The aim of this study is to improve and automatize the detection of HFOs by exploring the time-frequency content of iEEG and to investigate the seizure onset zone (SOZ) detection accuracy during the sleep, awake and pre-ictal states in patients with epilepsy, for the purpose of assisting the localization of SOZ in clinical practice. Ten-minute iEEG segments were defined during different states in eight patients with refractory epilepsy. A three-stage algorithm was implemented to detect HFOs in these segments. First, an amplitude based initial detection threshold was used to generate a large pool of HFO candidates. Then distinguishing features were extracted from the time and time-frequency domain of the raw iEEG and used with a Gaussian mixture model clustering to isolate HFO events from other activities. The spatial distribution of HFO clusters was correlated with the seizure onset channels identified by neurologists in seven patient with good surgical outcome. The overlapping rates of localized channels and seizure onset locations were high in all states. The best result was obtained using the iEEG data during sleep, achieving a sensitivity of 81%, and a specificity of 96%. The channels with maximum number of HFOs identified epileptogenic areas where the seizures occurred more frequently. The current study was conducted using iEEG data collected in realistic clinical conditions without channel pre-exclusion. HFOs were investigated with novel features extracted from the entire frequency band, and were correlated with SOZ in different states. The results indicate that automatic HFO detection with unsupervised clustering methods exploring the time-frequency content of raw iEEG can be efficiently used to identify the epileptogenic zone with an accurate and efficient manner.
Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S
2018-02-01
Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to
International Nuclear Information System (INIS)
Sheu, Yae-lin; Hsu, Liang-Yan; Wu, Hau-tieng; Li, Peng-Cheng; Chu, Shih-I
2014-01-01
This study introduces a new adaptive time-frequency (TF) analysis technique, the synchrosqueezing transform (SST), to explore the dynamics of a laser-driven hydrogen atom at an ab initio level, upon which we have demonstrated its versatility as a new viable venue for further exploring quantum dynamics. For a signal composed of oscillatory components which can be characterized by instantaneous frequency, the SST enables rendering the decomposed signal based on the phase information inherited in the linear TF representation with mathematical support. Compared with the classical type of TF methods, the SST clearly depicts several intrinsic quantum dynamical processes such as selection rules, AC Stark effects, and high harmonic generation
DEFF Research Database (Denmark)
Jin, Lin; Yuan-zhang, Sun; Sørensen, Poul Ejnar
2012-01-01
published studies are based entirely on deterministic methodology. This paper presents a novel assessment method based on Time-Frequency Transformation to overcome shortcomings of existing methods. The main contribution of the paper is to propose a stochastic process simulation model which is a better...... alternative of the existing dynamic frequency deviation simulation model. In this way, the method takes the stochastic wind power fluctuation into full account so as to give a quantitative risk assessment of grid frequency deviation to grid operators, even without using any dynamic simulation tool. The case...
Stellar parametrization from Gaia RVS spectra
Recio-Blanco, A.; de Laverny, P.; Allende Prieto, C.; Fustes, D.; Manteiga, M.; Arcay, B.; Bijaoui, A.; Dafonte, C.; Ordenovic, C.; Ordoñez Blanco, D.
2016-01-01
Context. Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as GRVS~ 16. A specific stellar parametrization will be performed on most of these RVS spectra, I.e. those with enough high signal-to-noise ratio (S/N), which should correspond to single stars that have a magnitude in the RVS band brighter than ~14.5. Some individual chemical abundances will also be estimated for the brightest targets. Aims: We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-Spec working group of the analysis consortium. The tested codes are based on optimisation (FERRE and GAUGUIN), projection (MATISSE), or pattern-recognition methods (Artificial Neural Networks). We present and discuss each of their expected performances in the recovered stellar atmospheric parameters (effective temperature, surface gravity, overall metallicity) for B- to K-type stars. The performances for determining of [α/Fe] ratios are also presented for cool stars. Methods: Each code has been homogeneously tested with a large grid of RVS simulated synthetic spectra of BAFGK-spectral types (dwarfs and giants), with metallicities varying from 10-2.5 to 10+ 0.5 the solar metallicity, and taking variations of ±0.4 dex in the composition of the α-elements into consideration. The tests were performed for S/N ranging from ten to 350. Results: For all the stellar types we considered, stars brighter than GRVS~ 12.5 are very efficiently parametrized by the GSP-Spec pipeline, including reliable estimations of [α/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40 K in Teff, 0.10 dex in log(g), 0.04 dex in [M/H], and 0.03 dex in [α/Fe] at GRVS = 10.3. They degrade to 155 K in Teff, 0.15 dex in log(g), 0.10 dex in [M/H], and 0.1 dex in [α/Fe] at GRVS~ 12. Similar accuracies in Teff and [M/H] are
Sueda, Keitaro; Takeuchi, Fumiya; Shiraishi, Hideaki; Nakane, Shingo; Asahina, Naoko; Kohsaka, Shinobu; Nakama, Hideyuki; Otsuki, Taisuke; Sawamura, Yutaka; Saitoh, Shinji
2010-02-01
To evaluate the effectiveness of surgery for epilepsy, we analyzed rhythmic fast activity by magnetoencephalography (MEG) before and after surgery using time-frequency analysis. To assess reliability, the results obtained by pre-surgical MEG and intraoperative electrocorticography were compared. Four children with symptomatic localization-related epilepsy caused by circumscribed cortical lesion were examined in the present study using 204-channel helmet-shaped MEG with a sampling rate of 600Hz. One patient had dysembryoplastic neuroepithelial tumor (DNT) and three patients had focal cortical dysplasia (FCD). Aberrant areas were superimposed, to reconstruct 3D MRI images, and illustrated as moving images. In three patients, short-time Fourier transform (STFT) analyses of MEG showed rhythmic activities just above the lesion with FCD and in the vicinity of DNT. In one patient with FCD in the medial temporal lobe, rhythmic activity appeared in the ipsilateral frontal lobe and temporal lateral aspect. These findings correlate well with the results obtained by intraoperative electrocorticography. After the surgery, three patients were relieved of their seizures, and the area of rhythmic MEG activity disappeared or become smaller. One patient had residual rhythmic MEG activity, and she suffered from seizure relapse. Time-frequency analyses using STFT successfully depicted MEG rhythmic fast activity, and would provide valuable information for pre- and post-surgical evaluations to define surgical strategies for patients with epilepsy.
Xu, Chengjin; Guan, Junjun; Bao, Ming; Lu, Jiangang; Ye, Wei
2018-01-01
Based on vibration signals detected by a phase-sensitive optical time-domain reflectometer distributed optical fiber sensing system, this paper presents an implement of time-frequency analysis and convolutional neural network (CNN), used to classify different types of vibrational events. First, spectral subtraction and the short-time Fourier transform are used to enhance time-frequency features of vibration signals and transform different types of vibration signals into spectrograms, which are input to the CNN for automatic feature extraction and classification. Finally, by replacing the soft-max layer in the CNN with a multiclass support vector machine, the performance of the classifier is enhanced. Experiments show that after using this method to process 4000 vibration signal samples generated by four different vibration events, namely, digging, walking, vehicles passing, and damaging, the recognition rates of vibration events are over 90%. The experimental results prove that this method can automatically make an effective feature selection and greatly improve the classification accuracy of vibrational events in distributed optical fiber sensing systems.
Time-frequency featured co-movement between the stock and prices of crude oil and gold
Huang, Shupei; An, Haizhong; Gao, Xiangyun; Huang, Xuan
2016-02-01
The nonlinear relationships among variables caused by the hidden frequency information complicate the time series analysis. To shed more light on this nonlinear issue, we examine their relationships in joint time-frequency domain with multivariate framework, and the analyses in the time domain and frequency domain serve as comparisons. The daily Brent oil prices, London gold fixing price and Shanghai Composite index from January 1991 to September 2014 are adopted as example. First, they have long-term cointegration relationship in time domain from holistic perspective. Second, the Granger causality tests in different frequency bands are heterogeneous. Finally, the comparison between results from wavelet coherence and multiple wavelet coherence in the joint time-frequency domain indicates that in the high (1-14 days) and medium frequency (14-128 days) bands, the combination of Brent and gold prices has stronger correlation with the stock. In the low frequency band (256-512 days), year 2003 is the structure broken point before which Brent and oil are ideal choice for hedging the risk of the stock market. Thus, this paper offers more details between the Chinese stock market and the commodities markets of crude oil and gold, which suggests that the decisions for different time and frequencies should consider the corresponding benchmark information.
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.
Yang, Yang; Li, Xiukun
2016-06-01
Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time-frequency Blind Source Separation (BSS) can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time-frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner-Ville Distribution (WVD) observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. An experimental simulation has been used, with changes in the pulse width of the transmitted signal, the relative amplitude and the time delay parameter, in order to analyzing the feasibility of this new method. Simulation results show that the new method is not only able to separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.
A parametric costing model for wave energy technology
International Nuclear Information System (INIS)
1992-01-01
This document describes the philosophy and technical approach to a parametric cost model for offshore wave energy systems. Consideration is given both to existing known devices and other devices yet to be conceptualised. The report is complementary to a spreadsheet based cost estimating model. The latter permits users to derive capital cost estimates using either inherent default data or user provided data, if a particular scheme provides sufficient design definition for more accurate estimation. The model relies on design default data obtained from wave energy device designs and a set of specifically collected cost data. (author)
Parametric Verification of Weighted Systems
DEFF Research Database (Denmark)
Christoffersen, Peter; Hansen, Mikkel; Mariegaard, Anders
2015-01-01
are themselves indexed with linear equations. The parameters change the model-checking problem into a problem of computing a linear system of inequalities that characterizes the parameters that guarantee the satisfiability. To address this problem, we use parametric dependency graphs (PDGs) and we propose...... a global update function that yields an assignment to each node in a PDG. For an iterative application of the function, we prove that a fixed point assignment to PDG nodes exists and the set of assignments constitutes a well-quasi ordering, thus ensuring that the fixed point assignment can be found after...
Parametric Sensibility in Lixiviation Reactors
Directory of Open Access Journals (Sweden)
Dra. Margarita Rivera-Soto
2015-11-01
Full Text Available This work presents the results obtained in an analysis of the parametric sensibility, on the base of a mathematical model, which describes the behavior a lixiviation reactors battery inside the limits of the habitual work of the industrial plant, in a concrete process and of high complexity. The analysis was carried out with the purpose of determining the effect that the changes in different operation variables have on the behavior of the system and it gave as result that the most important variables are: the mineral-acid relationship, the concentration of magnesium and of nickel.
International Nuclear Information System (INIS)
D’Ambrosio, S.; Ferrari, A.; Galleani, L.
2015-01-01
Highlights: • Direct pressure-based techniques have been applied successfully to spark-ignition engines. • The burned mass fraction of pressure-based techniques has been compared with that of 2- and 3-zone combustion models. • The time frequency analysis has been employed to simulate complex diesel combustion events. - Abstract: In-cylinder pressure measurement and analysis has historically been a key tool for off-line combustion diagnosis in internal combustion engines, but online applications for real-time condition monitoring and combustion management have recently become popular. The present investigation presents and compares different low computing-cost in-cylinder pressure based methods for the analyses of the main features of combustion, that is, the start of combustion, the end of combustion and the crankshaft angle that responds to half of the overall burned mass. The instantaneous pressure in the combustion chamber has been used as an input datum for the described analytical procedures and it has been measured by means of a standard piezoelectric transducer. Traditional pressure-based techniques have been shown to be able to predict the burned mass fraction time history more accurately in spark ignition engines than in diesel engines. The most suitable pressure-based techniques for both spark ignition and compression ignition engines have been chosen on the basis of the available experimental data. Time–frequency analysis has also been applied to the analysis of diesel combustion, which is richer in events than spark ignited combustion. Time frequency algorithms for the calculation of the mean instantaneous frequency are computationally efficient, allow the main events of the diesel combustion to be identified and provide the greatest benefits in the presence of multiple injection events. These algorithms can be optimized and applied to onboard diagnostics tools designed for real control, but can also be used as an advanced validation tool for
Evaluation of Two Energy Balance Closure Parametrizations
Eder, Fabian; De Roo, Frederik; Kohnert, Katrin; Desjardins, Raymond L.; Schmid, Hans Peter; Mauder, Matthias
2014-05-01
A general lack of energy balance closure indicates that tower-based eddy-covariance (EC) measurements underestimate turbulent heat fluxes, which calls for robust correction schemes. Two parametrization approaches that can be found in the literature were tested using data from the Canadian Twin Otter research aircraft and from tower-based measurements of the German Terrestrial Environmental Observatories (TERENO) programme. Our analysis shows that the approach of Huang et al. (Boundary-Layer Meteorol 127:273-292, 2008), based on large-eddy simulation, is not applicable to typical near-surface flux measurements because it was developed for heights above the surface layer and over homogeneous terrain. The biggest shortcoming of this parametrization is that the grid resolution of the model was too coarse so that the surface layer, where EC measurements are usually made, is not properly resolved. The empirical approach of Panin and Bernhofer (Izvestiya Atmos Oceanic Phys 44:701-716, 2008) considers landscape-level roughness heterogeneities that induce secondary circulations and at least gives a qualitative estimate of the energy balance closure. However, it does not consider any feature of landscape-scale heterogeneity other than surface roughness, such as surface temperature, surface moisture or topography. The failures of both approaches might indicate that the influence of mesoscale structures is not a sufficient explanation for the energy balance closure problem. However, our analysis of different wind-direction sectors shows that the upwind landscape-scale heterogeneity indeed influences the energy balance closure determined from tower flux data. We also analyzed the aircraft measurements with respect to the partitioning of the "missing energy" between sensible and latent heat fluxes and we could confirm the assumption of scalar similarity only for Bowen ratios 1.
Parametric nanomechanical amplification at very high frequency.
Karabalin, R B; Feng, X L; Roukes, M L
2009-09-01
Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.
Speaker Linking and Applications using Non-Parametric Hashing Methods
2016-09-08
nonparametric estimate of a multivariate density function,” The Annals of Math- ematical Statistics , vol. 36, no. 3, pp. 1049–1051, 1965. [9] E. A. Patrick...Speaker Linking and Applications using Non-Parametric Hashing Methods† Douglas Sturim and William M. Campbell MIT Lincoln Laboratory, Lexington, MA...with many approaches [1, 2]. For this paper, we focus on using i-vectors [2], but the methods apply to any embedding. For the task of speaker QBE and
Parametric Study of Sealant Nozzle
Yamamoto, Yoshimi
It has become apparent in recent years the advancement of manufacturing processes in the aerospace industry. Sealant nozzles are a critical device in the use of fuel tank applications for optimal bonds and for ground service support and repair. Sealants has always been a challenging area for optimizing and understanding the flow patterns. A parametric study was conducted to better understand geometric effects of sealant flow and to determine whether the sealant rheology can be numerically modeled. The Star-CCM+ software was used to successfully develop the parametric model, material model, physics continua, and simulate the fluid flow for the sealant nozzle. The simulation results of Semco sealant nozzles showed the geometric effects of fluid flow patterns and the influences from conical area reduction, tip length, inlet diameter, and tip angle parameters. A smaller outlet diameter induced maximum outlet velocity at the exit, and contributed to a high pressure drop. The conical area reduction, tip angle and inlet diameter contributed most to viscosity variation phenomenon. Developing and simulating 2 different flow models (Segregated Flow and Viscous Flow) proved that both can be used to obtain comparable velocity and pressure drop results, however; differences are seen visually in the non-uniformity of the velocity and viscosity fields for the Viscous Flow Model (VFM). A comprehensive simulation setup for sealant nozzles was developed so other analysts can utilize the data.
Dose-response curve estimation: a semiparametric mixture approach.
Yuan, Ying; Yin, Guosheng
2011-12-01
In the estimation of a dose-response curve, parametric models are straightforward and efficient but subject to model misspecifications; nonparametric methods are robust but less efficient. As a compromise, we propose a semiparametric approach that combines the advantages of parametric and nonparametric curve estimates. In a mixture form, our estimator takes a weighted average of the parametric and nonparametric curve estimates, in which a higher weight is assigned to the estimate with a better model fit. When the parametric model assumption holds, the semiparametric curve estimate converges to the parametric estimate and thus achieves high efficiency; when the parametric model is misspecified, the semiparametric estimate converges to the nonparametric estimate and remains consistent. We also consider an adaptive weighting scheme to allow the weight to vary according to the local fit of the models. We conduct extensive simulation studies to investigate the performance of the proposed methods and illustrate them with two real examples. © 2011, The International Biometric Society.
A general approach to optomechanical parametric instabilities
International Nuclear Information System (INIS)
Evans, M.; Barsotti, L.; Fritschel, P.
2010-01-01
We present a simple feedback description of parametric instabilities which can be applied to a variety of optical systems. Parametric instabilities are of particular interest to the field of gravitational-wave interferometry where high mechanical quality factors and a large amount of stored optical power have the potential for instability. In our use of Advanced LIGO as an example application, we find that parametric instabilities, if left unaddressed, present a potential threat to the stability of high-power operation.
Connections between classical and parametric network entropies.
Directory of Open Access Journals (Sweden)
Matthias Dehmer
Full Text Available This paper explores relationships between classical and parametric measures of graph (or network complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity.
Directory of Open Access Journals (Sweden)
Lutao Liu
2018-04-01
Full Text Available In this paper, a system for identifying eight kinds of radar waveforms is explored. The waveforms are the binary phase shift keying (BPSK, Costas codes, linear frequency modulation (LFM and polyphase codes (including P1, P2, P3, P4 and Frank codes. The features of power spectral density (PSD, moments and cumulants, instantaneous properties and time-frequency analysis are extracted from the waveforms and three new features are proposed. The classifier is support vector machine (SVM, which is optimized by artificial bee colony (ABC algorithm. The system shows well robustness, excellent computational complexity and high recognition rate under low signal-to-noise ratio (SNR situation. The simulation results indicate that the overall recognition rate is 92% when SNR is −4 dB.
A Sparsity-Based Approach to 3D Binaural Sound Synthesis Using Time-Frequency Array Processing
Cobos, Maximo; Lopez, JoseJ; Spors, Sascha
2010-12-01
Localization of sounds in physical space plays a very important role in multiple audio-related disciplines, such as music, telecommunications, and audiovisual productions. Binaural recording is the most commonly used method to provide an immersive sound experience by means of headphone reproduction. However, it requires a very specific recording setup using high-fidelity microphones mounted in a dummy head. In this paper, we present a novel processing framework for binaural sound recording and reproduction that avoids the use of dummy heads, which is specially suitable for immersive teleconferencing applications. The method is based on a time-frequency analysis of the spatial properties of the sound picked up by a simple tetrahedral microphone array, assuming source sparseness. The experiments carried out using simulations and a real-time prototype confirm the validity of the proposed approach.
DEFF Research Database (Denmark)
Mørup, Morten; Hansen, Lars Kai; Parnas, Josef
2006-01-01
We demonstrate how non-negative matrix factorization (NMF) can be used to decompose the inter trial phase coherence (ITPC) of multi-channel EEG to yield a unique decomposition of time-frequency signatures present in various degrees in the recording channels. The NMF optimization is easily...... generalized to a parallel factor (PARAFAC) model to form a non-negative multi-way factorization (NMWF). While the NMF can examine subject specific activities the NMWF can effectively extract the most similar activities across subjects and or conditions. The methods are tested on a proprioceptive stimulus...... consisting of a weight change in a handheld load. While somatosensory gamma oscillations have previously only been evoked by electrical stimuli we hypothesized that a natural proprioceptive stimulus also would be able to evoke gamma oscillations. ITPC maxima were determined by visual inspection...
International Nuclear Information System (INIS)
Kim, Hyun Soo; Nam, Ki Woo; Kang, Chang Young
2000-01-01
Demand for now nondestructive evaluation are growing to detect fatigue crack growth behavior to predict long term performance of materials and structure in aggressive environments, especially when they are in non-visible area. Acoustic emission technique is well suited to these problems and has drawn a keen interests because of its dynamic detection ability, extreme sensitivity and location of growing defects. In this study, we analysed acoustic emission signals obtained in fatigue and tensile test of high strength fire resistance steel for frame structure with time-frequency analysis methods. The main frequency range is different in the noise and the fatigue crack propagation. It could be classified that it were also generated by composite fracture mechanics of cleavage, dimple, inclusion separation etc
Directory of Open Access Journals (Sweden)
Matteo Gandetto
2004-09-01
Full Text Available The use of time-frequency distributions is proposed as a nonlinear signal processing technique that is combined with a pattern recognition approach to identify superimposed transmission modes in a reconfigurable wireless terminal based on software-defined radio techniques. In particular, a software-defined radio receiver is described aiming at the identification of two coexistent communication modes: frequency hopping code division multiple access and direct sequence code division multiple access. As a case study, two standards, based on the previous modes and operating in the same band (industrial, scientific, and medical, are considered: IEEE WLAN 802.11b (direct sequence and Bluetooth (frequency hopping. Neural classifiers are used to obtain identification results. A comparison between two different neural classifiers is made in terms of relative error frequency.
Acceleration of the direct reconstruction of linear parametric images using nested algorithms
International Nuclear Information System (INIS)
Wang Guobao; Qi Jinyi
2010-01-01
Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.
Addison, Paul S.; Watson, James N.
2004-11-01
We present a novel time-frequency method for the measurement of oxygen saturation using the photoplethysmogram (PPG) signals from a standard pulse oximeter machine. The method utilizes the time-frequency transformation of the red and infrared PPGs to derive a 3D Lissajous figure. By selecting the optimal Lissajous, the method provides an inherently robust basis for the determination of oxygen saturation as regions of the time-frequency plane where high- and low-frequency signal artefacts are to be found are automatically avoided.
On the problem of neutron spectroscopy of parametrically non-equilibrium quasiparticles in solids
International Nuclear Information System (INIS)
Vo Khong An'.
1981-01-01
A suitable for numerical estimations formula for coherent neutron inelastic scattering cross sections on the plasmon-phonon mixed modes of electron-phonon systems in the parametric resonance conditions is obtained from the analytical one presented in the previous work using some relations of the general parametric excitation theory. The cross sections of neutron scattering on the high-frequency plasmon-like and the low-frequency longitudinal optical phonon-like modes in InSb crystals are calculated as functions of the driving laser field intensity, which show an increase in values by about two orders of magnitude as the field intensity approaches the parametric excitation threshold
Influence of Surge Motion on the Probability of Parametric Roll in a Stationary Sea State
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher; Vidic-Perunovic, Jelena; Pedersen, Preben Terndrup
2007-01-01
A typical parametric roll scenario for a ship in head waves implies that the roll motion is coupled with vertical motion of the vessel. The added resistance of the ship is increased when the bow pitches down in a wave crest. As a consequence, the ship speed is slowed down and, hence, the roll...... resonance condition might be changed. In an attempt to study the influence of this speed variation in waves on parametric roll, the procedure for estimation of probability of parametric roll by Jensen and Pedersen (2006) has been extended to account for the surge motion of the vessel....
Housing price prediction: parametric versus semi-parametric spatial hedonic models
Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema
2018-01-01
House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.
Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation
Pentaris, Fragkiskos P.; Fouskitakis, George N.
2014-05-01
The problem of modal identification in civil structures is of crucial importance, and thus has been receiving increasing attention in recent years. Vibration-based methods are quite promising as they are capable of identifying the structure's global characteristics, they are relatively easy to implement and they tend to be time effective and less expensive than most alternatives [1]. This paper focuses on the off-line structural/modal identification of civil (concrete) structures subjected to low-level earthquake excitations, under which, they remain within their linear operating regime. Earthquakes and their details are recorded and provided by the seismological network of Crete [2], which 'monitors' the broad region of south Hellenic arc, an active seismic region which functions as a natural laboratory for earthquake engineering of this kind. A sufficient number of seismic events are analyzed in order to reveal the modal characteristics of the structures under study, that consist of the two concrete buildings of the School of Applied Sciences, Technological Education Institute of Crete, located in Chania, Crete, Hellas. Both buildings are equipped with high-sensitivity and accuracy seismographs - providing acceleration measurements - established at the basement (structure's foundation) presently considered as the ground's acceleration (excitation) and at all levels (ground floor, 1st floor, 2nd floor and terrace). Further details regarding the instrumentation setup and data acquisition may be found in [3]. The present study invokes stochastic, both non-parametric (frequency-based) and parametric methods for structural/modal identification (natural frequencies and/or damping ratios). Non-parametric methods include Welch-based spectrum and Frequency response Function (FrF) estimation, while parametric methods, include AutoRegressive (AR), AutoRegressive with eXogeneous input (ARX) and Autoregressive Moving-Average with eXogeneous input (ARMAX) models[4, 5
Design of parametric software tools
DEFF Research Database (Denmark)
Sabra, Jakob Borrits; Mullins, Michael
2011-01-01
The studies investigate the field of evidence-based design used in architectural design practice and propose a method using 2D/3D CAD applications to: 1) enhance integration of evidence-based design knowledge in architectural design phases with a focus on lighting and interior design and 2) assess...... fulfilment of evidence-based design criterion regarding light distribution and location in relation to patient safety in architectural health care design proposals. The study uses 2D/3D CAD modelling software Rhinoceros 3D with plug-in Grasshopper to create parametric tool prototypes to exemplify...... the operations and functions of the design method. To evaluate the prototype potentials, surveys with architectural and healthcare design companies are conducted. Evaluation is done by the administration of questionnaires being part of the development of the tools. The results show that architects, designers...
Parametric instabilities in large plasmas
International Nuclear Information System (INIS)
Brambilla, Marco; Liberman, Bernardo.
1979-01-01
Parametric decay processes in large plasmas are considered as the linear stage of a three wave interaction (pump, sideband and beat wave) in which the amplitude of the externally excited pump is sufficiently large to neglect pump depletion to first order, yet sufficiently small to allow a linearized treatment of the pump propagation to zeroth order. The coupling coefficients are then obtained from an iterative solution of Vlasov equation, and a compact expression is derived, in which the multiple series over Bessel functions is explicitly summed. Even in the limit of a very long wavelength pump, the dispersion relation obtained in this way does not coincide with the one obtained using the well-known ''dipole'' approximation, unless both the sideband and beat wave are resonant modes of the plasma. An analysis of the origin of this discrepancy allows us to conclude that ''quasimodes'' (evanescent waves driven absolutely unstable by the pump) are more correctly described by the iterative approach
Parametric embedding for class visualization.
Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B
2007-09-01
We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.
Parametric studies on automotive radiators
International Nuclear Information System (INIS)
Oliet, C.; Oliva, A.; Castro, J.; Perez-Segarra, C.D.
2007-01-01
This paper presents a set of parametric studies performed on automotive radiators by means of a detailed rating and design heat exchanger model developed by the authors. This numerical tool has been previously verified and validated using a wide experimental data bank. A first part of the analysis focuses on the influence of working conditions on both fluids (mass flows, inlet temperatures) and the impact of the selected coolant fluid. Following these studies, the influence of some geometrical parameters is analysed (fin pitch, louver angle) as well as the importance of coolant flow lay-out on the radiator global performance. This work provides an overall behaviour report of automobile radiators working at usual range of operating conditions, while significant knowledge-based design conclusions have also been reported. The results show the utility of this numerical model as a rating and design tool for heat exchangers manufacturers, being a reasonable compromise between classic ε - NTU methods and CFD
Parametric instabilities in inhomogeneous plasma
International Nuclear Information System (INIS)
Nicholson, D.R.
1975-01-01
The nonlinear coupling of three waves in a plasma is considered. One of the waves is assumed large and constant; its amplitude is the parameter of the parametric instability. The spatial-temporal evolution of the other two waves is treated theoretically, in one dimension, by analytic methods and by direct numerical integration of the basic equations. Various monotonic forms of inhomogeneity are considered; agreement with previous work is found and new results are established. Nonmonotonic inhomogeneities are considered, in the form of turbulence and, as a model problem, in the form of a simple sinusoidal modulation. Relatively small amounts of nonmonotonic inhomogeneity, in the presence of a linear density gradient, are found to destabilize the well-known convective saturation, absolute growth occurring instead. (U.S.)
Optimal Design of Experiments for Parametric Identification of Civil Engineering Structures
Kirkegaard, Poul Henning
1991-01-01
Optimal Systems of experiments for parametric identification of civil engineering structures is investigated. Design of experiments for parametric identification of dynamic systems is usually done by minimizing a scalar measure, e.g the determinant, the trace ect., of an estimated parameter covariance matrix, based on prior knowledge. The experimental conditions available for adjustment, considering in this thesis, are input signal, sampling rate, the location of sensors and number of sensors.
Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.
Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao
2013-01-01
Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.
Integrable multi parametric SU(N) chain
International Nuclear Information System (INIS)
Foerster, Angela; Roditi, Itzhak; Rodrigues, Ligia M.C.S.
1996-03-01
We analyse integrable models associated to a multi parametric SU(N) R-matrix. We show that the Hamiltonians describe SU(N) chains with twisted boundary conditions and that the underlying algebraic structure is the multi parametric deformation of SU(N) enlarged by the introduction of a central element. (author). 15 refs
Observation of Parametric Instability in Advanced LIGO.
Evans, Matthew; Gras, Slawek; Fritschel, Peter; Miller, John; Barsotti, Lisa; Martynov, Denis; Brooks, Aidan; Coyne, Dennis; Abbott, Rich; Adhikari, Rana X; Arai, Koji; Bork, Rolf; Kells, Bill; Rollins, Jameson; Smith-Lefebvre, Nicolas; Vajente, Gabriele; Yamamoto, Hiroaki; Adams, Carl; Aston, Stuart; Betzweiser, Joseph; Frolov, Valera; Mullavey, Adam; Pele, Arnaud; Romie, Janeen; Thomas, Michael; Thorne, Keith; Dwyer, Sheila; Izumi, Kiwamu; Kawabe, Keita; Sigg, Daniel; Derosa, Ryan; Effler, Anamaria; Kokeyama, Keiko; Ballmer, Stefan; Massinger, Thomas J; Staley, Alexa; Heinze, Matthew; Mueller, Chris; Grote, Hartmut; Ward, Robert; King, Eleanor; Blair, David; Ju, Li; Zhao, Chunnong
2015-04-24
Parametric instabilities have long been studied as a potentially limiting effect in high-power interferometric gravitational wave detectors. Until now, however, these instabilities have never been observed in a kilometer-scale interferometer. In this Letter, we describe the first observation of parametric instability in a gravitational wave detector, and the means by which it has been removed as a barrier to progress.
Parametric Methods for Order Tracking Analysis
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm
2017-01-01
Order tracking analysis is often used to find the critical speeds at which structural resonances are excited by a rotating machine. Typically, order tracking analysis is performed via non-parametric methods. In this report, however, we demonstrate some of the advantages of using a parametric method...
Parametric resonance in neutrino oscillations in matter
Indian Academy of Sciences (India)
Neutrino oscillations in matter can exhibit a specific resonance enhancement - parametric resonance, which is different from the MSW resonance. Oscillations of atmospheric and solar neutrinos inside the earth can undergo parametric enhancement when neutrino trajectories cross the core of the earth. In this paper we ...
On the parametric approximation in quantum optics
Energy Technology Data Exchange (ETDEWEB)
D' Ariano, G.M.; Paris, M.G.A.; Sacchi, M.F. [Istituto Nazionale di Fisica Nucleare, Pavia (Italy); Pavia Univ. (Italy). Dipt. di Fisica ' Alessandro Volta'
1999-03-01
The authors perform the exact numerical diagonalization of Hamiltonians that describe both degenerate and nondegenerate parametric amplifiers, by exploiting the conservation laws pertaining each device. It is clarify the conditions under which the parametric approximation holds, showing that the most relevant requirements is the coherence of the pump after the interaction, rather than its un depletion.
On the parametric approximation in quantum optics
International Nuclear Information System (INIS)
D'Ariano, G.M.; Paris, M.G.A.; Sacchi, M.F.; Pavia Univ.
1999-01-01
The authors perform the exact numerical diagonalization of Hamiltonians that describe both degenerate and nondegenerate parametric amplifiers, by exploiting the conservation laws pertaining each device. It is clarify the conditions under which the parametric approximation holds, showing that the most relevant requirements is the coherence of the pump after the interaction, rather than its un depletion
Parametric form of QCD travelling waves
Peschanski, R.
2005-01-01
We derive parametric travelling-wave solutions of non-linear QCD equations. They describe the evolution towards saturation in the geometric scaling region. The method, based on an expansion in the inverse of the wave velocity, leads to a solvable hierarchy of differential equations. A universal parametric form of travelling waves emerges from the first two orders of the expansion.
Parametric modeling for damped sinusoids from multiple channels
DEFF Research Database (Denmark)
Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll
2013-01-01
frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....
Developing a Parametric Urban Design Tool
DEFF Research Database (Denmark)
Steinø, Nicolai; Obeling, Esben
2014-01-01
Parametric urban design is a potentially powerful tool for collaborative urban design processes. Rather than making one- off designs which need to be redesigned from the ground up in case of changes, parametric design tools make it possible keep the design open while at the same time allowing...... for a level of detailing which is high enough to facilitate an understan- ding of the generic qualities of proposed designs. Starting from a brief overview of parametric design, this paper presents initial findings from the development of a parametric urban design tool with regard to developing a structural...... logic which is flexible and expandable. It then moves on to outline and discuss further development work. Finally, it offers a brief reflection on the potentials and shortcomings of the software – CityEngine – which is used for developing the parametric urban design tool....
Parametric, nonparametric and parametric modelling of a chaotic circuit time series
Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.
2000-09-01
The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.
Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H; Maurits, Natasha M
2016-01-01
In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a
Parametric level correlations in random-matrix models
International Nuclear Information System (INIS)
Weidenmueller, Hans A
2005-01-01
We show that parametric level correlations in random-matrix theories are closely related to a breaking of the symmetry between the advanced and the retarded Green functions. The form of the parametric level correlation function is the same as for the disordered case considered earlier by Simons and Altshuler and is given by the graded trace of the commutator of the saddle-point solution with the particular matrix that describes the symmetry breaking in the actual case of interest. The strength factor differs from the case of disorder. It is determined solely by the Goldstone mode. It is essentially given by the number of levels that are strongly mixed as the external parameter changes. The factor can easily be estimated in applications
Parametric wave penetration through an overdense plasma layer
International Nuclear Information System (INIS)
Gradov, O.M.; Suender, D.
1981-01-01
The nonlinear penetration of an electromagnetic wave through an overdense plasma layer due to the excitation of parametric instabilities is studied. The quasistatic h.f. surface wave and the ion-acoustic wave, both parametrically growing, generate a nonlinear current which also exist beyound the linear skin length of the incident electromagnetic wave. This current leads to an exponential amplification of the electromagnetic wave amplitude in the layer. The growth rate of this process depends on the overthreshold value of the external wave intensity and the thickness of the layer. The saturation level of the transmitted wave amplitude is estimated for the case, when the instabilities are stabilized by generation of ion-acoustic harmonics. (author)
Dao, Duy; Salehizadeh, S M A; Noh, Yeonsik; Chong, Jo Woon; Cho, Chae Ho; McManus, Dave; Darling, Chad E; Mendelson, Yitzhak; Chon, Ki H
2017-09-01
Motion and noise artifacts (MNAs) impose limits on the usability of the photoplethysmogram (PPG), particularly in the context of ambulatory monitoring. MNAs can distort PPG, causing erroneous estimation of physiological parameters such as heart rate (HR) and arterial oxygen saturation (SpO2). In this study, we present a novel approach, "TifMA," based on using the time-frequency spectrum of PPG to first detect the MNA-corrupted data and next discard the nonusable part of the corrupted data. The term "nonusable" refers to segments of PPG data from which the HR signal cannot be recovered accurately. Two sequential classification procedures were included in the TifMA algorithm. The first classifier distinguishes between MNA-corrupted and MNA-free PPG data. Once a segment of data is deemed MNA-corrupted, the next classifier determines whether the HR can be recovered from the corrupted segment or not. A support vector machine (SVM) classifier was used to build a decision boundary for the first classification task using data segments from a training dataset. Features from time-frequency spectra of PPG were extracted to build the detection model. Five datasets were considered for evaluating TifMA performance: (1) and (2) were laboratory-controlled PPG recordings from forehead and finger pulse oximeter sensors with subjects making random movements, (3) and (4) were actual patient PPG recordings from UMass Memorial Medical Center with random free movements and (5) was a laboratory-controlled PPG recording dataset measured at the forehead while the subjects ran on a treadmill. The first dataset was used to analyze the noise sensitivity of the algorithm. Datasets 2-4 were used to evaluate the MNA detection phase of the algorithm. The results from the first phase of the algorithm (MNA detection) were compared to results from three existing MNA detection algorithms: the Hjorth, kurtosis-Shannon entropy, and time-domain variability-SVM approaches. This last is an approach
Directory of Open Access Journals (Sweden)
Wayne M Koster
Full Text Available Tributary and mainstem connections represent important links for the movement of fish and other biota throughout river networks. We investigated the timing, frequency and environmental conditions associated with movements by adult golden perch (Macquaria ambigua between the mainstem of the mid-Murray River and a tributary, the Goulburn River, in south-eastern Australia, using acoustic telemetry over four years (2007-2011. Fish were tagged and released in autumn 2007-2009 in the mid-Murray (n = 42 and lower Goulburn (n = 37 rivers within 3-6 km of the mid-Murray-lower Goulburn junction. 38% of tagged fish undertook mainstem-tributary movements, characterised mostly by temporary occupation followed by return of fish to the original capture river. Approximately 10% of tagged fish exhibited longer-term shifts between the mainstem and tributary. Movement of fish from the tributary into the mainstem occurred primarily during the spawning season and in some years coincided with the presence of golden perch eggs/larvae in drift samples in the mainstem. Many of the tributary-to-mainstem movements occurred during or soon after changes in flow. The movements of fish from the mainstem into the tributary were irregular and did not appear to be associated with spawning. The findings show that golden perch moved freely across the mainstem-tributary interface. This demonstrates the need to consider the spatial, behavioural and demographic interdependencies of aquatic fauna across geographic management units such as rivers.
Koster, Wayne M; Dawson, David R; O'Mahony, Damien J; Moloney, Paul D; Crook, David A
2014-01-01
Tributary and mainstem connections represent important links for the movement of fish and other biota throughout river networks. We investigated the timing, frequency and environmental conditions associated with movements by adult golden perch (Macquaria ambigua) between the mainstem of the mid-Murray River and a tributary, the Goulburn River, in south-eastern Australia, using acoustic telemetry over four years (2007-2011). Fish were tagged and released in autumn 2007-2009 in the mid-Murray (n = 42) and lower Goulburn (n = 37) rivers within 3-6 km of the mid-Murray-lower Goulburn junction. 38% of tagged fish undertook mainstem-tributary movements, characterised mostly by temporary occupation followed by return of fish to the original capture river. Approximately 10% of tagged fish exhibited longer-term shifts between the mainstem and tributary. Movement of fish from the tributary into the mainstem occurred primarily during the spawning season and in some years coincided with the presence of golden perch eggs/larvae in drift samples in the mainstem. Many of the tributary-to-mainstem movements occurred during or soon after changes in flow. The movements of fish from the mainstem into the tributary were irregular and did not appear to be associated with spawning. The findings show that golden perch moved freely across the mainstem-tributary interface. This demonstrates the need to consider the spatial, behavioural and demographic interdependencies of aquatic fauna across geographic management units such as rivers.
Koster, Wayne M.; Dawson, David R.; O’Mahony, Damien J.; Moloney, Paul D.; Crook, David A.
2014-01-01
Tributary and mainstem connections represent important links for the movement of fish and other biota throughout river networks. We investigated the timing, frequency and environmental conditions associated with movements by adult golden perch (Macquaria ambigua) between the mainstem of the mid-Murray River and a tributary, the Goulburn River, in south-eastern Australia, using acoustic telemetry over four years (2007–2011). Fish were tagged and released in autumn 2007–2009 in the mid-Murray (n = 42) and lower Goulburn (n = 37) rivers within 3–6 km of the mid-Murray-lower Goulburn junction. 38% of tagged fish undertook mainstem–tributary movements, characterised mostly by temporary occupation followed by return of fish to the original capture river. Approximately 10% of tagged fish exhibited longer-term shifts between the mainstem and tributary. Movement of fish from the tributary into the mainstem occurred primarily during the spawning season and in some years coincided with the presence of golden perch eggs/larvae in drift samples in the mainstem. Many of the tributary-to-mainstem movements occurred during or soon after changes in flow. The movements of fish from the mainstem into the tributary were irregular and did not appear to be associated with spawning. The findings show that golden perch moved freely across the mainstem–tributary interface. This demonstrates the need to consider the spatial, behavioural and demographic interdependencies of aquatic fauna across geographic management units such as rivers. PMID:24788137
International Nuclear Information System (INIS)
Ortigosa, Nuria; Fernández, Carmen; Galbis, Antonio; Cano, Óscar
2015-01-01
Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and patient classification is done afterwards, when its clinical course is available. In this paper we present a comparison of classification performances when differentiating paroxysmal and persistent atrial fibrillation episodes by means of support vector machines. We analyze short surface electrocardiogram recordings by extracting modulus and phase features from several time-frequency transforms: short-time Fourier transform, Wigner–Ville, Choi–Williams, Stockwell transform, and general Fourier-family transform. Overall, accuracy higher than 81% is obtained when classifying phase information features of real test ECGs from a heterogeneous cohort of patients (in terms of progression of the arrhythmia and antiarrhythmic treatment) recorded in a tertiary center. Therefore, phase features can facilitate the clinicians’ choice of the most appropriate treatment for each patient by means of a non-invasive technique (the surface ECG). (paper)
Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane
2017-06-01
Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.
Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane
2017-06-01
Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.
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.
Leahy, Lauren N.; Haslach, Henry W.
2018-02-01
During normal extracellular fluid (ECF) flow in the brain glymphatic system or during pathological flow induced by trauma resulting from impacts and blast waves, ECF-solid matter interactions result from sinusoidal shear waves in the brain and cranial arterial tissue, both heterogeneous biological tissues with high fluid content. The flow in the glymphatic system is known to be forced by pulsations of the cranial arteries at about 1 Hz. The experimental shear stress response to sinusoidal translational shear deformation at 1 Hz and 25% strain amplitude and either 0% or 33% compression is compared for rat cerebrum and bovine aortic tissue. Time-frequency analyses aim to correlate the shear stress signal frequency components over time with the behavior of brain tissue constituents to identify the physical source of the shear nonlinear viscoelastic response. Discrete fast Fourier transformation analysis and the novel application to the shear stress signal of harmonic wavelet decomposition both show significant 1 Hz and 3 Hz components. The 3 Hz component in brain tissue, whose magnitude is much larger than in aortic tissue, may result from interstitial fluid induced drag forces. The harmonic wavelet decomposition locates 3 Hz harmonics whose magnitudes decrease on subsequent cycles perhaps because of bond breaking that results in easier fluid movement. Both tissues exhibit transient shear stress softening similar to the Mullins effect in rubber. The form of a new mathematical model for the drag force produced by ECF-solid matter interactions captures the third harmonic seen experimentally.
Abid, Fathi; Kaffel, Bilel
2018-01-01
Understanding the interrelationships of the global macro assets is crucial for global macro investing. This paper investigates the local variance and the interconnection between the stock, gold, oil, Forex and the implied volatility markets in the time/frequency domains using the wavelet methodology, including the wavelet power spectrum, the wavelet squared coherence and phase difference, the wavelet multiple correlation and cross-correlation. The univariate analysis reveals that, in some crisis periods, underlying asset markets present the same pattern in terms of the wavelet power spectrum indicating high volatility for the medium scale, and that for the other market stress periods, volatility behaves differently. Moreover, unlike the underlying asset markets, the implied volatility markets are characterized by high power regions across the entire period, even in the absence of economic events. Bivariate results show a bidirectional relationship between the underlying assets and their corresponding implied volatility indexes, and a steady co-movement between the stock index and its corresponding fear index. Multiple correlation analysis indicates a strong correlation between markets at high scales with evidence of a nearly perfect integration for a period longer than a year. In addition, the hedging strategies based on the volatility index lead to an increase in portfolio correlation. On the other hand, the results from multiple cross-correlations reveal that the lead-lag effect starts from the medium scale and that the VIX (stock market volatility index) index is the potential leader or follower of the other markets.
Wavelet analysis of frequency chaos game signal: a time-frequency signature of the C. elegans DNA.
Messaoudi, Imen; Oueslati, Afef Elloumi; Lachiri, Zied
2014-12-01
Challenging tasks are encountered in the field of bioinformatics. The choice of the genomic sequence's mapping technique is one the most fastidious tasks. It shows that a judicious choice would serve in examining periodic patterns distribution that concord with the underlying structure of genomes. Despite that, searching for a coding technique that can highlight all the information contained in the DNA has not yet attracted the attention it deserves. In this paper, we propose a new mapping technique based on the chaos game theory that we call the frequency chaos game signal (FCGS). The particularity of the FCGS coding resides in exploiting the statistical properties of the genomic sequence itself. This may reflect important structural and organizational features of DNA. To prove the usefulness of the FCGS approach in the detection of different local periodic patterns, we use the wavelet analysis because it provides access to information that can be obscured by other time-frequency methods such as the Fourier analysis. Thus, we apply the continuous wavelet transform (CWT) with the complex Morlet wavelet as a mother wavelet function. Scalograms that relate to the organism Caenorhabditis elegans (C. elegans) exhibit a multitude of periodic organization of specific DNA sequences.
Shang, Jianyu; Deng, Zhihong; Fu, Mengyin; Wang, Shunting
2016-06-16
Traditional artillery guidance can significantly improve the attack accuracy and overall combat efficiency of projectiles, which makes it more adaptable to the information warfare of the future. Obviously, the accurate measurement of artillery spin rate, which has long been regarded as a daunting task, is the basis of precise guidance and control. Magnetoresistive (MR) sensors can be applied to spin rate measurement, especially in the high-spin and high-g projectile launch environment. In this paper, based on the theory of a MR sensor measuring spin rate, the mathematical relationship model between the frequency of MR sensor output and projectile spin rate was established through a fundamental derivation. By analyzing the characteristics of MR sensor output whose frequency varies with time, this paper proposed the Chirp z-Transform (CZT) time-frequency (TF) domain analysis method based on the rolling window of a Blackman window function (BCZT) which can accurately extract the projectile spin rate. To put it into practice, BCZT was applied to measure the spin rate of 155 mm artillery projectile. After extracting the spin rate, the impact that launch rotational angular velocity and aspect angle have on the extraction accuracy of the spin rate was analyzed. Simulation results show that the BCZT TF domain analysis method can effectively and accurately measure the projectile spin rate, especially in a high-spin and high-g projectile launch environment.
Berezina-Greene, Maria A.; Guinan, John J.
2015-12-01
To aid in understanding their origin, stimulus frequency otoacoustic emissions (SFOAEs) were measured at a series of tone frequencies using the suppression method, both with and without stimulation of medial olivocochlear (MOC) efferents, in anesthetized guinea pigs. Time-frequency analysis showed SFOAE energy peaks in 1-3 delay components throughout the measured frequency range (0.5-12 kHz). One component's delay usually coincided with the phase-gradient delay. When multiple delay components were present, they were usually near SFOAE dips. Below 2 kHz, SFOAE delays were shorter than predicted from mechanical measurements. With MOC stimulation, SFOAE amplitude was decreased at most frequencies, but was sometimes enhanced, and all SFOAE delay components were affected. The MOC effects and an analysis of model data suggest that the multiple SFOAE delay components arise at the edges of the traveling-wave peak, not far basal of the peak. Comparisons with published guinea-pig neural data suggest that the short latencies of low-frequency SFOAEs may arise from coherent reflection from an organ-of-Corti motion that has a shorter group delay than the traveling wave.
Multi-parametric variational data assimilation for hydrological forecasting
Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.
2017-12-01
Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.
Ionization Cooling using Parametric Resonances
Energy Technology Data Exchange (ETDEWEB)
Johnson, Rolland P.
2008-06-07
Ionization Cooling using Parametric Resonances was an SBIR project begun in July 2004 and ended in January 2008 with Muons, Inc., (Dr. Rolland Johnson, PI), and Thomas Jefferson National Accelerator Facility (JLab) (Dr. Yaroslav Derbenev, Subcontract PI). The project was to develop the theory and simulations of Parametric-resonance Ionization Cooling (PIC) so that it could be used to provide the extra transverse cooling needed for muon colliders in order to relax the requirements on the proton driver, reduce the site boundary radiation, and provide a better environment for experiments. During the course of the project, the theoretical understanding of PIC was developed and a final exposition is ready for publication. Workshops were sponsored by Muons, Inc. in May and September of 2007 that were devoted to the PIC technique. One outcome of the workshops was the interesting and somewhat unexpected realization that the beam emittances using the PIC technique can get small enough that space charge forces can be important. A parallel effort to develop our G4beamline simulation program to include space charge effects was initiated to address this problem. A method of compensating for chromatic aberrations by employing synchrotron motion was developed and simulated. A method of compensating for spherical aberrations using beamline symmetry was also developed and simulated. Different optics designs have been developed using the OptiM program in preparation for applying our G4beamline simulation program, which contains all the power of the Geant4 toolkit. However, no PIC channel design that has been developed has had the desired cooling performance when subjected to the complete G4beamline simulation program. This is believed to be the consequence of the difficulties of correcting the aberrations associated with the naturally large beam angles and beam sizes of the PIC method that are exacerbated by the fringe fields of the rather complicated channel designs that have been
Ionization Cooling using Parametric Resonances
International Nuclear Information System (INIS)
Johnson, Rolland P.
2008-01-01
Ionization Cooling using Parametric Resonances was an SBIR project begun in July 2004 and ended in January 2008 with Muons, Inc., (Dr. Rolland Johnson, PI), and Thomas Jefferson National Accelerator Facility (JLab) (Dr. Yaroslav Derbenev, Subcontract PI). The project was to develop the theory and simulations of Parametric-resonance Ionization Cooling (PIC) so that it could be used to provide the extra transverse cooling needed for muon colliders in order to relax the requirements on the proton driver, reduce the site boundary radiation, and provide a better environment for experiments. During the course of the project, the theoretical understanding of PIC was developed and a final exposition is ready for publication. Workshops were sponsored by Muons, Inc. in May and September of 2007 that were devoted to the PIC technique. One outcome of the workshops was the interesting and somewhat unexpected realization that the beam emittances using the PIC technique can get small enough that space charge forces can be important. A parallel effort to develop our G4beamline simulation program to include space charge effects was initiated to address this problem. A method of compensating for chromatic aberrations by employing synchrotron motion was developed and simulated. A method of compensating for spherical aberrations using beamline symmetry was also developed and simulated. Different optics designs have been developed using the OptiM program in preparation for applying our G4beamline simulation program, which contains all the power of the Geant4 toolkit. However, no PIC channel design that has been developed has had the desired cooling performance when subjected to the complete G4beamline simulation program. This is believed to be the consequence of the difficulties of correcting the aberrations associated with the naturally large beam angles and beam sizes of the PIC method that are exacerbated by the fringe fields of the rather complicated channel designs that have been
Parametric Decay during HHFW on NSTX
International Nuclear Information System (INIS)
Wilson, J.R.; Bernabei, S.; Biewer, T.; Diem, S.; Hosea, J.; LeBlanc, B.; Phillips, C.K.; Ryan, P.; Swain, D.W.
2005-01-01
High Harmonic Fast Wave (HHFW) heating experiments on NSTX have been observed to be accompanied by significant edge ion heating (T i >> T e ). This heating is found to be anisotropic with T perp > T par . Simultaneously, coherent oscillations have been detected with an edge Langmuir probe. The oscillations are consistent with parametric decay of the incident fast wave (ω > 13ω ci ) into ion Bernstein waves and an unobserved ion-cyclotron quasi-mode. The observation of anisotropic heating is consistent with Bernstein wave damping, and the Bernstein waves should completely damp in the plasma periphery as they propagate toward a cyclotron harmonic resonance. The number of daughter waves is found to increase with rf power, and to increase as the incident wave's toroidal wavelength increases. The frequencies of the daughter wave are separated by the edge ion cyclotron frequency. Theoretical calculations of the threshold for this decay in uniform plasma indicate an extremely small value of incident power should be required to drive the instability. While such decays are commonly observed at lower harmonics in conventional ICRF heating scenarios, they usually do not involve the loss of significant wave power from the pump wave. On NSTX an estimate of the power loss can be found by calculating the minimum power required to support the edge ion heating (presumed to come from the decay Bernstein wave). This calculation indicates at least 20-30% of the incident rf power ends up as decay waves
Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction
Picchio, M.; Mussida, C.
2010-01-01
Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce might therefore be a relevant issue when estimating gender wage gaps. This paper proposes a new semi-parametric estimator of densities in the presence of covariates which incorporates
Controlling flexible rotor vibrations using parametric excitation
Energy Technology Data Exchange (ETDEWEB)
Atepor, L, E-mail: katepor@yahoo.co [Department of Mechanical Engineering, University of Glasgow, G12 8QQ (United Kingdom)
2009-08-01
This paper presents both theoretical and experimental studies of an active vibration controller for vibration in a flexible rotor system. The paper shows that the vibration amplitude can be modified by introducing an axial parametric excitation. The perturbation method of multiple scales is used to solve the equations of motion. The steady-state responses, with and without the parametric excitation terms, is investigated. An experimental test machine uses a piezoelectric exciter mounted on the end of the shaft. The results show a reduction in the rotor response amplitude under principal parametric resonance, and some good correlation between theory and experiment.
Linear Parametric Model Checking of Timed Automata
DEFF Research Database (Denmark)
Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle
2001-01-01
We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication...... of a subclass of parametric timed automata (L/U automata), for which the emptiness problem is decidable, contrary to the full class where it is know to be undecidable. Also we present a number of lemmas enabling the verication eort to be reduced for L/U automata in some cases. We illustrate our approach...
Chaotic parametric soliton-like pulses in ferromagnetic-film active ring resonators
International Nuclear Information System (INIS)
Grishin, S. V.; Golova, T. M.; Morozova, M. A.; Romanenko, D. V.; Seleznev, E. P.; Sysoev, I. V.; Sharaevskii, Yu. P.
2015-01-01
The generation of quasi-periodic sequences of parametric soliton-like pulses in an active ring resonator with a ferromagnetic film via the three-wave parametric instability of a magnetostatic surface wave is studied theoretically and experimentally. These dissipative structures form in time due to the competition between the cubic nonlinearity caused by parametric coupling between spin waves and the time dispersion caused by the resonant cavity that is present in a self-oscillatory system. The development of dynamic chaos due to the parametric instability of a magnetostatic surface wave results in irregular behavior of a phase. However, this behavior does not break a quasi-periodic pulse sequence when the gain changes over a wide range. The generated soliton-like pulses have a chaotic nature, which is supported by the maximum Lyapunov exponent estimated from experimental time series
Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin
2016-10-01
Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.
Sun, Xiaole; Djordjevic, Ivan B.; Neifeld, Mark A.
2016-03-01
Free-space optical (FSO) channels can be characterized by random power fluctuations due to atmospheric turbulence, which is known as scintillation. Weak coherent source based FSO quantum key distribution (QKD) systems suffer from the scintillation effect because during the deep channel fading the expected detection rate drops, which then gives an eavesdropper opportunity to get additional information about protocol by performing photon number splitting (PNS) attack and blocking single-photon pulses without changing QBER. To overcome this problem, in this paper, we study a large-alphabet QKD protocol, which is achieved by using pulse-position modulation (PPM)-like approach that utilizes the time-frequency uncertainty relation of the weak coherent photon state, called here TF-PPM-QKD protocol. We first complete finite size analysis for TF-PPM-QKD protocol to give practical bounds against non-negligible statistical fluctuation due to finite resources in practical implementations. The impact of scintillation under strong atmospheric turbulence regime is studied then. To overcome the secure key rate performance degradation of TF-PPM-QKD caused by scintillation, we propose an adaptation method for compensating the scintillation impact. By changing source intensity according to the channel state information (CSI), obtained by classical channel, the adaptation method improves the performance of QKD system with respect to the secret key rate. The CSI of a time-varying channel can be predicted using stochastic models, such as autoregressive (AR) models. Based on the channel state predictions, we change the source intensity to the optimal value to achieve a higher secret key rate. We demonstrate that the improvement of the adaptation method is dependent on the prediction accuracy.
Shelley, Kirk H; Awad, Aymen A; Stout, Robert G; Silverman, David G
2006-04-01
In the process of determining oxygen saturation, the pulse oximeter functions as a photoelectric plethysmograph. By analyzing how the frequency spectrum of the pulse oximeter waveform changes over time, new clinically relevant features can be extracted. Thirty patients undergoing general anesthesia for abdominal surgery had their pulse oximeter, airway pressure and CO(2) waveforms collected (50 Hz). The pulse oximeter waveform was analyzed with a short-time Fourier transform using a moving 4096 point Hann window of 82 seconds duration. The frequency signal created by positive pressure ventilation was extracted using a peak detection algorithm in the frequency range of ventilation (0.08-0.4 Hz = 5-24 breaths/minute). The respiratory rate derived in this manner was compared to the respiratory rate as determined by CO(2) detection. In total, 52 hours of telemetry data were analyzed. The respiratory rate measured from the pulse oximeter waveform was found to have a 0.89 linear correlation when compared to CO(2) detection and airway pressure change. the bias was 0.03 breath/min, SD was 0.557 breath/min and the upper and lower limits of agreement were 1.145 and -1.083 breath/min respectively. The presence of motion artifact proved to be the primary cause of failure of this technique. Joint time frequency analysis of the pulse oximeter waveform can be used to determine the respiratory rate of ventilated patients and to quantify the impact of ventilation on the waveform. In addition, when applied to the pulse oximeter waveform new clinically relevant features were observed.
Spatial variability and parametric uncertainty in performance assessment models
International Nuclear Information System (INIS)
Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo
2011-01-01
The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)
Fast and Statistically Efficient Fundamental Frequency Estimation
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm; Jensen, Jesper Rindom
2016-01-01
Fundamental frequency estimation is a very important task in many applications involving periodic signals. For computational reasons, fast autocorrelation-based estimation methods are often used despite parametric estimation methods having superior estimation accuracy. However, these parametric...... a recursive solver. Via benchmarks, we demonstrate that the computation time is reduced by approximately two orders of magnitude. The proposed fast algorithm is available for download online....
Parametric Estimation by Generalized Moment Methods for Extremes
Czech Academy of Sciences Publication Activity Database
Fabián, Zdeněk
2008-01-01
Roč. 11, č. 4 (2008), s. 26-35 ISSN 1450-7196 R&D Projects: GA MŠk ME 949 Institutional research plan: CEZ:AV0Z10300504 Keywords : heavy tails * transformation-based score Subject RIV: BB - Applied Statistics, Operational Research
Parametric Estimation of Load for Air Force Data Centers
2015-03-27
inferential statistics . The purpose of descriptive statistics is to describe and summarize the characteristics of a sample. To accomplish that...28 Descriptive Statistical Analysis... Inferential Statistical Analysis ....................................................................................33 Contrasting with Sixty Percent
Linear minimax estimation for random vectors with parametric uncertainty
Bitar, E; Baeyens, E; Packard, A; Poolla, K
2010-01-01
consider two uncertainty models, PA and PB. Model PA represents X and Y as jointly Gaussian whose covariance matrix Λ belongs to the convex hull of a set of m known covariance matrices. Model PB characterizes X and Y as jointly distributed according to a
Estimation of Parametric Roll in a Stochastic Seaway
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher; Pedersen, Preben Terndrup; Vidic-Perunovic, Jelena
2008-01-01
-degree of freedom (roll and heave) time domain model [10]. In the present paper the effect of the increased added resistance when the bow heaves and pitches down in a wave crest is introduced. Due to the resulting forward speed variation the roll resonance condition will be changed. The influence of ship speed...
Robust Parametric Fault Estimation in a Hopper System
DEFF Research Database (Denmark)
Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal
2012-01-01
The ability of diagnosis of the possible faults is a necessity for satellite launch vehicles during their mission. In this paper, a structural analysis method is employed to divide the complex propulsion system into simpler subsystems for fault diagnosis filter design. A robust fault diagnosis me...
Impacts of Advanced Manufacturing Technology on Parametric Estimating
1989-12-01
been build ( Blois , p. 65). As firms move up the levels of automation, there is a large capital investment to acquire robots, computer numerically...Affordable Acquisition Approach Study, Executive Summary, Air Force Systems Command, Andrews AFB, Maryland, February 9, 1983. Blois , K.J., "Manufacturing
Efficient Characterization of Parametric Uncertainty of Complex (Biochemical Networks.
Directory of Open Access Journals (Sweden)
Claudia Schillings
2015-08-01
Full Text Available Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.
Parametric optimization of inverse trapezoid oleophobic surfaces
DEFF Research Database (Denmark)
Cavalli, Andrea; Bøggild, Peter; Okkels, Fridolin
2012-01-01
In this paper, we introduce a comprehensive and versatile approach to the parametric shape optimization of oleophobic surfaces. We evaluate the performance of inverse trapezoid microstructures in terms of three objective parameters: apparent contact angle, maximum sustainable hydrostatic pressure...
Parametric decay below the upper hybrid frequency
Energy Technology Data Exchange (ETDEWEB)
Albers, E; Krause, K; Schlueter, H [Bochum Univ. (Germany, F.R.). Inst. fuer Experimentalphysik 2
1977-03-21
Parametric decay of the upper hybrid mode is observed between the electron cyclotron frequency and its first two harmonics. The decay products are identified as electron Bernstein and ion acoustic mode. The diagnostic results confirm the relevant dispersion relations.
Robust and Efficient Parametric Face Alignment
Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja
2011-01-01
We propose a correlation-based approach to parametric object alignment particularly suitable for face analysis applications which require efficiency and robustness against occlusions and illumination changes. Our algorithm registers two images by iteratively maximizing their correlation coefficient
Ranking Forestry Investments With Parametric Linear Programming
Paul A. Murphy
1976-01-01
Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.
Parametric resonance in neutrino oscillations in matter
Indian Academy of Sciences (India)
specific phase relationships has an interesting property that it can accumulate if the matter .... In Д 3 we discuss the physical interpretation of the parametric reso- nance in neutrino ..... long-baseline accelerator and reactor experiments [12,29].
von Hirschhausen, Christian R.; Cullmann, Astrid
2005-01-01
Abstract This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. We use labour, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) ...
Measuring economy-wide energy efficiency performance: A parametric frontier approach
International Nuclear Information System (INIS)
Zhou, P.; Ang, B.W.; Zhou, D.Q.
2012-01-01
This paper proposes a parametric frontier approach to estimating economy-wide energy efficiency performance from a production efficiency point of view. It uses the Shephard energy distance function to define an energy efficiency index and adopts the stochastic frontier analysis technique to estimate the index. A case study of measuring the economy-wide energy efficiency performance of a sample of OECD countries using the proposed approach is presented. It is found that the proposed parametric frontier approach has higher discriminating power in energy efficiency performance measurement compared to its nonparametric frontier counterparts.
Schmidt, K; Witte, H
1999-11-01
Recently the assumption of the independence of individual frequency components in a signal has been rejected, for example, for the EEG during defined physiological states such as sleep or sedation [9, 10]. Thus, the use of higher-order spectral analysis capable of detecting interrelations between individual signal components has proved useful. The aim of the present study was to investigate the quality of various non-parametric and parametric estimation algorithms using simulated as well as true physiological data. We employed standard algorithms available for the MATLAB. The results clearly show that parametric bispectral estimation is superior to non-parametric estimation in terms of the quality of peak localisation and the discrimination from other peaks.
Parametric design study of tandem mirror fusion reactors
International Nuclear Information System (INIS)
Carlson, G.A.
1977-01-01
The parametric design study of the tandem mirror reactor (TMR) is described. The results of this study illustrate the variation of reactor characteristics with changes in the independent design parameters, reveal the set of design parameters which minimizes the cost of the reactor, and show the sensitivity of the optimized design to physics and technological uncertainties. The total direct capital cost of an optimized 1000 MWe TMR is estimated to be $1300/kWe. The direct capital cost of a 2000 MWe plant is less than $1000/kWe
Tokamak transmutation of (nuclear) waste (TTW): Parametric studies
International Nuclear Information System (INIS)
Cheng, E.T.; Krakowski, R.A.; Peng, Y.K.M.
1994-01-01
Radioactive waste generated as part of the commercial-power and defense nuclear programs can be either stored or transmuted. The latter treatment requires a capital-intensive neutron source and is reserved for particularly hazardous and long-lived actinide and fission-product waste. A comparative description of fusion-based transmutation is made on the basis of rudimentary estimates of ergonic performance and transmutation capacities versus inventories for both ultra-low-aspect-ratio (spherical torus, ST) and conversional (aspect-ratio) tokamak fusion-power-core drivers. The parametric systems studies reported herein provides a preamble to more-detailed, cost-based systems analyses
Process simulation and parametric modeling for strategic project management
Morales, Peter J
2013-01-01
Process Simulation and Parametric Modeling for Strategic Project Management will offer CIOs, CTOs and Software Development Managers, IT Graduate Students an introduction to a set of technologies that will help them understand how to better plan software development projects, manage risk and have better insight into the complexities of the software development process.A novel methodology will be introduced that allows a software development manager to better plan and access risks in the early planning of a project. By providing a better model for early software development estimation and softw
Uncertainty importance analysis using parametric moment ratio functions.
Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen
2014-02-01
This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.
Parametric packet-based audiovisual quality model for IPTV services
Garcia, Marie-Neige
2014-01-01
This volume presents a parametric packet-based audiovisual quality model for Internet Protocol TeleVision (IPTV) services. The model is composed of three quality modules for the respective audio, video and audiovisual components. The audio and video quality modules take as input a parametric description of the audiovisual processing path, and deliver an estimate of the audio and video quality. These outputs are sent to the audiovisual quality module which provides an estimate of the audiovisual quality. Estimates of perceived quality are typically used both in the network planning phase and as part of the quality monitoring. The same audio quality model is used for both these phases, while two variants of the video quality model have been developed for addressing the two application scenarios. The addressed packetization scheme is MPEG2 Transport Stream over Real-time Transport Protocol over Internet Protocol. In the case of quality monitoring, that is the case for which the network is already set-up, the aud...
Parametric system identification of catamaran for improving controller design
Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai
2018-01-01
This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.
Regional and parametric sensitivity analysis of Sobol' indices
International Nuclear Information System (INIS)
Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen
2015-01-01
Nowadays, utilizing the Monte Carlo estimators for variance-based sensitivity analysis has gained sufficient popularity in many research fields. These estimators are usually based on n+2 sample matrices well designed for computing both the main and total effect indices, where n is the input dimension. The aim of this paper is to use such n+2 sample matrices to investigate how the main and total effect indices change when the uncertainty of the model inputs are reduced. For this purpose, the regional main and total effect functions are defined for measuring the changes on the main and total effect indices when the distribution range of one input is reduced, and the parametric main and total effect functions are introduced to quantify the residual main and total effect indices due to the reduced variance of one input. Monte Carlo estimators are derived for all the developed sensitivity concepts based on the n+2 samples matrices originally used for computing the main and total effect indices, thus no extra computational cost is introduced. The Ishigami function, a nonlinear model and a planar ten-bar structure are utilized for illustrating the developed sensitivity concepts, and for demonstrating the efficiency and accuracy of the derived Monte Carlo estimators. - Highlights: • The regional main and total effect functions are developed. • The parametric main and total effect functions are introduced. • The proposed sensitivity functions are all generalizations of Sobol' indices. • The Monte Carlo estimators are derived for the four sensitivity functions. • The computational cost of the estimators is the same as that of Sobol' indices
Organizational flexibility estimation
Komarynets, Sofia
2013-01-01
By the help of parametric estimation the evaluation scale of organizational flexibility and its parameters was formed. Definite degrees of organizational flexibility and its parameters for the Lviv region enterprises were determined. Grouping of the enterprises under the existing scale was carried out. Special recommendations to correct the enterprises behaviour were given.
Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations
Energy Technology Data Exchange (ETDEWEB)
Chen, Peng, E-mail: peng@ices.utexas.edu [The Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 East 24th Street, Stop C0200, Austin, TX 78712-1229 (United States); Schwab, Christoph, E-mail: christoph.schwab@sam.math.ethz.ch [Seminar für Angewandte Mathematik, Eidgenössische Technische Hochschule, Römistrasse 101, CH-8092 Zürich (Switzerland)
2016-07-01
We extend the reduced basis (RB) accelerated Bayesian inversion methods for affine-parametric, linear operator equations which are considered in [16,17] to non-affine, nonlinear parametric operator equations. We generalize the analysis of sparsity of parametric forward solution maps in [20] and of Bayesian inversion in [48,49] to the fully discrete setting, including Petrov–Galerkin high-fidelity (“HiFi”) discretization of the forward maps. We develop adaptive, stochastic collocation based reduction methods for the efficient computation of reduced bases on the parametric solution manifold. The nonaffinity and nonlinearity with respect to (w.r.t.) the distributed, uncertain parameters and the unknown solution is collocated; specifically, by the so-called Empirical Interpolation Method (EIM). For the corresponding Bayesian inversion problems, computational efficiency is enhanced in two ways: first, expectations w.r.t. the posterior are computed by adaptive quadratures with dimension-independent convergence rates proposed in [49]; the present work generalizes [49] to account for the impact of the PG discretization in the forward maps on the convergence rates of the Quantities of Interest (QoI for short). Second, we propose to perform the Bayesian estimation only w.r.t. a parsimonious, RB approximation of the posterior density. Based on the approximation results in [49], the infinite-dimensional parametric, deterministic forward map and operator admit N-term RB and EIM approximations which converge at rates which depend only on the sparsity of the parametric forward map. In several numerical experiments, the proposed algorithms exhibit dimension-independent convergence rates which equal, at least, the currently known rate estimates for N-term approximation. We propose to accelerate Bayesian estimation by first offline construction of reduced basis surrogates of the Bayesian posterior density. The parsimonious surrogates can then be employed for online data
Kbaier Ben Ismail, Dhouha; Lazure, Pascal; Puillat, Ingrid
2016-10-01
data. The Lomb-Scargle algorithm is adapted to unevenly-spaced data and is used as an alternative. The limits of the method are also set out. It was found that beyond 50% of missing measures, few significant frequencies are detected, several seasonalities are no more visible, and even a whole range of high frequency disappears progressively. Furthermore, two time-frequency decomposition methods, namely wavelets and Hilbert-Huang Transformation (HHT), are applied for the analysis of the entire dataset. Using the Continuous Wavelet Transform (CWT), some properties of the time series are determined. Then, the inertial wave and several low-frequency tidal waves are identified by the application of the Empirical Mode Decomposition (EMD). Finally, EMD based Time Dependent Intrinsic Correlation (TDIC) analysis is applied to consider the correlation between two nonstationary time series.
Parametric pendulum based wave energy converter
Yurchenko, Daniil; Alevras, Panagiotis
2018-01-01
The paper investigates the dynamics of a novel wave energy converter based on the parametrically excited pendulum. The herein developed concept of the parametric pendulum allows reducing the influence of the gravity force thereby significantly improving the device performance at a regular sea state, which could not be achieved in the earlier proposed original point-absorber design. The suggested design of a wave energy converter achieves a dominant rotational motion without any additional mechanisms, like a gearbox, or any active control involvement. Presented numerical results of deterministic and stochastic modeling clearly reflect the advantage of the proposed design. A set of experimental results confirms the numerical findings and validates the new design of a parametric pendulum based wave energy converter. Power harvesting potential of the novel device is also presented.
Parametric methods for spatial point processes
DEFF Research Database (Denmark)
Møller, Jesper
is studied in Section 4, and Bayesian inference in Section 5. On one hand, as the development in computer technology and computational statistics continues,computationally-intensive simulation-based methods for likelihood inference probably will play a increasing role for statistical analysis of spatial...... inference procedures for parametric spatial point process models. The widespread use of sensible but ad hoc methods based on summary statistics of the kind studied in Chapter 4.3 have through the last two decades been supplied by likelihood based methods for parametric spatial point process models......(This text is submitted for the volume ‘A Handbook of Spatial Statistics' edited by A.E. Gelfand, P. Diggle, M. Fuentes, and P. Guttorp, to be published by Chapmand and Hall/CRC Press, and planned to appear as Chapter 4.4 with the title ‘Parametric methods'.) 1 Introduction This chapter considers...
Parametric Conversion Using Custom MOS Varactors
Directory of Open Access Journals (Sweden)
Iniewski Krzysztof (Kris
2006-01-01
Full Text Available The possible role of customized MOS varactors in amplification, mixing, and frequency control of future millimeter wave CMOS RFICs is outlined. First, the parametric conversion concept is revisited and discussed in terms of modern RF communications systems. Second, the modeling, design, and optimization of MOS varactors are reconsidered in the context of their central role in parametric circuits. Third, a balanced varactor structure is proposed for robust oscillator frequency control in the presence of large extrinsic noise expected in tightly integrated wireless communicators. Main points include the proposal of a subharmonic pumping scheme based on the MOS varactor, a nonequilibrium elastance-voltage model, optimal varactor layout suggestions, custom m-CMOS varactor design and measurement, device-level balanced varactor simulations, and parametric circuit evaluation based on measured device characteristics.
Piezoelectric energy harvesting with parametric uncertainty
International Nuclear Information System (INIS)
Ali, S F; Friswell, M I; Adhikari, S
2010-01-01
The design and analysis of energy harvesting devices is becoming increasing important in recent years. Most of the literature has focused on the deterministic analysis of these systems and the problem of uncertain parameters has received less attention. Energy harvesting devices exhibit parametric uncertainty due to errors in measurement, errors in modelling and variability in the parameters during manufacture. This paper investigates the effect of parametric uncertainty in the mechanical system on the harvested power, and derives approximate explicit formulae for the optimal electrical parameters that maximize the mean harvested power. The maximum of the mean harvested power decreases with increasing uncertainty, and the optimal frequency at which the maximum mean power occurs shifts. The effect of the parameter variance on the optimal electrical time constant and optimal coupling coefficient are reported. Monte Carlo based simulation results are used to further analyse the system under parametric uncertainty
Parametric analysis of ATM solar array.
Singh, B. K.; Adkisson, W. B.
1973-01-01
The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.
Nonparametric predictive inference for combining diagnostic tests with parametric copula
Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.
2017-09-01
Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.
Parametric imaging of tumor perfusion and neovascular morphology using ultrasound
Hoyt, Kenneth
2015-03-01
A new image processing strategy is detailed for the simultaneous measurement of tumor perfusion and neovascular morphology parameters from a sequence of dynamic contrast-enhanced ultrasound (DCE-US) images. A technique for locally mapping tumor perfusion parameters using skeletonized neovascular data is also introduced. Simulated images were used to test the neovascular skeletonization technique and variance (error) of relevant parametric estimates. Preliminary DCE-US image datasets were collected in 6 female patients diagnosed with invasive breast cancer and using a Philips iU22 ultrasound system equipped with a L9-3 MHz transducer and Definity contrast agent. Simulation data demonstrates that neovascular morphology parametric estimation is reproducible albeit measurement error can occur at a lower signal-to-noise ratio (SNR). Experimental results indicate the feasibility of our approach to performing both tumor perfusion and neovascular morphology measurements from DCE-US images. Future work will expand on our initial clinical findings and also extent our image processing strategy to 3-dimensional space to allow whole tumor characterization.
Parametric Landau damping of space charge modes
Energy Technology Data Exchange (ETDEWEB)
Macridin, Alexandru [Fermilab; Burov, Alexey [Fermilab; Stern, Eric [Fermilab; Amundson, James [Fermilab; Spentzouris, Panagiotis [Fermilab
2016-09-23
Landau damping is the mechanism of plasma and beam stabilization; it arises through energy transfer from collective modes to the incoherent motion of resonant particles. Normally this resonance requires the resonant particle's frequency to match the collective mode frequency. We have identified an important new damping mechanism, parametric Landau damping, which is driven by the modulation of the mode-particle interaction. This opens new possibilities for stability control through manipulation of both particle and mode-particle coupling spectra. We demonstrate the existence of parametric Landau damping in a simulation of transverse coherent modes of bunched accelerator beams with space charge.
Parametric number covariance in quantum chaotic spectra.
Vinayak; Kumar, Sandeep; Pandey, Akhilesh
2016-03-01
We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.
Parametric frequency conversion in long Josephson junctions
International Nuclear Information System (INIS)
Irie, F.; Ashihara, S.; Yoshida, K.
1976-01-01
Current steps at voltages corresponding to the parametric coupling between an applied r.f. field and junction resonant modes have been observed in long Josephson tunnel junctions in the flux-flow state. The observed periodic variations of the step height due to the applied magnetic field are explained quantitatively by a perturbational analysis using Josephson phase equations. The present study demonstrates that the moving vortex array can serve as a coherent pump wave for signal waves propagating in the barrier region, which indicates, as a result, the possibility of traveling-wave parametric devices with long Josephson tunnel junctions. (author)
Oude Lansink, A.G.J.M.; Pietola, K.
2005-01-01
This paper applies a semi-parametric approach to estimating a generalised model of investments in heating installations. The results suggest that marginal costs of investments in heating installations increase quickly at small investment levels, whereas the increase slows down at higher investment
International Nuclear Information System (INIS)
Sterbentz, J.W.
1997-03-01
Parametric burnup calculations are performed to estimate radionuclide isotopic mass and activity concentrations for four different Training, Research, and Isotope General Atomics (TRIGA) nuclear reactor fuel element types: (1) Aluminum-clad standard, (2) Stainless Steel-clad standard, (3) High-enrichment Fuel Life Improvement Program (FLIP), and (4) Low-enrichment Fuel Life Improvement Program (FLIP-LEU-1). Parametric activity data are tabulated for 145 important radionuclides that can be used to generate gamma-ray emission source terms or provide mass quantity estimates as a function of decay time. Fuel element decay heats and dose rates are also presented parametrically as a function of burnup and decay time. Dose rates are given at the fuel element midplane for contact, 3.0-feet, and 3.0-meter detector locations in air. The data herein are estimates based on specially derived Beginning-of-Life (BOL) neutron cross sections using geometrically-explicit TRIGA reactor core models. The calculated parametric data should represent good estimates relative to actual values, although no experimental data were available for direct comparison and validation. However, because the cross sections were not updated as a function of burnup, the actinide concentrations may deviate from the actual values at the higher burnups
A non-parametric Bayesian approach to decompounding from high frequency data
Gugushvili, Shota; van der Meulen, F.H.; Spreij, Peter
2016-01-01
Given a sample from a discretely observed compound Poisson process, we consider non-parametric estimation of the density f0 of its jump sizes, as well as of its intensity λ0. We take a Bayesian approach to the problem and specify the prior on f0 as the Dirichlet location mixture of normal densities.
Evaluating Portfolio Value-At-Risk Using Semi-Parametric GARCH Models
J.V.K. Rombouts; M.J.C.M. Verbeek (Marno)
2009-01-01
textabstractIn this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes.
Energy Technology Data Exchange (ETDEWEB)
Schlemmer, Heinz-Peter [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Abt. Radiologie
2017-03-15
Multi-parametric NMR imaging in case of prostate carcinoma can improve diagnostics, allows reliable prognostic estimations and helps to find the optimum individual therapy. The contribution is focused to deliver the needed methodological tools and background knowledge for the daily routine.
Parametric variation of radiated power in Aditya Tokamak
International Nuclear Information System (INIS)
Tahiliani, Kumudni; Chowdhuri, M.B.; Manchanda, R.
2017-01-01
We report the study of parametric variation of radiated power in Aditya Tokamak for ohmic discharges. The radiated power was measured using AXUV diodes that are responsive to radiation in the range 1 eV to 4 keV and are insensitive to the neutral particles (<0.5 keV). Hence only the radiation power loss is measured and charge exchange losses are excluded. The measured radiated power was also used for the estimation of the effective ion charge, Z eff based on the scaling obtained by the regression analysis of the data from multiple Tokamaks. The estimated values were compared with the experimental Z eff values obtained from the visible continuum measurement. We also tested the scaling for modelled radiation power loss. (author)
2007-01-01
14 1.E-13 1.E+03 1.E+04 1.E+05 1.E+06 1.E+07 AVERAGING TIME τ (s) O V E R LA P P IN G σ y ( τ )/T H E O _B R (F R A C F R E Q ) METAS-NIST NPL-NIST... Metrologia , 42, 411-422. [2] C. Hackman, J. Levine, T. E. Parker, D. Piester and J. Becker, 2006, “A Straightforward Frequency- Estimation Technique for... Metrologia , 43, 109-120. [6] http://igscb.jpl.nasa.gov [7] G. Blewitt, 1989, “Carrier-Phase Ambiguity Resolution for the Global Positioning System Applied
Model reduction of parametrized systems
Ohlberger, Mario; Patera, Anthony; Rozza, Gianluigi; Urban, Karsten
2017-01-01
The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems. The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor t, carried out over the last 12 years, to build a growing research community in this field. Though not a textbook, some of the chapters ca...
Beattie, Zachary T.; Jacobs, Peter G.; Riley, Thomas C.; Hagen, Chad C.
2015-01-01
Sleep apnea is a serious health condition that affects many individuals and has been associated with serious health conditions such as cardiovascular disease. Clinical diagnosis of sleep apnea requires that a patient spend the night in a sleep clinic while being wired up to numerous obtrusive sensors. We are developing a system that utilizes respiration rate and breathing amplitude inferred from non-contact bed sensors (i.e. load cells placed under bed supports) to detect sleep apnea. Multi-harmonic artifacts generated either biologically or as a result of the impulse response of the bed have made it challenging to track respiration rate and amplitude with high resolution in time. In this paper, we present an algorithm that can accurately track respiration on a second-by-second basis while removing noise harmonics. The algorithm is tested using data collected from 5 patients during overnight sleep studies. Respiration rate is compared with polysomnography estimations of respiration rate estimated by a technician following clinical standards. Results indicate that certain subjects exhibit a large harmonic component of their breathing signal that can be removed by our algorithm. When compared with technician transcribed respiration rates using polysomnography signals, we demonstrate improved accuracy of respiration rate tracking using harmonic artifact rejection (mean error: 0.18 breaths/minute) over tracking not using harmonic artifact rejection (mean error: −2.74 breaths/minute). PMID:26738176
Non-parametric system identification from non-linear stochastic response
DEFF Research Database (Denmark)
Rüdinger, Finn; Krenk, Steen
2001-01-01
An estimation method is proposed for identification of non-linear stiffness and damping of single-degree-of-freedom systems under stationary white noise excitation. Non-parametric estimates of the stiffness and damping along with an estimate of the white noise intensity are obtained by suitable...... of the energy at mean-level crossings, which yields the damping relative to white noise intensity. Finally, an estimate of the noise intensity is extracted by estimating the absolute damping from the autocovariance functions of a set of modified phase plane variables at different energy levels. The method...
Non-asymptotic fractional order differentiators via an algebraic parametric method
Liu, Dayan
2012-08-01
Recently, Mboup, Join and Fliess [27], [28] introduced non-asymptotic integer order differentiators by using an algebraic parametric estimation method [7], [8]. In this paper, in order to obtain non-asymptotic fractional order differentiators we apply this algebraic parametric method to truncated expansions of fractional Taylor series based on the Jumarie\\'s modified Riemann-Liouville derivative [14]. Exact and simple formulae for these differentiators are given where a sliding integration window of a noisy signal involving Jacobi polynomials is used without complex mathematical deduction. The efficiency and the stability with respect to corrupting noises of the proposed fractional order differentiators are shown in numerical simulations. © 2012 IEEE.
Non-asymptotic fractional order differentiators via an algebraic parametric method
Liu, Dayan; Gibaru, O.; Perruquetti, Wilfrid
2012-01-01
Recently, Mboup, Join and Fliess [27], [28] introduced non-asymptotic integer order differentiators by using an algebraic parametric estimation method [7], [8]. In this paper, in order to obtain non-asymptotic fractional order differentiators we apply this algebraic parametric method to truncated expansions of fractional Taylor series based on the Jumarie's modified Riemann-Liouville derivative [14]. Exact and simple formulae for these differentiators are given where a sliding integration window of a noisy signal involving Jacobi polynomials is used without complex mathematical deduction. The efficiency and the stability with respect to corrupting noises of the proposed fractional order differentiators are shown in numerical simulations. © 2012 IEEE.
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Directory of Open Access Journals (Sweden)
Jinchao Feng
2018-03-01
Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Using Parametrics to Facilitate Collaborative Urban Design
DEFF Research Database (Denmark)
Steinø, Nicolai; Benbih, Karima; Obeling, Esben
2013-01-01
in the context of the urban South which is characterized by high urban growth rates, weak planning systems and modest means. The current state of planning and urban development in Morocco is introduced as a context for discussing collaborative urban design and parametric urban design, and some tentative...
Parametric Architectural Design with Point-clouds
DEFF Research Database (Denmark)
Zwierzycki, Mateusz; Evers, Henrik Leander; Tamke, Martin
2016-01-01
This paper investigates the efforts and benefits of the implementation of point clouds into architectural design processes and tools. Based on a study on the principal work processes of designers with point clouds the prototypical plugin/library - Volvox - was developed for the parametric modelling...
Global chaos synchronization of coupled parametrically excited ...
Indian Academy of Sciences (India)
In this paper, we study the synchronization behaviour of two linearly coupled parametrically excited chaotic pendula. The stability of the synchronized state is examined using Lyapunov stability theory and linear matrix inequality (LMI); and some sufficient criteria for global asymptotic synchronization are derived from which ...
Interdisciplinary parametric design : The XXL experience
Turrin, M.; Sariyildiz, I.S.; Paul, J.C.
2015-01-01
Focusing on large span structures for sport buildings, the paper tackles the role of parametric modelling and performance simulations, to enhance the integration between architectural and engineering design. The general approach contrasts post-engineering processes. In post-engineering, technical
The parametrized simulation of electromagnetic showers
International Nuclear Information System (INIS)
Peters, S.
1992-09-01
The simulation of electromagnetic showers in calorimeters by detailed tracking of all secondary particles is extremely computer time consuming. Without loosing considerably in precision, the use of parametrizations for global shower properties may reduce the computing time by factors of 10 1 to 10 4 , depending on the energy, the degree of parametrization, and the complexity in the material description and the cut off energies in the detailed simulation. To arrive at a high degree of universality, parametrizations of individual electromagnetic showers in homogeneous media are developed, taking the dependence of the shower development on the material into account. In sampling calorimeters, the inhomogeneous material distribution leads to additional effects which can be taken into account by geometry dependent terms in the parametrization of the longitudinal and radial energy density distributions. Comparisons with detailed simulations of homogeneous and sampling calorimeters show very good agreement in the fluctuations, correlations, and signal averages of spatial energy distributions. Verifications of the algorithms for the simulation of the H1 detector are performed using calorimeter test data for different moduls of the H1 liquid argon calorimeter. Special attention has been paid to electron pion separation, which is of great importance for physics analysis. (orig.) [de
Narrow linewidth pulsed optical parametric oscillator
Indian Academy of Sciences (India)
Tunable narrow linewidth radiation by optical parametric oscillation has many applications, particularly in spectroscopic investigation. In this paper, different techniques such as injection seeding, use of spectral selecting element like grating, grating and etalon in combination, grazing angle of incidence, entangled cavity ...
Consequences of hadron-nucleus multiplicity parametrization
International Nuclear Information System (INIS)
Singh, C.P.; Shyam, M.
1986-01-01
Some interesting consequences are analyzed of a new parametrization for the hadron-nucleus multiplicity distributions and they are compared with the experimental data. Further, it is illustrated how the scaling property for the average multiplicity will be modified and it is found that the experimental data support this behaviour. (orig.)
Simple parametrization of nucleon form factors
International Nuclear Information System (INIS)
Kelly, J.J.
2004-01-01
This Brief Report provides simple parametrizations of the nucleon electromagnetic form factors using functions of Q 2 that are consistent with dimensional scaling at high Q 2 . Good fits require only four parameters each for G Ep , G Mp , and G Mn and only two for G En
Parametric studies of tandem mirror reactors
International Nuclear Information System (INIS)
Carlson, G.A.; Boghosian, B.M.; Fink, J.H.; Myall, J.O.; Neef, W.S. Jr.
1979-01-01
This report, along with its companion, An Improved Tandem Mirror Reactor, discusses the recent progress and present status of our tandem mirror reactor studies. This report presents the detailed results of parametric studies up to, but not including, the very new ideas involving thermal barriers
Path integral quantization of parametrized field theory
International Nuclear Information System (INIS)
Varadarajan, Madhavan
2004-01-01
Free scalar field theory on a flat spacetime can be cast into a generally covariant form known as parametrized field theory in which the action is a functional of the scalar field as well as the embedding variables which describe arbitrary, in general curved, foliations of the flat spacetime. We construct the path integral quantization of parametrized field theory in order to analyze issues at the interface of quantum field theory and general covariance in a path integral context. We show that the measure in the Lorentzian path integral is nontrivial and is the analog of the Fradkin-Vilkovisky measure for quantum gravity. We construct Euclidean functional integrals in the generally covariant setting of parametrized field theory using key ideas of Schleich and show that our constructions imply the existence of nonstandard 'Wick rotations' of the standard free scalar field two-point function. We develop a framework to study the problem of time through computations of scalar field two-point functions. We illustrate our ideas through explicit computation for a time independent (1+1)-dimensional foliation. Although the problem of time seems to be absent in this simple example, the general case is still open. We discuss our results in the contexts of the path integral formulation of quantum gravity and the canonical quantization of parametrized field theory
Probabilistic Reachability for Parametric Markov Models
DEFF Research Database (Denmark)
Hahn, Ernst Moritz; Hermanns, Holger; Zhang, Lijun
2011-01-01
Given a parametric Markov model, we consider the problem of computing the rational function expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression...
Parametric Primitives for Hand Gesture Recognition
DEFF Research Database (Denmark)
Baby, Sanmohan; Krüger, Volker
2009-01-01
Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize parametric actions with object context is presented. Objects are key instruments in understanding...
Parametric Transverse Patterns in Broad Aperture Lasers
DEFF Research Database (Denmark)
Grigorieva, E.V.; Kashchenko, S.A.; Mosekilde, Erik
1998-01-01
Parametrically generated optical patterns are investigated for finite and large-scale transverse aperture lasers. Standing and rotating patterns as well as periodic and chaotic pattern alternations are described in the framework of the amplitude equation formalism. Sensitive dependence...... on the geometrical size of the system is demonstrated even in the case of large-scale systems....
Parametric instabilities in advanced gravitational wave detectors
International Nuclear Information System (INIS)
Gras, S; Zhao, C; Blair, D G; Ju, L
2010-01-01
As the LIGO interferometric gravitational wave detectors have finished gathering a large observational data set, an intense effort is underway to upgrade these observatories to improve their sensitivity by a factor of ∼10. High circulating power in the arm cavities is required, which leads to the possibility of parametric instability due to three-mode opto-acoustic resonant interactions between the carrier, transverse optical modes and acoustic modes. Here, we present detailed numerical analysis of parametric instability in a configuration that is similar to Advanced LIGO. After examining parametric instability for a single three-mode interaction in detail, we examine instability for the best and worst cases, as determined by the resonance condition of transverse modes in the power and signal recycling cavities. We find that, in the best case, the dual recycling detector is substantially less susceptible to instability than a single cavity, but its susceptibility is dependent on the signal recycling cavity design, and on tuning for narrow band operation. In all cases considered, the interferometer will experience parametric instability at full power operation, but the gain varies from 3 to 1000, and the number of unstable modes varies between 7 and 30 per test mass. The analysis focuses on understanding the detector complexity in relation to opto-acoustic interactions, on providing insights that can enable predictions of the detector response to transient disturbances, and of variations in thermal compensation conditions.
The Knowledge Base Interface for Parametric Grid Information
International Nuclear Information System (INIS)
Hipp, James R.; Simons, Randall W.; Young, Chris J.
1999-01-01
The parametric grid capability of the Knowledge Base (KBase) provides an efficient robust way to store and access interpolatable information that is needed to monitor the Comprehensive Nuclear Test Ban Treaty. To meet both the accuracy and performance requirements of operational monitoring systems, we use an approach which combines the error estimation of kriging with the speed and robustness of Natural Neighbor Interpolation. The method involves three basic steps: data preparation, data storage, and data access. In past presentations we have discussed in detail the first step. In this paper we focus on the latter two, describing in detail the type of information which must be stored and the interface used to retrieve parametric grid data from the Knowledge Base. Once data have been properly prepared, the information (tessellation and associated value surfaces) needed to support the interface functionality, can be entered into the KBase. The primary types of parametric grid data that must be stored include (1) generic header information; (2) base model, station, and phase names and associated ID's used to construct surface identifiers; (3) surface accounting information; (4) tessellation accounting information; (5) mesh data for each tessellation; (6) correction data defined for each surface at each node of the surfaces owning tessellation (7) mesh refinement calculation set-up and flag information; and (8) kriging calculation set-up and flag information. The eight data components not only represent the results of the data preparation process but also include all required input information for several population tools that would enable the complete regeneration of the data results if that should be necessary
A Strategy for a Parametric Flood Insurance Using Proxies
Haraguchi, M.; Lall, U.
2017-12-01
Traditionally, the design of flood control infrastructure and flood plain zoning require the estimation of return periods, which have been calculated by river hydraulic models with rainfall-runoff models. However, this multi-step modeling process leads to significant uncertainty to assess inundation. In addition, land use change and changing climate alter the potential losses, as well as make the modeling results obsolete. For these reasons, there is a strong need to create parametric indexes for the financial risk transfer for large flood events, to enable rapid response and recovery. Hence, this study examines the possibility of developing a parametric flood index at the national or regional level in Asia, which can be quickly mobilized after catastrophic floods. Specifically, we compare a single trigger based on rainfall index with multiple triggers using rainfall and streamflow indices by conducting case studies in Bangladesh and Thailand. The proposed methodology is 1) selecting suitable indices of rainfall and streamflow (if available), 2) identifying trigger levels for specified return periods for losses using stepwise and logistic regressions, 3) measuring the performance of indices, and 4) deriving return periods of selected windows and trigger levels. Based on the methodology, actual trigger levels were identified for Bangladesh and Thailand. Models based on multiple triggers reduced basis risks, an inherent problem in an index insurance. The proposed parametric flood index can be applied to countries with similar geographic and meteorological characteristics, and serve as a promising method for ex-ante risk financing for developing countries. This work is intended to be a preliminary work supporting future work on pricing risk transfer mechanisms in ex-ante risk finance.
Composite likelihood and two-stage estimation in family studies
DEFF Research Database (Denmark)
Andersen, Elisabeth Anne Wreford
2004-01-01
In this paper register based family studies provide the motivation for linking a two-stage estimation procedure in copula models for multivariate failure time data with a composite likelihood approach. The asymptotic properties of the estimators in both parametric and semi-parametric models are d...
International Nuclear Information System (INIS)
Kim, Su Jin; Lee, Jae Sung; Kim, Yu Kyeong; Lee, Dong Soo
2007-01-01
Parametric imaging allows us analysis of the entire brain or body image. Graphical approaches are commonly employed to generate parametric imaging through linear or multilinear regression. However, this linear regression method has limited accuracy due to bias in high level of noise data. Several methods have been proposed to reduce bias for linear regression estimation especially in reversible model. In this study, we focus on generating a net accumulation rate (K i ), which is related to binding parameter in brain receptor study, parametric imaging in an irreversible compartment model using multiple linear analysis. The reliability of a newly developed multiple linear analysis method (MLAIR) was assessed through the Monte Carlo simulation, and we applied it to a [ 11 C]MeNTI PET for opioid receptor
Parametric instabilities in magnetized bi-ion and dusty plasmas
Indian Academy of Sciences (India)
-ion or dusty plasma with parametric pumping of the magnetic field is analysed. The equation of motion governing the perturbed plasma is derived and parametrically excited transverse modes propagating along the magnetic field are found.
Ultrasonic defect characterization using parametric-manifold mapping
Velichko, A.; Bai, L.; Drinkwater, B. W.
2017-06-01
The aim of ultrasonic non-destructive evaluation includes the detection and characterization of defects, and an understanding of the nature of defects is essential for the assessment of structural integrity in safety critical systems. In general, the defect characterization challenge involves an estimation of defect parameters from measured data. In this paper, we explore the extent to which defects can be characterized by their ultrasonic scattering behaviour. Given a number of ultrasonic measurements, we show that characterization information can be extracted by projecting the measurement onto a parametric manifold in principal component space. We show that this manifold represents the entirety of the characterization information available from far-field harmonic ultrasound. We seek to understand the nature of this information and hence provide definitive statements on the defect characterization performance that is, in principle, extractable from typical measurement scenarios. In experiments, the characterization problem of surface-breaking cracks and the more general problem of elliptical voids are studied, and a good agreement is achieved between the actual parameter values and the characterization results. The nature of the parametric manifold enables us to explain and quantify why some defects are relatively easy to characterize, whereas others are inherently challenging.
A variational approach to parametric instabilities in inhomogeneous plasmas
Energy Technology Data Exchange (ETDEWEB)
Afeyan, B.B.
1993-12-31
A variational principle is constructed for the pump strength of a three-wave parametric instability in a spatially nonuniform medium. Using this expression together with appropriate trial functions, analytic estimates of the growth rate of the most unstable mode of a given parametric instability may be calculated. The usefullness of the variational method is first demonstrated on the Rosenbluth model problem with a power-law phase-mismatch, followed by a treatment of the Liu, Rosenbluth, and White sidescattering model equation. Two particular instabilities which are of interest in laser fusion and laser-plasma interaction experiments are treated next. These are Stimulated Raman Scattering and Two-Plasmon Decay. Various incidence and scattering geometries, and different density profiles are considered. Previously known results are reproduced in a unified manner and extended to cases where the usual local-expansion techniques do not apply. In particular, using the variational approach, the growth rate of the Two-Plasmon Decay instability occurring at or anywhere below the apex of a parabolic density profile is obtained for the first time. Similarly, Stimulated Raman Scattering from a density extremum at or anywhere below quarter critical, and for all scattering angles from backscattering to sidescattering inclusively is considered for the first time. The limit where the Two-Plasmon Decay and Stimulated Raman Scattering instabilities merge and become indistinguishable is also treated.
Parametric Characterization of TES Detectors Under DC Bias
Chiao, Meng P.; Smith, Stephen James; Kilbourne, Caroline A.; Adams, Joseph S.; Bandler, Simon R.; Betancourt-Martinez, Gabriele L.; Chervenak, James A.; Datesman, Aaron M.; Eckart, Megan E.; Ewin, Audrey J.;
2016-01-01
The X-ray integrated field unit (X-IFU) in European Space Agency's (ESA's) Athena mission will be the first high-resolution X-ray spectrometer in space using a large-format transition-edge sensor microcalorimeter array. Motivated by optimization of detector performance for X-IFU, we have conducted an extensive campaign of parametric characterization on transition-edge sensor (TES) detectors with nominal geometries and physical properties in order to establish sensitivity trends relative to magnetic field, dc bias on detectors, operating temperature, and to improve our understanding of detector behavior relative to its fundamental properties such as thermal conductivity, heat capacity, and transition temperature. These results were used for validation of a simple linear detector model in which a small perturbation can be introduced to one or multiple parameters to estimate the error budget for X-IFU. We will show here results of our parametric characterization of TES detectors and briefly discuss the comparison with the TES model.
Pump to signal noise transfer in parametric fiber amplifiers
DEFF Research Database (Denmark)
Lund-Hansen, Toke; Rottwitt, Karsten; Peucheret, Christophe
2010-01-01
Fiber optic parametric amplifiers have been suggested due to their potential low spontaneous emission. However, by nature the parametric amplifier only work in a forward pumped configuration, which result in transfer of relative intensity noise in the pump to the signal.......Fiber optic parametric amplifiers have been suggested due to their potential low spontaneous emission. However, by nature the parametric amplifier only work in a forward pumped configuration, which result in transfer of relative intensity noise in the pump to the signal....
Hyperbolic and semi-parametric models in finance
Bingham, N. H.; Kiesel, Rüdiger
2001-02-01
The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.
Fault detection and isolation in systems with parametric faults
DEFF Research Database (Denmark)
Stoustrup, Jakob; Niemann, Hans Henrik
1999-01-01
The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated...
Parametric Audio Based Decoder and Music Synthesizer for Mobile Applications
Oomen, A.W.J.; Szczerba, M.Z.; Therssen, D.
2011-01-01
This paper reviews parametric audio coders and discusses novel technologies introduced in a low-complexity, low-power consumption audiodecoder and music synthesizer platform developed by the authors. Thedecoder uses parametric coding scheme based on the MPEG-4 Parametric Audio standard. In order to
Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene
2017-11-01
-enhancing lesion (CEL) and a 1 cm shell of surrounding peri-tumoral tissue were performed. Prediction using tumor volume metrics was also investigated. Leave-one-out cross validation (LOOCV) was used in combination with permutation testing to assess preliminary predictive efficacy and estimate statistically robust P-values. The predictive endpoint was overall survival (OS) greater than or equal to the median OS of 18.2 months. Single-parameter PRM and multi-parametric response maps (MPRMs) were generated for each patient and used to predict OS via the LOOCV. Tumor volume metrics (P ≥ 0.071 ± 0.01) and single-parameter PRM analyses (P ≥ 0.170 ± 0.01) were not found to be predictive of OS within this study. MPRM analysis of the peri-tumoral region but not the CEL was found to be predictive of OS with a classification sensitivity, specificity and accuracy of 80%, 100%, and 89%, respectively (P = 0.001 ± 0.01). The feasibility of a generalized MPRM analysis framework was demonstrated with improved prediction of overall survival compared to the original single-parameter method when applied to a glioblastoma dataset. The proposed algorithm takes the spatial heterogeneity in multi-parametric response into consideration and enables visualization. MPRM analysis of peri-tumoral regions was shown to have predictive potential supporting further investigation of a larger glioblastoma dataset. © 2017 American Association of Physicists in Medicine.
Parametric Study Of Window Frame Geometry
DEFF Research Database (Denmark)
Zajas, Jan Jakub; Heiselberg, Per
2013-01-01
This paper describes a parametric study on window frame geometry with the goal of designing frames with very good thermal properties. Three different parametric frame models are introduced, deseribed by a number of variables. In the first part of the study, a process of sensitivity analysis...... is conducted to determine which of the parameters describing the frame have the highest impact on its thermal performance. Afterwards, an optimization process is conducted on each frame in order to optimize the design with regard to three objectives: minimizing the thermal transmittance, maxim izing the net...... energy gain factor and minimizing the material use. Since the objectives contradiet each other, it was found that it is not possible to identifY a single solution that satisfies all these goals. lnstead, a compromise between the objectives has to be found....
Parametric structural modeling of insect wings
International Nuclear Information System (INIS)
Mengesha, T E; Vallance, R R; Barraja, M; Mittal, R
2009-01-01
Insects produce thrust and lift forces via coupled fluid-structure interactions that bend and twist their compliant wings during flapping cycles. Insight into this fluid-structure interaction is achieved with numerical modeling techniques such as coupled finite element analysis and computational fluid dynamics, but these methods require accurate and validated structural models of insect wings. Structural models of insect wings depend principally on the shape, dimensions and material properties of the veins and membrane cells. This paper describes a method for parametric modeling of wing geometry using digital images and demonstrates the use of the geometric models in constructing three-dimensional finite element (FE) models and simple reduced-order models. The FE models are more complete and accurate than previously reported models since they accurately represent the topology of the vein network, as well as the shape and dimensions of the veins and membrane cells. The methods are demonstrated by developing a parametric structural model of a cicada forewing.
Casas-Ibarra parametrization and leptogenesis
International Nuclear Information System (INIS)
Xing Zhizhong
2010-01-01
The Casas-Ibarra parametrization is a description of the Dirac neutrino mass matrix M D in terms of the neutrino mixing matrix V, an orthogonal matrix O and the diagonal mass matrices of light and heavy Majorana neutrinos in the type-I seesaw mechanism. Because M D + M D is apparently independent of V but dependent on O in this parametrization, a number of authors have claimed that unflavored leptogenesis has nothing to do with CP violation at low energies. Here we question this logic by clarifying the physical meaning of O. We establish a clear relationship between O and the observable quantities, and find that O does depend on V. We show that both unflavored leptogenesis and flavored leptogenesis have no direct connection with low-energy CP violation. (authors)
Rayleigh-type parametric chemical oscillation
Energy Technology Data Exchange (ETDEWEB)
Ghosh, Shyamolina; Ray, Deb Shankar, E-mail: pcdsr@iacs.res.in [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032 (India)
2015-09-28
We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.
Rayleigh-type parametric chemical oscillation.
Ghosh, Shyamolina; Ray, Deb Shankar
2015-09-28
We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.
Parametric instability in GEO 600 interferometer
International Nuclear Information System (INIS)
Gurkovsky, A.G.; Vyatchanin, S.P.
2007-01-01
We present analysis of undesirable effect of parametric instability in signal recycled GEO 600 interferometer. The basis for this effect is provided by excitation of additional (Stokes) optical mode, having frequency ω 1 , and mirror elastic mode, having frequency ω m , when the optical energy stored in the main FP cavity mode, having frequency ω 0 , exceeds a certain threshold and detuning Δ=ω 0 -ω 1 -ω m is small. We discuss the potential of observing parametric instability and its precursors in GEO 600 interferometer. This approach provides the best option to get familiar with this phenomenon, to develop experimental methods to depress it and to test the effectiveness of these methods in situ
Parametric Immunization in Bond Portfolio Management
Bravo, Jorge; Fonseca, José
2012-01-01
In this paper, we evaluate the relative immunization performance of the multifactor parametric interest rate risk model based on the Nelson-Siegel-Svensson specification of the yield curve with that of standard benchmark investment strategies, using European Central Bank yield curve data in the period between January 3, 2005 and December 31, 2011. In addition, we examine the role of portfolio design in the success of immunization strategies, particularly the role of the maturit...
Parametric study of laser photovoltaic energy converters
Walker, G. H.; Heinbockel, J. H.
1987-01-01
Photovoltaic converters are of interest for converting laser power to electrical power in a space-based laser power system. This paper describes a model for photovoltaic laser converters and the application of this model to a neodymium laser silicon photovoltaic converter system. A parametric study which defines the sensitivity of the photovoltaic parameters is described. An optimized silicon photovoltaic converter has an efficiency greater than 50 percent for 1000 W/sq cm of neodymium laser radiation.
Acoustic parametric pumping of spin waves
Keshtgar, Hedyeh; Zareyan, Malek; Bauer, Gerrit E. W.
2014-11-01
Recent experiments demonstrated generation of spin currents by ultrasound. We can understand this acoustically induced spin pumping in terms of the coupling between magnetization and lattice waves. Here we study the parametric excitation of magnetization by longitudinal acoustic waves and calculate the acoustic threshold power. The induced magnetization dynamics can be detected by the spin pumping into an adjacent normal metal that displays the inverse spin Hall effect.
Acoustic parametric pumping of spin waves
Keshtgar, Hedyeh; Zareyan, Malek; Bauer, Gerrit E. W.
2013-01-01
Recent experiments demonstrated generation of spin currents by ultrasound. We can understand this acoustically induced spin pumping in terms of the coupling between magnetization and lattice waves. Here we study the parametric excitation of magnetization by longitudinal acoustic waves and calculate the acoustic threshold power. The induced magnetization dynamics can be detected by the spin pumping into an adjacent normal metal that displays the inverse spin Hall effect.
Parametric motivation bases of floranimic nomination
Directory of Open Access Journals (Sweden)
Olga P. Ryabko
2016-09-01
Full Text Available The period of further development in the cognitive theory of nomination has been extensive in recent years. Our research has been concentrated on the formation of conceptual foundations in cognitive theory of flora nomination. The macrofield of flora namings embraces three microfields: parametric, pragmatic and locative-temporal ones. They determine motivation processes in cognitive theory of flora nomination, i.e., the presentation of systematic qualities in flora namings in the English language. The description and characterization of such qualities presupposes the existence of their taxonomic organization and methodology criteria, both general and practical ones. Flora namings on the phenomenological level are considered to be the products of naöve-cognitive consciousness of language speakers. They are determined, from the one hand, by the external perceptive adaptations (parametric nomination and, from the other hand, by practical needs (pure pragmatic nomination and local-temporal nomination. In this article we have concentrated on the complex parametric motivated basis of flora nomination. It is presented by a number of qualities, firstly, by dominative qualities («form», «appearance and manner of growth», «color», secondly, by peripheral qualities («odour», «taste», «size» and, finally, by minor qualities («sound», «weight», «genger». In the structure of complex parametric nomination the only one conerete qualitative element from the whole combination of qualities becomes the leading one. The cultural-archetypal dominant element determines. In each concrete situation, the choice of preferable prototypal motivated quality.
Multidimensional Scaling Visualization using Parametric Similarity Indices
Machado, J. A. Tenreiro; Lopes, António M.; Galhano, A.M.
2015-01-01
In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, an...
Supercritical nonlinear parametric dynamics of Timoshenko microbeams
Farokhi, Hamed; Ghayesh, Mergen H.
2018-06-01
The nonlinear supercritical parametric dynamics of a Timoshenko microbeam subject to an axial harmonic excitation force is examined theoretically, by means of different numerical techniques, and employing a high-dimensional analysis. The time-variant axial load is assumed to consist of a mean value along with harmonic fluctuations. In terms of modelling, a continuous expression for the elastic potential energy of the system is developed based on the modified couple stress theory, taking into account small-size effects; the kinetic energy of the system is also modelled as a continuous function of the displacement field. Hamilton's principle is employed to balance the energies and to obtain the continuous model of the system. Employing the Galerkin scheme along with an assumed-mode technique, the energy terms are reduced, yielding a second-order reduced-order model with finite number of degrees of freedom. A transformation is carried out to convert the second-order reduced-order model into a double-dimensional first order one. A bifurcation analysis is performed for the system in the absence of the axial load fluctuations. Moreover, a mean value for the axial load is selected in the supercritical range, and the principal parametric resonant response, due to the time-variant component of the axial load, is obtained - as opposed to transversely excited systems, for parametrically excited system (such as our problem here), the nonlinear resonance occurs in the vicinity of twice any natural frequency of the linear system; this is accomplished via use of the pseudo-arclength continuation technique, a direct time integration, an eigenvalue analysis, and the Floquet theory for stability. The natural frequencies of the system prior to and beyond buckling are also determined. Moreover, the effect of different system parameters on the nonlinear supercritical parametric dynamics of the system is analysed, with special consideration to the effect of the length-scale parameter.
Quantum theory of novel parametric devices
International Nuclear Information System (INIS)
Drummond, P.D.; Reid, M.D.; Dechoum, K.; Chaturvedi, S.; Olsen, M.; Kheruntsyan, K.; Bradley, A.
2005-01-01
While the parametric amplifier is a widely used and important source of entangled and squeezed photons, there are many possible ways to investigate the physics of intracavity parametric devices. Novel quantum theory of parametric devices in this talk will cover several new types of unconventional devices, including the following topics:- Critical intracavity paramp - We calculate intrinsic limits to entanglement of a quantum paramp, caused by nonlinear effects originating in phase noise of the pump. - Degenerate planar paramp - We obtain universal quantum critical fluctuations in a planar paramp device by mapping to the equations of magnetic Lifshitz points Nondegenerate planar paramp - The Mermin-Wagner theorem is used to demonstrate that there is no phase transition in the case of a nondegenerate planar device - Coupled channel paramp - A robust and novel integrated entanglement source can be generated using type I waveguides coupled inside a cavity to generate spatial entanglement - Cascade paramps - This possible 'GHZ-type' source is obtained by cascading successive down conversion crystals inside the same cavity, giving two thresholds Parallel paramps - Tripartite entanglement can be generated if three intracavity paramp crystals are operated in parallel, each idler mode acting as a signal for the next. Finally, we briefly treat the relevant experimental developments. (author)
Parametric Architecture in the Urban Space
Januszkiewicz, Krystyna; Kowalski, Karol G.
2017-10-01
The paper deals with the parametric architecture which is trying to introduce a new spatial language in the context for urban tissue that correspond to the artistic consciousness and the attitude of information and digital technologies era. The first part of the paper defines the main features of parametric architecture (such as: folding, continuity and curvilinearity) which are are characteristic of the new style of named the “parametricism”. This architecture is a strong emphasis on geometry, materiality, feasibility and sustainability, what emerges is an explicit agenda promoting material ornamentation, spatial spectacle and formal theatricality. The second part presents result of case study, especially parametric public use buildings, within the tissue of city. The analyzed objects are: The Sage Gateshead (1998-2004) in Gateshead, Kunsthaus in Graz (2000-2003), the Weltstadthaus (2003-2005) in Cologne, The Golden Terraces in Warsaw (2000-2007), the Metropol Parasol in Seville (2005-2011) the King Cross Station (2005-2012) in London, the headquarters of the Pathé Foundation (2006-2014) in Paris. Each of the enumerated examples shows a diverse approach to designing in the urban space, which reflect the age of digital technologies and the information society. In conclusion emphasizes, that new concept of the spatialization of architecture is the equivalent of the democratization of the political system, the liberalization of the economy, among other examples.
Sgr A* Emission Parametrizations from GRMHD Simulations
Anantua, Richard; Ressler, Sean; Quataert, Eliot
2018-06-01
Galactic Center emission near the vicinity of the central black hole, Sagittarius (Sgr) A*, is modeled using parametrizations involving the electron temperature, which is found from general relativistic magnetohydrodynamic (GRMHD) simulations to be highest in the disk-outflow corona. Jet-motivated prescriptions generalizing equipartition of particle and magnetic energies, e.g., by scaling relativistic electron energy density to powers of the magnetic field strength, are also introduced. GRMHD jet (or outflow)/accretion disk/black hole (JAB) simulation postprocessing codes IBOTHROS and GRMONTY are employed in the calculation of images and spectra. Various parametric models reproduce spectral and morphological features, such as the sub-mm spectral bump in electron temperature models and asymmetric photon rings in equipartition-based models. The Event Horizon Telescope (EHT) will provide unprecedentedly high-resolution 230+ GHz observations of the "shadow" around Sgr A*'s supermassive black hole, which the synthetic models presented here will reverse-engineer. Both electron temperature and equipartition-based models can be constructed to be compatible with EHT size constraints for the emitting region of Sgr A*. This program sets the groundwork for devising a unified emission parametrization flexible enough to model disk, corona and outflow/jet regions with a small set of parameters including electron heating fraction and plasma beta.