• Title/Summary/Keyword: Order Statistics

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3D Model Reconstruction Algorithm Using a Focus Measure Based on Higher Order Statistics (고차 통계 초점 척도를 이용한 3D 모델 복원 알고리즘)

  • Lee, Joo-Hyun;Yoon, Hyeon-Ju;Han, Kyu-Phil
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.11-18
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    • 2013
  • This paper presents a SFF(shape from focus) algorithm using a new focus measure based on higher order statistics for the exact depth estimation. Since conventional SFF-based 3D depth reconstruction algorithms used SML(sum of modified Laplacian) as the focus measure, their performance is strongly depended on the image characteristics. These are efficient only for the rich texture and well focused images. Therefore, this paper adopts a new focus measure using HOS(higher order statistics), in order to extract the focus value for relatively poor texture and focused images. The initial best focus area map is generated by the measure. Thereafter, the area refinement, thinning, and corner detection methods are successively applied for the extraction of the locally best focus points. Finally, a 3D model from the carefully selected points is reconstructed by Delaunay triangulation.

MIXED TYPE SECOND-ORDER DUALITY WITH SUPPORT FUNCTION

  • Husain, I.;Ahmed, A.;Masoodi, Mashoob
    • Journal of applied mathematics & informatics
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    • v.27 no.5_6
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    • pp.1381-1395
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    • 2009
  • Mixed type second order dual to the non-differentiable problem containing support functions is formulated and duality theorems are proved under generalized second order convexity conditions. It is pointed out that the mixed type duality results already reported in the literature are the special cases of our results.

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A Note on the Covariance Matrix of Order Statistics of Standard normal Observations

  • Lee, Hak-Myung
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.285-290
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    • 2000
  • We noted a property of a stationary distribution on the matrix C, which is the covariance matrix of order statistics of standard normal distribution That is the sup norm of th powers of C is ee' divided by its dimension. The matrix C can be taken as a transition probability matrix in an acyclic Markov chain.

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Dual Sliding Statistics Switching Median Filter for the Removal of Low Level Random-Valued Impulse Noise

  • Suid, Mohd Helmi;Jusof, M F.M.;Ahmad, Mohd Ashraf
    • Journal of Electrical Engineering and Technology
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    • v.13 no.3
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    • pp.1383-1391
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    • 2018
  • A new nonlinear filtering algorithm for effectively denoising images corrupted by the random-valued impulse noise, called dual sliding statistics switching median (DSSSM) filter is presented in this paper. The proposed DSSSM filter is made up of two subunits; i.e. Impulse noise detection and noise filtering. Initially, the impulse noise detection stage of DSSSM algorithm begins by processing the statistics of a localized detection window in sorted order and non-sorted order, simultaneously. Next, the median of absolute difference (MAD) obtained from both sorted statistics and non-sorted statistics will be further processed in order to classify any possible noise pixels. Subsequently, the filtering stage will replace the detected noise pixels with the estimated median value of the surrounding pixels. In addition, fuzzy based local information is used in the filtering stage to help the filter preserves the edges and details. Extensive simulations results conducted on gray scale images indicate that the DSSSM filter performs significantly better than a number of well-known impulse noise filters existing in literature in terms of noise suppression and detail preservation; with as much as 30% impulse noise corruption rate. Finally, this DSSSM filter is algorithmically simple and suitable to be implemented for electronic imaging products.

Effects of Order Misspecification on Unit Root Tests

  • Shin, Dong-Wan;Lee, Yoon-Dong
    • Journal of the Korean Statistical Society
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    • v.26 no.2
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    • pp.171-180
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    • 1997
  • Effects of order misspecification on statistical behavior of unit root tests are studied. We derive the limiting distributions of the Dickey-Fuller test statistics whose numerators are of the form c .int. W dW + .kappa. where W is a standard Brownian motion on [0, 1] and c is a real number. The term .kappa. is a major consequence of order misspecification and its explict expression is derived. Based on an analysis of .kappa., effects of order misspecification on unit root tests for AR(2), ARMA(1, 1), and AR(3) models are investigated.

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A New Formula to Predict the Exact Detection Probability of a Generalized Order Statistics CFAR Detector for a Correlated Rayleigh Target

  • Kim, Chang-Joo
    • ETRI Journal
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    • v.16 no.2
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    • pp.15-25
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    • 1994
  • In this paper we present a new formula which can predict the exact detection probability of a generalized order statistics (GOS) constant false alarm rate (DFAR) detector for a partially correlated Rayleigh target model (0 < $ \rho$< 1) in a closed form, where $\rho$ is the correlation coefficient between returned pulses. By simply substituting a set of specific coefficient into the derived formula, one can obtain the detection probability of any kind of CFAR detector. Detectors may include the order statistics CFAR detector, the censored mean level detector, and the trimmed mean CFAR detector, but are not necessarily restricted to them. The numerical result for the first order Markov correlation model as applied to some of the detectors shows that as $\rho$ increases from zero to one, higher signal-to-noise ratio is required to achieve the same detection probability.

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Second-order statistics of natural frequencies of smart laminated composite plates with random material properties

  • Singh, B.N.;Umrao, Atul;Shukla, K.K.;Vyas, N.
    • Smart Structures and Systems
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    • v.4 no.1
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    • pp.19-34
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    • 2008
  • Nowadays developments in the field of laminated composite structures with piezoelectric have attracted significant attention of researchers due to their wide range of applications in engineering such as sensors, actuators, vibration suppression, shape control, noise attenuation and precision positioning. Due to large number of parameters associated with its manufacturing and fabrication, composite structures with piezoelectric display a considerable amount of uncertainty in their material properties. The present work investigates the effect of the uncertainty on the free vibration response of piezoelectric laminated composite plate. The lamina material properties have been modeled as independent random variables for accurate prediction of the system behavior. System equations have been derived using higher order shear deformation theory. A finite element method in conjunction with Monte Carlo simulation is employed to obtain the secondorder statistics of the natural frequencies. Typical results are presented for all edges simply supported piezoelectric laminated composite plates to show the influence of scattering in material properties on the second order statistics of the natural frequencies. The results have been compared with those available in literature.

자력복구 적응 채널등화기를 위한 Run and Go 알고리즘 (Run and Go Algorithm for Blind Equalization)

  • Chung, Won-Zoo
    • Journal of IKEEE
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    • v.10 no.1 s.18
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    • pp.62-68
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    • 2006
  • In this paper, we propose an adaptation strategy for blind equalizers, which combines a blind algorithm based on high order statistics and the decision directed LMS algorithm. In contrast to 'Stop-and-Go' algorithm, where adaptation is stopped for unreliable signals, the proposed algorithm applies high order statistics (HOS) blind algorithm to the unreliable signals and applies DD-LMS for the reliable signals. The proposed algorithm, named 'Run-and-Go' algorithm, inherits minimum MSE performance of DD-LMS and acquisition ability of blind algorithms. Furthermore, by updating the reliable signal region according to signal quality in each iteration, the convergence speed and acquisition ability is further improved.

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Plotting positions and approximating first two moments of order statistics for Gumbel distribution: estimating quantiles of wind speed

  • Hong, H.P.;Li, S.H.
    • Wind and Structures
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    • v.19 no.4
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    • pp.371-387
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    • 2014
  • Probability plotting positions are popular and used as the basis for distribution fitting and for inspecting the quality of the fit because of its simplicity. The plotting positions that lead to excellent approximation to the mean of the order statistics should be used if the objective of the fitting is to estimate quantiles. Since the mean depends on the sample size and is not amenable for simple to use closed form solution, many plotting positions have been presented in the literature, including a new plotting position that is derived based on the weighted least-squares method. In this study, the accuracy of using the new plotting position to fit the Gumbel distribution for estimating quantiles is assessed. Also, plotting positions derived by fitting the mean of the order statistics for all ranks is proposed, and an approximation to the covariance of the order statistics for the Gumbel (and Weibull) variate is given. Relative bias and root-mean-square-error of the estimated quantiles by using the proposed plotting position are shown. The use of the proposed plotting position to estimate the quantiles of annual maximum wind speed is illustrated.