• Title/Summary/Keyword: Statistical estimation

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Fast Multiple Reference Frame Selection Method for Motion Estimation and Compensation in Video Coding (동영상 부호화의 움직임 추정 및 보상을 위한 고속 다중 참조 프레임 선택 기법)

  • Kim, Jae-Hoon;Kim, Myoung-Jin;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.11C
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    • pp.1066-1072
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    • 2007
  • In this paper, we propose a fast multiple reference frame selection method for motion estimation and compensation in video coding. Reference frames selected as an optimal reference frame by variable block sizes motion estimation have the statistical characteristic that was based on block size. Using the statistical characteristic, reference frames for smaller block size motion estimation can be selected from reference frame which was decided as an optimal one for the upper layer block size. Simulation results show that the proposal method decreased the computations about 60%. Nevertheless, PSNR and bit rate were almost same as the performances of original H.264 multiple reference motion estimation.

Development of Statistical Model for Line Width Estimation in Laser Micro Material Processing Using Optical Sensor (레이저 미세 가공 공정에서 광센서를 이용한 선폭 예측을 위한 통계적 모델의 개발)

  • Park Young Whan;Rhee Sehun
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.7 s.172
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    • pp.27-37
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    • 2005
  • Direct writing technology on the silicon wafer surface is used to reduce the size of the chip as the miniature trend in electronic circuit. In order to improve the productivity and efficiency, the real time quality estimation is very important in each semiconductor process. In laser marking, marking quality is determined by readability which is dependant on the contrast of surface, the line width, and the melting depth. Many researchers have tried to find theoretical and numerical estimation models fur groove geometry. However, these models are limited to be applied to the real system. In this study, the estimation system for the line width during the laser marking was proposed by process monitoring method. The light intensity emitted by plasma which is produced when irradiating the laser to the silicon wafer was measured using the optical sensor. Because the laser marking is too fast to measure with external sensor, we build up the coaxial monitoring system. Analysis for the correlation between the acquired signals and the line width according to the change of laser power was carried out. Also, we developed the models enabling the estimation of line width of the laser marking through the statistical regression models and may see that their estimating performances were excellent.

ComputationalAalgorithm for the MINQUE and its Dispersion Matrix

  • Huh, Moon Y.
    • Journal of the Korean Statistical Society
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    • v.10
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    • pp.91-96
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    • 1981
  • The development of Minimum Norm Quadratic Unbiased Estimation (MINQUE) has introduced a unified approach for the estimation of variance components in general linear models. The computational problem has been studied by Liu and Senturia (1977) and Goodnight (1978, setting a-priori values to 0). This paper further simplifies the computation and gives efficient and compact computational algorithm for the MINQUE and dispersion matrix in general linear random model.

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Regularity of Maximum Likelihood Estimation for ARCH Regression Model with Lagged Dependent Variables

  • Hwang, Sun Y.
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.9-16
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    • 2000
  • This article addresses the problem of maximum likelihood estimation in ARCH regression with lagged dependent variables. Some topics in asymptotics of the model such as uniform expansion of likelihood function and construction of a class of MLE are discussed, and the regularity property of MLE is obtained. The error process here is possibly non-Gaussian.

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Piecewise Linear Fuzzy Random Variables and their Statistical Application

  • WATANABE, Norio;IMAIZUMI, Tadashi
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.696-700
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    • 1998
  • Fuzzy random variables with piecewise linear membership functions are introduced from a practical viewpoint. The estimation of the expected values of these fuzzy random variables is also discussed and statistical application is denonstratied by using a real data set.

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Adaptive Estimation of Monotone Functions

  • Kang, Yung-Gyung
    • Journal of the Korean Statistical Society
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    • v.27 no.4
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    • pp.485-494
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    • 1998
  • In the white noise model we construct an adaptive estimate for f(0) for a decreasing function f. We also show that the maximum mean square error of this estimate attains the same rate as the minimax risk simultaneously over a range of Lipschitz classes of order less than or equal to one.

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Algorithm for the Constrained Chebyshev Estimation in Linear Regression

  • Kim, Bu-yong
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.47-54
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    • 2000
  • This article is concerned with the algorithm for the Chebyshev estimation with/without linear equality and/or inequality constraints. The algorithm employs a linear scaling transformation scheme to reduce the computational burden which is induced when the data set is quite large. The convergence of the proposed algorithm is proved. And the updating and orthogonal decomposition techniques are considered to improve the computational efficiency and numerical stability.

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Robust Estimation and Outlier Detection

  • Myung Geun Kim
    • Communications for Statistical Applications and Methods
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    • v.1 no.1
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    • pp.33-40
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    • 1994
  • The conditional expectation of a random variable in a multivariate normal random vector is a multiple linear regression on its predecessors. Using this fact, the least median of squares estimation method developed in a multiple linear regression is adapted to a multivariate data to identify influential observations. The resulting method clearly detect outliers and it avoids the masking effect.

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ON HELLINGER CONSISTENT DENSITY ESTIMATION

  • Nicoleris, Theodoros;Walker, Stephen-G.
    • Journal of the Korean Statistical Society
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    • v.32 no.3
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    • pp.261-270
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    • 2003
  • This paper introduces a new density estimator which is Hellinger consistent under a simple condition. A number of issues are discussed, such as extension to Kullback-Leibler consistency, robustness, the Bayes version of the estimator and the maximum likelihood case. An illustration is presented.