• 한국통신학회논문지
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• 제32권11C호
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• pp.1066-1072
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• 2007

본 논문에서는 동영상 부호화 방식의 움직임 추정을 위한 고속 다중 참조 프레임 선택 기법에 대해 제안한다. 움직임 추정을 위해 다중 프레임을 참조하는 H.264 동영상 부호화 방식의 경우, 블록별로 선택된 최적의 참조 프레임들은 일정한 상관관계를 유지하는 특성이 존재한다. 제안 방식은 이러한 통계적 특성을 이용하여, 임의의 블록 크기의 움직임 추정 모드에서 선택된 최적의 참조 프레임 정보를 이용하여 하위 블록 크기의 움직임 추정 모드에서 사용할 참조 프레임을 예측한다. 실험 결과를 통해 5개의 참조 프레임 사용을 기준으로 제안하는 기법을 사용하였을 때, 움직임 추정에 소요되는 시간은 가용한 모든 참조 프레임에 대해 움직임 추정을 수행하는 방식 대비 평균 60% 감소되었으며, PSNR 및 발생 비트율 측면에서 거의 동일한 성능을 유지함을 확인할 수 있었다.

• 한국정밀공학회지
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• 제22권7호
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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.

• Journal of the Korean Statistical Society
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• 제10권
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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.

• Journal of the Korean Statistical Society
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• 제29권1호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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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.

• Journal of the Korean Statistical Society
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• 제27권4호
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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.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.603-611
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• 1996

In this article we consider a sequential procedure for the fixed width interval estimation of the means of two mutually independent linear processes. It is shown that the proposed stopping rule is asymptotically efficient as in iid samples (cf. Robbins, Simons and Starr(l967)).

• Communications for Statistical Applications and Methods
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• 제7권1호
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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.

• Communications for Statistical Applications and Methods
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• 제1권1호
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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.

• Journal of the Korean Statistical Society
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• 제32권3호
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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.