• 한국정보처리학회논문지
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• 제7권8호
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• pp.2565-2574
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• 2000

오차확산법은 연속계조 영상을 중간조 영상으로 생성시 우수한 재현성을 보인다. 그러나 표시오차의 전력스펙트럼 분석에서 경계정보의 재현성이 다소 떨어지는 특성을 보인다. 이를 개선하기 위해 원영상의 현재화소와 로컬 평균간의 차이정보를 이용하는 경계강조 오차확산법을 제안한다. 제안한 기법은 원영상이 현재화소와 로컬 평균과의 차이정보 및 이를 활용하는 필터의 가중치 함수로 구성된다. 첫째, 원영상의 차이정보는 현재 화소와 이의 인접화소(5x5)의 로컬 평균과의 차이이다. 둘째, 필터의 가중치 함수는 차이정보의 크기를 포함하는 함수와 이의 부호로 구성된다. 제안한 기법을 적용한 중간조 영상은 경계가 강조되어 시각적으로 선명한 결과를 보인다. 환상 평균 전력 스펙트럼 밀도를 이용한 표시오차, 경계상관도 및 로컬 평균 일치도의 평가함수로 제안한 경계강조 오차확산법과 기존의 경계강조 오차확산법의 특성을 비교한다.

• 지구물리
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• 제5권2호
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• pp.131-142
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• 2002

일반적으로 지자기 전달함수는 관측치와 예측치의 차이를 최소화하는 관점에서 해가 추정된다. 오차의 구조가 가우스 분포를 따르면 최소자승 추정이 최적의 추정이지만, 그렇지 않은 경우 전달 함수 추정을 심각하게 왜곡시킬 수 있으므로 오차 구조에 대한 정보가 요구된다. 본 연구에서는 Q-Q plot을 이용한 오차 구조으 검증을 통하여 실제 오차 구조에 대한 정보를 획득하였고 가우스 분포 가정을 벗어나는 오차 구조에 대해 외치(outlier)에 의한 영향을 최소로 하며 해를 추정하는 로버스트 추정(regression M-estimate)을 적용하였다. 오차가 가우스 분포를 따르는 경우, 최소자승 추정과 로버스트 추정은 유사한 결과를 나타내나, 오차가 가우스 분포를 벗어나는 경우 로버스트 추정이 최소자승 추정보다 부드러운 결과를 나타냄을 확인하였다.

• 정보학연구
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• 제8권3호
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• pp.1-10
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• 2005

Cosine and Sine function is widely used for the arithmetic, translation, object drawing, Simulation and etc. of Computer Graphics in Natural Science and Engineering. In general, Cordic Algorithm is effective method since it has relatively small size and simple architecture on trigonometric function generation. However profitably it has those merits, the problem of operation speed is occurred. In graphic display system, the operation result of object drawing is quantized and has the condition that is satisfied with rms error less than 1. So in this paper, the proposed generator is composed of partition operation at each ${\pi}/4$ and basic Cosine, Sine function generator in the range of $0{\sim}{\pi}/4$ using the lower order of Tayler's series in an acceptable error range, that enlarge the range of $0{\sim}2{\pi}$ according to a definition of the trigonometric function for the purpose of having a high speed Cosine, Sine function generation. And, division operator using code partition for divisor three is proposed, the proposed function generator has high speed operation, but it has the problems in the other application parts with accurate results, is need to increase the speed of the multiplication.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.33-55
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• 2007

The economic world is full of patterns, many of which exert a profound influence over society and business. One of the most contentious is the distribution of wealth. Way back in 1897, an Italian engineer-turned-economist named Vilfredo Pareto discovered a pattern in the distribution of wealth that appears to be every bit as universal as the laws of thermodynamics or chemistry. The present paper proposes some Bayes estimators of shape parameter of Pareto income distribution in censored sampling. Asymmetric LINEX loss function has been considered to study the effects of overestimation and underestimation. For the prior distribution of the parameter involved a number of priors including one and two-parameter exponential, truncated Erlang and doubly truncated gamma have been contemplated to express the belief of the experimenter s/he has regarding the parameter. The estimators thus obtained have been compared theoretically and empirically with the corresponding estimators under squared error loss function, some of which were reported by Bhattacharya et al. (1999).

• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.323-330
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• 1989

Large bias errors which occur during a numerical evaluation of the Rayleigh's integral is not due to the replicated source problem but due to the coincidence of singularities of the Green's function and the sampling points in Fourier domain. We found that there is no replicated source problem in evaluating the Rayleigh's integral numerically by the reason of the periodic assumption of the input sequence in Dn or by the periodic sampling of the Green's function in the Fourier domain. The wrap around error is not due to an overlap of the individual adjacent sources but berallse of the undersampling of the Green's function in the frequency domain. The replicated and overlApped one is inverse Fourier transformed Green's function rather than the source function.

• Communications for Statistical Applications and Methods
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• 제18권5호
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• pp.667-674
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• 2011

A recent trend in software reliability engineering accounts for the coverage growth behavior during testing. The coverage growth function (representing the coverage growth behavior) has become an essential component of software reliability models. Application of a coverage growth function requires the estimation of the coverage growth function. This paper considers the problem of estimating the coverage growth function. The existing maximum likelihood method is reviewed and corrected. A method of minimizing the sum of squares of the standardized prediction error is proposed for situations where the maximum likelihood method is not applicable.

• 한국경영과학회지
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• 제30권1호
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• pp.95-104
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• 2005

A desirability function approach to a multiresponse problem is proposed considering process parameter fluctuation which may amplify the variance of response. It is called POE (propagation of error), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. In order to obtain more robust process parameter setting, a new desirability function is proposed by considering POE as well as distance-to-target of response and response variance. The proposed method is illustrated using a rubber product case in Ribeiro et al. (2000).

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.885-898
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• 2012

In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.

• 한국자동차공학회논문집
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• 제3권5호
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• pp.1-9
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• 1995

The purpose of this study is to develop a computer simulation program for analyzing load transmission characteristics of a helical gear system in design stage. In this analysis, the rotational delay, load distribution, root stress, and contact area are investigated. That is, the influence function of deflection is obtained by finite element analysis and the influence function of approach and gear tooth error are considered. Load distribution, rotational delay, and contact area are calculated by solving load-deflection equation which includes these influence functions and tooth error, and the influence function of the bending moment is obtained by finite element analysis. The root stress is calculated by the load distribution and the influence function of the bending moment. The results of the simulation are cross-checked through a specially designed experimental set-up.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.849-860
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• 1999

This paper addresses the issue of estimating regression function with errors in variables using wavelets. We adopt a nonparametric approach in assuming that the regression function has no specific parametric form, To account for errors in covariates deconvolution is involved in the construction of a new class of linear wavelet estimators. using the wavelet characterization of Besov spaces the question of regression estimation with Besov constraint can be reduced to a problem in a space of sequences. Rates of convergence are studied over Besov function classes $B_{spq}$ using $L_2$ error measure. It is shown that the rates of convergence depend on the smoothness s of the regression function and the decay rate of characteristic function of the contaminating error.