• Journal of the Korean Data and Information Science Society
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• 제11권1호
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• pp.103-110
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• 2000

Suppose that there is a population of hidden objects of which the total number N is unknown. From such data, we derive second-order approximations to the stopping time with fixed proportional accuracy.

• 대한수학회보
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• 제51권5호
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• pp.1539-1549
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• 2014

The closed spacelike hypersurfaces with higher order mean curvature is discussed in a de Sitter space. The hypersurface is proved stable if and only if it is totally umbilical.

• Journal of applied mathematics & informatics
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• 제28권3_4호
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• pp.877-882
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• 2010

In this paper, a third-order three-point boundary value problem on time scales is considered. We establish criteria for the existence of a solution and a positive solution by using the Leray-Schauder fixed point theorem. An example is also given to illustrate our results.

• Journal of the Korean Statistical Society
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• 제34권4호
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• pp.273-280
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• 2005

In this paper we introduce an estimator of the second order parameter characterizing the tail behavior of probability distributions and prove its consistency.

• 대한전자공학회논문지SP
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• 제37권5호
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• pp.94-104
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• 2000

차량 충돌 경보용 레이더 시스템의 개발에 있어 표적 추적의 정확도와 신뢰도는 매우 중요한 요소이다. 여러 표적을 동시에 추적할 때 중요한 것은 표적과 측정치와의 데이터 연관(data association) 이며, 부적절한 측정치가 어느 표적과 연관되면 그 표적은 트랙을 벗어나 추적능력을 잃어버릴 수 있고 심지어 다른 표적의 추적에도 영향을 줄 수 있다 지금까지 발표된 대부분의 데이터 연관 필터들은 근접하여 이동하는 표적들의 경우 이와 같은 문제점을 보여왔다 따라서, 현재 개발되고 있는 많은 알고리즘들은 이러한 데이터 연 관 문제의 해결에 초점을 맞추고 있다 본 논문에서는 순서통계(order statistics)를 이용한 새로운 다중 표적의 데이터 연관 방법에 대하여 서술하고자 한다 OSPDA와 OSJPDA로 불리는 제안된 방법은 각각 PDA 필터 또는 JPDA 필터에서 계산된 연관 확률을 이용하며 이 연관 확률을 결정 논리(dicision logic)에 의한 가중치로 함수화 하여 표적과 측정치 사이에 최적 혹은 최적 근처의(near optimal) 데이터 연관이 가능하도록 한 것이다 시뮬레이션 결과를 통해, 제안한 방법은 기존의 NN 필터, PDA 필터, 그리고 JPDA 필터의 성능과 비교 분석되었으며, 그 결과 제안한 OSPDA, OSJPDA 필터는 PDA, JPDA 필터보다 추적 정확도에 대해 각각 약 18%, 19% 이상으로 성능이 향상됨을 확인하였다 제안한 방법은 CAN을 통해 차량 엔진 등의 ECU와 통신하도록 개발된 DSP 보드를 이용하여 구현되었다

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.177-183
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• 1997

A data-adaptive order selection procedure is proposed for local polynomial nonparametric regression. For each given polynomial order, bias and variance are estimated and the adaptive polynomial order that has the smallest estimated mean squared error is selected locally at each location point. To estimate mean squared error, empirical bias estimate of Ruppert (1995) and local polynomial variance estimate of Ruppert, Wand, Wand, Holst and Hossjer (1995) are used. Since the proposed method does not require fitting polynomial model of order higher than the model order, it is simpler than the order selection method proposed by Fan and Gijbels (1995b).

• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.271-282
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• 1993

Unit root test for temporally aggregated first order autoregressive process is considered. The temporal aggregate of fist order autoregression is an autoregressive moving average of order (1,1) with moving average parameter being function of the autoregressive parameter. One-step Gauss-Newton estimators are proposed and are shown to have the same limiting distribution as the ordinary least squares estimator for unit root when complete observations are available. A Monte-Carlo simulation shows that the temporal aggregation have no effect on the size. The power of the suggested test are nearly the same as the powers of the test based on complete observations.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.907-910
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• 2001

In this paper, we address a new time delay estimation method using third-order statistics and subband adaptive filtering to improve the accuracy of target detection for acoustic backscattered signals in a noise interference environment. Each reference and primary signals are decorrelated using the multiresolution analysis framework through a M-band discrete wavelet transform(M-DWT). Then noise effect can be reduced. Here, time delays are estimated iteratively in each subband using two different adaptation mechanisms that minimize the mean squared error (MSE) between the references and primary signal. More specifically, third-order cumulants and projection cross-correlation(PCC) criterion are utilized to achieve an effective SNR improvement for the time delay estimation.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제5권1호
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• pp.55-78
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• 2001

Given the anisotropic Poisson equation $-{\nabla}{\cdot}{\mathcal{K}}{\nabla}p=f$, one can convert it into a system of two first order PDEs: the Darcy law for the flux $u=-{\mathcal{K}{\nabla}p$ and conservation of mass ${\nabla}{\cdot}u=f$. A very natural mixed finite volume method for this system is to seek the pressure in the nonconforming P1 space and the Darcy velocity in the lowest order Raviart-Thomas space. The equations for these variables are obtained by integrating the two first order systems over the triangular volumes. In this paper we show that such a method is really a standard finite element method with local recovery of the flux in disguise. As a consequence, we compare two approaches in analyzing finite volume methods (FVM) and shed light on the proper way of analyzing non co-volume type of FVM. Numerical results for Dirichlet and Neumann problems are included.

• Journal of Mechanical Science and Technology
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• 제17권12호
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• pp.1867-1875
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• 2003

In exhaust pipes of automotive engines, the pulsating pressure waves are composed of fundamental frequency and high order harmonics. The nonlinearities in the exhaust pipe is caused by their interactions. The error between prediction and measurement is induced by the nonlinearities. We can not explain this phenomenon using linear acoustics theory. So power spectrum, which is used in linear theory, is not useful. This paper is concerned with the development of useful engineering techniques to detect and analyze nonlinearity in exhaust pipe of automotive engines. The study of higher order statistics has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment (skewness) of a signal over frequency and as such is blind to symmetric nonlinearities. The phenomenon of quadratic phase coupling (QPC) can be analyzed by the bicoherence function. Finally the application of these techniques to data from actual exhaust pipe systems is performed.