• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 하계종합학술대회 논문집
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• pp.207-210
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• 1989

In probabilistic production costing simulation, cumulant method is widely used. But this method have some limitations in some cases. To overcome these serious drawbacks, MONA(Mixture of Normals Approximation) method was proposed. The MONA method uses multiple normals to represent the Equivalent Load Duration Curve. In this paper we investigate the MONA's characteristics by comparing other methods and derive the efficient formulae for MONA. Also, we propose the fundamental algorithm for Mixture of Cumulants Approximation(MOCA) which is the general case of MONA.

• 대한기계학회논문집
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• 제19권3호
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• pp.697-704
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• 1995

The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents the stochastic model of a nonlinear dynamic system with uncertain parameters under nonstationary stochastic inputs. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method and the second moment equation is numerically evaluated by stochastic process closure method, 4th cumulant neglect closure method and Runge-Kutta method. But the first and the second moment equations are coupled each other, so this equations are approximately evaluated by a iterative method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.630-635
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• 1998

The objective of this paper is to propose a new efficient technique for the estimation of time-delay parameters using wavelet theory and third-order cumulants, yielding good performance even in the case of low SNR. In particular, band-limited non-Gaussian signals with non-zero skewness and spatially correlated Gaussian noises are considered here. The approach is based on the fact that the effects of spatially correlated Gaussian noises on time-delay estimation can be reduced by using the projection sequences (based on the redundant wavelet decomposition) of given measurements in the higher-order cumulant domain. Finally, the performance of the proposed approach is demonstrated using simulations.

• 응용통계연구
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• 제27권5호
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• pp.809-818
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• 2014

다변량 왜정규분포는 다변량 정규분포를 포함하는 분포로 최근 많은 응용분야에서 활용되고 있다. 본 논문에서는 다변량 왜정규분포를 기반으로 하는 선형결합통계량의 분포함수에 대한 안장점근사를 다루었다. 이는 단변량 왜정규분포 기반 표본평균에 대한 Na와 Yu (2013)의 결과를 선형결합 및 다변량의 경우로 확장한 것이다. 모의실험과 실제자료분석을 통해 제안된 근사법의 유용성과 정확도를 확인하였다.

• 응용통계연구
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• 제18권1호
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• pp.183-196
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• 2005

본 논문에서는 다변량 정규분포하에서 비동차(non-homogeneous) 이차형식의 분포 함수에 대한 안장점근사법을 다루었다. 이는 Kuonen (1999)의 동차(homogeneous) 이차형식에 대한 안장점근사를 비동차의 경우로 확장한 것이다. 안장점근사의 적용을 위해 비동차 이차형식의 누율생성함수 및 관련 성질들을 유도하였다. 모의실험을 통해 안장점근사의 정도가 매우 뛰어남을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.267-276
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• 2012

Bagai et al. (1989) proposed a distribution-free test for stochastic ordering in the competing risk model, and recently Murakami (2009) utilized a standard saddlepoint approximation to provide tail probabilities for the Bagai statistic under finite sample sizes. In the present paper, we consider the Gaussian-polynomial approximation proposed in Ha and Provost (2007) and compare it to the saddlepoint approximation in terms of approximating the percentiles of the Bagai statistic. We make numerical comparisons of these approximations for moderate sample sizes as was done in Murakami (2009). From the numerical results, it was observed that the Gaussianpolynomial approximation provides comparable or greater accuracy in the tail probabilities than the saddlepoint approximation. Unlike saddlepoint approximation, the Gaussian-polynomial approximation provides a simple explicit representation of the approximated density function. We also discuss the details of computations.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.839-845
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• 2003

This paper introduces multichannel blind source separation (BSS) and multichannel blind deconvolution (MBD) based on higher order statistics of signals from convolutive mixtures. In particular, we are concerned with the case that the number of inputs is the same as the number of outputs. Simulations for two input two output cases are carried out and their performances are assessed. One of the major applications of those sequential algorithms (BSS and MBD) is demonstrated through the fault signal detection from only a single measurement of rotating machine, which offers a certain degree of practicability in the engineering field such as machine health monitoring or condition monitoring.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.28-30
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• 2003

Probabilistic Load Flow(PLF) solution based on the method of moments is used for security assessment of bus voltages in power systems. Bus voltages, line currents, line admittances, generated real and reactive power, and bus loads are treated as complex random variables. These complex random variables are known in terms of probability density functions(PDF). Also, expressions for the convolutions of complex random variables in terms of moments and cumulants have been derived. Proposed PLF solution using the method of moments is fast, because the process of convolution of various complex random variables is performed in moment and cumulant domain. Therefore, the method is applied to security assessment of power systems in this paper. Finally, system operator also can be used information of security assessment to improve reliability of power systems.

• 응용통계연구
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• 제29권4호
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• pp.571-579
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• 2016

이차형식 통계량의 분포함수에 대한 연구는 주로 다변량 정규분포의 가정하에서 진행되어 왔다. 최근 다변량 정규분포를 포함하는 다변량 왜정규분포에 대한 연구가 활발하다. 본 논문에서는 다변량 왜정규분포의 가정하에서 이차형식 통계량의 분포함수에 대한 근사를 다루었다. 근사의 방법으로는 소표본에서도 정확도가 뛰어난 근사법으로 알려진 안장점근사를 사용하였으며, 모의실험을 통해 그 정도를 확인하였다.

• 한국정밀공학회지
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• 제12권4호
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• pp.127-134
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• 1995

The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents a generalized stochastic model of dynamic system subjected to bot external and parametric nonstationary stochastic input. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method. But the second moment equation is founded to constitute an infinite coupled set of differential equations, so this equations are numerically evaluated by cumulant neglect closure method and Runge-Kutta method. Finally the accuracy of the present method is verified by Monte Carlo simulation.