• 한국전자파학회논문지
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• 제13권7호
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• pp.679-686
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• 2002

본 논문에서는 PSK 변조 신호에 대한 위상 잡음 성능 특성을 무한 급수로 전개하여 위상 잡음 분포 함수인 Tikhonov 함수와 Gaussian 함수에 대한 오율 특성을 평가하였으며, 위상 잡음에 의한 성능 손실 분석을 통하여 Tikhonov 함수와 Gaussian 함수에 의한 위상 잡음 영향이 일치하는 복원 반송파 신호대 잡음비 범위를 고찰하였다. 그리고, 주파수 변조 신호의 변조 지수와 위상 잡음의 상관 정의에 의해 1/f$^2$특성을 갖는 위상 잡음 신호를 발생하였으며, 발생된 위상 잡음 신호를 디지털 위성통신시스템 수신기에 적용하여 측정한 위상 잡음에 의한 성능 손실과 위상 잡음 분포 함수에 의해 분석된 성능 열화를 평가하였다

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.246-249
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• 2009

Due to the additive white Gaussian noise (AWGN), images are often corrupted. In recent days, Bayesian estimation techniques to recover noisy images in the wavelet domain have been studied. The probability density function (PDF) of an image in wavelet domain can be described using highly-sharp head and long-tailed shapes. If a priori probability density function having the above properties would be applied well adaptively, better results could be obtained. There were some frequently proposed PDFs such as Gaussian, Laplace distributions, and so on. These functions model the wavelet coefficients satisfactorily and have its own of characteristics. In this paper, mixture distributions of Gaussian and Laplace distribution are proposed, which attempt to corporate these distributions' merits. Such mixture model will be used to remove the noise in images by adopting Maximum a Posteriori (MAP) estimation method. With respect to visual quality, numerical performance and computational complexity, the proposed technique gained better results.

• 한국정밀공학회지
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• 제11권1호
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• pp.192-200
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• 1994

The methodology of a simple probabilistic fatigue crack under random loading is proposed. Using the crack closure concept, the crack opening stress is assumed to be constant during random loading. The loading history was analyzed to determine the probability density functions, probability distribution functions and other related parameters for the probabilistic fatigue crack growth analysis. Fatigue crack growth using the exisiting available data was predicted by the proposed probabilistic analysis and compared with experimental data.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• 한국인터넷방송통신학회논문지
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• 제17권6호
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• pp.59-68
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• 2017

무선 통신시스템에서 Random 과정을 해석적으로 표현할 수 있으며 적당한 확률분포를 구할 수 있다. 감쇄지수함수 확률분포에 의한 가우스, 레일레이, 나카가미 확률분포를 쉽게 유도했으며 시뮬레이션을 그림으로 보인다. 시간의 개념을 포함한 파형의 집합에 의한 확률적 표현이 Random과정(or Stochasic Process)인데 이를 무선환경의 조건에 따라 유도한다. 또한 가시거리 통신과 비가시거리 채널환경을 Rayleigh와 Rician 채널로 구체적인 예를 SISO, MIMO 환경에서 보인다. 또한, 본 논문에서 채널이 송신 블록 동안 일정하고 연속적인 송신 블록 사이에서 독립적으로 변하는 블록 페이딩 채널 모델을 가정함으로써 i.i.d 채널을 갖는 높은 SNR 영역에서 더 나은 성능을 얻을 수 있다는 동기를 부여한다. 이러한 변환을 실현하기 위한 알고리즘은 크로네 커 MIMO 채널에 적용 할 수 있다.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.251-268
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• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.

• Wind and Structures
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• 제25권3호
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• pp.261-282
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• 2017

The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.243-255
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• 1996

The number of neutron signals from a neutral particle beam(NPB) at the detector, without any errors, obeys Poisson distribution, Under two assumptions that NPB scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of signals becomes a Poisson-power function distribution. In this paper, we show that the error rate in simple hypothesis testing for the limiting Poisson-power function distribution is not zero. That is, the limit of ${\alpha}+{\beta}$ is zero when Poisson parameter$\kappa\rightarro\infty$, but this limit is not zero (i.e., $\rho\ell$>0)for the Poisson-power function distribution. We also give optimal decision algorithms for a specified error rate.

• 한국지반공학회지:지반
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• 제1권2호
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• pp.41-54
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• 1985

비교적 얕은 깊이에서 터널을 착굴하거나 개착을 하늘 경우, 열변지반에 침하 및 수평이동 등의 변위가 발생하게 된다. 이러한 변위는 주변 구조물의 안정에 큰 영향을 미치며, 심한 경우 주변 구조물이 파괴되는 상태에 까지 이른다. 인구가 밀집된 대도시에 지하철을 시공할 경우, 주변 문화재, 고층건물, 상하수도관, 가스관 등의 안정을 지하철 설계시 고려하여야 하므로 터널굴착에 따른 지반변위의 예측과 자세한 침하의 원인이 규명되어야 할 필요가 있다. 본 연구에서는 지반 침하량 및 침하발생 영역을 예상하거나 침하요인을 파악하기 위하여 부산지하철 NATM회간의 지표면 침하, 지표면 수평변위, 지중침하, 천단침하 들에 관한 측정 분석이 이루어졌다. 그 결과, 횡방향 지표면 침하는 Gaussian normal probability curve, 종방향 지표면 심하하는 cumulative Gaussian probability curve로서 해석이 가능하다는 것과 가인버어트의 조기폐합이 침하량 감소에 큰 영향을 미친다는 것을 알 수 있었다.

• Geomechanics and Engineering
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• 제36권6호
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• pp.601-618
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• 2024

The joint probability distribution of uncertain geomechanical parameters of geotechnical strata is a crucial aspect in constructing the reliability functional function for roof structures. However, due to the limited number of on-site exploration and test data samples, it is challenging to conduct a scientifically reliable analysis of roof geotechnical strata. This study proposes a Copula method based on small sample exploration and test data to construct the intensity characteristics of roof geotechnical strata. Firstly, the theory of multidimensional copula is systematically introduced, especially the construction of four-dimensional Gaussian copula. Secondly, data from measurements of 176 groups of geomechanical parameters of roof geotechnical strata in 31 coal mines in China are collected. The goodness of fit and simulation error of the four-dimensional Gaussian Copula constructed using the Pearson method, Kendall method, and Spearman methods are analyzed. Finally, the fitting effects of positive and negative correlation coefficients under different copula functions are discussed respectively. The results demonstrate that the established multidimensional Gaussian Copula joint distribution model can scientifically represent the uncertainty of geomechanical parameters in roof geotechnical strata. It provides an important theoretical basis for the study of reliability functional functions for roof structures. Different construction methods for multidimensional Gaussian Copula yield varying simulation effects. The Kendall method exhibits the best fit in constructing correlations of geotechnical parameters. For the bivariate Copula fitting ability of uncertain parameters in roof geotechnical strata, when the correlation is strong, Gaussian Copula demonstrates the best fit, and other Copula functions also show remarkable fitting ability in the region of fixed correlation parameters. The research results can offer valuable reference for the stability analysis of roof geotechnical engineering.