• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.191-194
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• 2007

The paper clarifies all the noise sources of a CMOS image sensor, with which the GOCI (Geostationary Ocean Color Imager) is equipped, and analyzes their contribution to a nonlinear image sensor model. In particular, the noise PDF (Probability Density Function) is derived in terms of sensor-gain coefficients: a linear and a nonlinear gains. As a result, the relation between the noise characteristic and the sensor gains is studied.

• 한국물환경학회지
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• 제24권4호
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• pp.430-435
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• 2008

In order to design Non-point source management, the aspect of statistical features of the entire precipitation data should be focused since non-point source discharge is driven by continuous rainfall runoffs. 3-parameter mixed exponential probability density function is used to establish urban stormwater capture curve instead of previous single-parameter exponential PDF. Then, recent 10-year data in Busan are applied to establish the curve. The result shows that 3-parameter mixed PDF gives better resolution.

• 대한전자공학회논문지TC
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• 제48권8호
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• pp.1-6
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• 2011

본 논문에서는 이중 홉 증폭 후 전달(AF: Amplify-and-Forward) 릴레이 시스템에 대한 새로운 성능 분석 기법을 레일리 페이딩 채널에 대하여 제안한다. 기존의 분석 기법들에서는 S-R-D(Source-Relay-Destination) 링크의 수신 신호 대 잡음비(SNR: Signal-to-Noise Ratio)에 대한 누적 분포 함수(CDF: Cumulative Distribution Function) 혹은 확률 밀도 함수 (PDF: Probability Density Function)로부터 모멘트 발생 함수(MGF: Moment Generating Function)를 유도한 후 평균 심벌 오류율을 유도된 MGF를 이용하여 표현하였다. 본 논문에서는 기존의 분석과 다른 새로운 접근법을 제안한다. 즉, S-R(Source-Relay) 링크 및 R-D(Relay-Destination) 링크의 PDF들로부터 S-R-D 링크에 대한 MGF를 직접 유도한다. 그리고 새롭게 유도된 MGF을 기존의 연구들에서 제시한 형태와 비교 분석한다. 또한 제안된 성능분석 기법의 정확성은 모의실험을 통하여 검증한다. 이를 통하여 제안된 분석 기법이 이중 홉 증폭 후 전달 릴레이 시스템에 대한 새로운 해를 제시함을 확인한다.

• Journal of Communications and Networks
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• 제14권5호
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• pp.540-545
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• 2012

In this paper, the lagged cross-correlation of two probability density functions constructed by kernel density estimation is proposed, and by maximizing the proposed function, adaptive filtering algorithms for supervised and unsupervised training are also introduced. From the results of simulation for blind equalization applications in multipath channels with impulsive and slowly varying direct current (DC) bias noise, it is observed that Gaussian kernel of the proposed algorithm cuts out the large errors due to impulsive noise, and the output affected by the DC bias noise can be effectively controlled by the lag ${\tau}$ intrinsically embedded in the proposed function.

• Structural Engineering and Mechanics
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• 제68권4호
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• 대한금속재료학회지
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• 제46권9호
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• pp.554-562
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• 2008

The distribution and prediction interval for the misorientation angle of grain boundary at which $Cr_2N$ was precipitated during heating at $900^{\circ}C$ for $10^4$ sec were newly estimated, and followed by the estimation of mathematical and median rank methods. The probability density function of the misorientation angle can be estimated by a statistical analysis. And then the ($1-{\alpha}$)100% prediction interval of misorientation angle obtained by the estimated probability density function. If the estimated probability density function was symmetric then a prediction interval for the misorientation angle could be derived by the estimated probability density function. In the case of non-symmetric probability density function, the prediction interval could be obtained from the cumulative distribution function of the estimated probability density function. In this paper, 95, 99 and 99.73% prediction interval obtained by probability density function method and cumulative distribution function method and compared with the former results by median rank regression or mathematical method.

• 대한전자공학회논문지SP
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• 제42권1호
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• pp.51-57
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• 2005

본 논문에서는 실시간 처리론 위한 적응형 콘트라스트 조정 기법을 제안하였다. 제안된 방식은 과도한 영상의 밝기 변화를 제어하기 위하여 활률밀도함수(PDF: Probability Density Function)를 이용하였다. 또한 제안된 알고리즘은 처리된 영상에 영향을 주지 않으면서 최대 콘트라스트를 얻을 수 있었다. 하드웨어의 복잡성을 감소하기 위하여 누적분포함수(CDF: Cumulative Density Function)의 샘플 값을 이용한 선형화 방법을 이용하였다. 제안된 방식에 의한 처리 결과와 원 영상의 화질 평가를 위하여 시각적 검증과 히스토그램 편차를 도입하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.602-606
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• 2005

A systematic procedure of probability analysis for general distributions is developed based on the first four moments estimated from polynomial interpolation of the system response function and the Pearson system. The function approximation is based on a specially selected experimental region for accuracy and the number of function evaluations is taken equal to that of the unknown coefficient for efficiency. For this purpose, three error-minimizing conditions are proposed and corresponding canonical experimental regions are formed for popular probability. This approach is applied to study the stochastic properties of the performance functions of a MEMS structure, which has quite large fabrication errors compared to other structures. Especially, the vibratory micro-gyroscope is studied using the statistical moments and probability density function (PDF) of the performance function to be the difference between resonant frequencies corresponding to sensing and driving mode. The results show that it is very sensitive to the fabrication errors and that the types of PDF of each variable also affect the stochastic properties of the performance function although they have same the mean and variance.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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• pp.495-502
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• 2003

This study proposed the Probability Density Function (PDF) interpolation technique to evaluate the seismic fragility curves as a function of the return period. Seismic fragility curves have been developed as a function of seismic intensities such as peak ground acceleration, peak pound velocity, and pseudo-velocity spectrum. The return period of design earthquakes, however, can be more useful among those seismic intensity measurements, because the seismic hazard curves are generally represented with a return period of design earthquakes and the seismic design codes also require to consider the return period of design earthquake spectrum for a specific site. In this respect the PDF interpolation technique is proposed to evaluate the seismic fragility curves as a function of return period. Seismic fragility curves based on the return period are compared with ones based on the peak ground acceleration for the bridge model.

• Structural Engineering and Mechanics
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• 제25권3호
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• pp.331-345
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• 2007

Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.