• 제목/요약/키워드: Gaussian Probability Density Function

검색결과 118건 처리시간 0.026초

A novel reliability analysis method based on Gaussian process classification for structures with discontinuous response

  • Zhang, Yibo;Sun, Zhili;Yan, Yutao;Yu, Zhenliang;Wang, Jian
    • Structural Engineering and Mechanics
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    • 제75권6호
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    • pp.771-784
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    • 2020
  • Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

디지털 위성통신시스템에서 위상 잡음으로 인한 성능 손실 예측 (Prediction of Performance Loss Due to Phase Noise in Digital Satellite Communication System)

  • 김영완;박동철
    • 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

복소 라플라시안 확률 밀도 함수에 기반한 음성 향상 기법 (Noisy Speech Enhancement Based on Complex Laplacian Probability Density Function)

  • 박윤식;조규행;장준혁
    • 대한전자공학회논문지SP
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    • 제44권6호
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    • pp.111-117
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    • 2007
  • 본 논문에서는 복소 라플라시안 확률밀도함수 (PDF, Probability Density Function)에 기반한 새로운 음성 향상 기법을 제시한다. 적용된 복소 라플라시안 PDF가 기존의 가우시안 PDF보다 오염된 음성 분포를 정확하게 표현한다는 것을 Goodness-of-Fit (GOF) 테스트로 확인하였고, 음성 향상 알고리즘의 음성부재확률을 위해 우도비 (LR, Likelihood Ratio)를 적용하였다. 제시된 알고리즘의 성능은 객관적 테스트에 의해 평가하였고 기존의 가우시안 PDF보다 개선된 음성 향상 결과를 나타내었다.

IMAGE DENOISING BASED ON MIXTURE DISTRIBUTIONS IN WAVELET DOMAIN

  • Bae, Byoung-Suk;Lee, Jong-In;Kang, Moon-Gi
    • 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.

  • PDF

라이시안 감쇄 채널에서의 위상오류 분포 (On the Distribution of Phase Error in the Rician Fading Channel)

  • 김민종;한영열
    • 한국전자파학회논문지
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    • 제13권8호
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    • pp.797-803
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    • 2002
  • 본 논문에서는 라이시안(Rician) 감쇄가 존재하는 채널 환경에서 협대역 잡음이 더하여진 경우에 대역 여파기를 통과한 수신신호의 위상오류에 대한 확률 밀도 함수를 유도하고 0차 모먼트가 1이 됨을 보임으로써 확률밀도 함수로서의 타당성을 검증한다. 일반적으로 감쇄 환경에서 시스템의 오류 확률은 먼저 가산성 백색 가우시안 잡음(AWGN : Additive White Gaussian Noise)만이 존재할 때의 오류 확률을 구한 후, 그 결과 식을 해당 감쇄에 대한 확률 밀도 함수로 평균을 취하여 구한다. 하지만 본 논문에서는 감쇄 환경에서의 수신 신호에 대한 위상 오류식을 구한 다음, 그 식을 한번의 이중 적분을 취함으로써 오류 확률을 구하게 된다.

Linear prediction and z-transform based CDF-mapping simulation algorithm of multivariate non-Gaussian fluctuating wind pressure

  • Jiang, Lei;Li, Chunxiang;Li, Jinhua
    • Wind and Structures
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    • 제31권6호
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    • pp.549-560
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    • 2020
  • Methods for stochastic simulation of non-Gaussian wind pressure have increasingly addressed the efficiency and accuracy contents to offer an accurate description of the extreme value estimation of the long-span and high-rise structures. This paper presents a linear prediction and z-transform (LPZ) based Cumulative distribution function (CDF) mapping algorithm for the simulation of multivariate non-Gaussian fluctuating wind pressure. The new algorithm generates realizations of non-Gaussian with prescribed marginal probability distribution function (PDF) and prescribed spectral density function (PSD). The inverse linear prediction and z-transform function (ILPZ) is deduced. LPZ is improved and applied to non-Gaussian wind pressure simulation for the first time. The new algorithm is demonstrated to be efficient, flexible, and more accurate in comparison with the FFT-based method and Hermite polynomial model method in two examples for transverse softening and longitudinal hardening non-Gaussian wind pressures.

Input Density에 대한 Compandor 특성에 관한 연구 (A Study On The Computer Characteristics For the Various Input Probability Density Function)

  • 박찬경;한영열
    • 한국통신학회:학술대회논문집
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    • 한국통신학회 1984년도 추계학술발표회논문집
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    • pp.92-95
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    • 1984
  • This paper describes the output P.D.F. of various Compandors, optimum, -law and A-law for the Gaussian and Laplacian Density as an input analog signal. Also we consider the truncated densities compensated by weighted impulse or density coefficient.

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Lagged Cross-Correlation of Probability Density Functions and Application to Blind Equalization

  • Kim, Namyong;Kwon, Ki-Hyeon;You, Young-Hwan
    • 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.

색도 영상분할을 위한 문턱치 결정방법 (Determination of threshold values for color image segmentation)

  • 이병욱
    • 한국통신학회논문지
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    • 제21권4호
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    • pp.869-875
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    • 1996
  • This paper investigates a method for dtermining a threshold value based on the probability distribution function for color image segmentation. Principal components of normalized color is nalyzed and found that there are effective color transforms for outdoor scents. We esplain the functional relationship of the treshold and the probability of a regiona detection, asuming bivarate Gaussian probability density function. Experimental results show that the probability of detection is proportional to the segmented area.

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Vessel traffic geometric probability approaches with AIS data in active shipping lane for subsea pipeline quantitative risk assessment against third-party impact

  • Tanujaya, Vincent Alvin;Tawekal, Ricky Lukman;Ilman, Eko Charnius
    • Ocean Systems Engineering
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    • 제12권3호
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    • pp.267-284
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    • 2022
  • A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.