• 제목/요약/키워드: Probability density functions

검색결과 241건 처리시간 0.028초

Analysis of structural dynamic reliability based on the probability density evolution method

  • Fang, Yongfeng;Chen, Jianjun;Tee, Kong Fah
    • Structural Engineering and Mechanics
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    • 제45권2호
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    • pp.201-209
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    • 2013
  • A new dynamic reliability analysis of structure under repeated random loads is proposed in this paper. The proposed method is developed based on the idea that the probability density of several times random loads can be derived from the probability density of single-time random load. The reliability prediction models of structure based on time responses under several times random loads with and without strength degradation are obtained by using the stress-strength interference theory and probability density evolution method. The resulting differential equations in the prediction models can be solved by using the forward finite difference method. Then, the probability density functions of strength redundancy of the structures can be obtained. Finally, the structural dynamic reliability can be calculated using integral method. The efficiency of the proposed method is demonstrated numerically through a speed reducer. The results have shown that the proposed method is practicable, feasible and gives reasonably accurate prediction.

경사제 피복재의 안정성 해석을 위한 동력학적 신뢰성 모형 (Dynamic Reliability Model for Stability Analysis of Armor Units on Rubble-Mound Breakwater)

  • 이철응
    • 산업기술연구
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    • 제21권B호
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    • pp.163-174
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    • 2001
  • A dynamic reliability model for analyzing the stability of armor units on rubble-mound breakwater is mathematically developed by using Hudson's formula and definition of single-failure mode. The probability density functions of resistance and loading functions are defined properly, the related parameters to those probability density functions are also estimated straightforwardly by the first-order analysis. It is found that probabilities of failure for the stability of armor units on rubble-mound breakwater are continuously increased as the service periods are elapsed, because of the occurrence of repeated loading of random magnitude by which the resistance may be deteriorated. In particular, the factor of safety is incorporated into the dynamic reliability model in order to evaluate the probability of failure as a function of factor of safety. It may thus be possible to take some informations for optimal design as well as managements and repairs of armor units on rubble-mound breakwater from the dynamic reliability analyses.

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컨볼루션 기법을 이용한 영역이 제한된 비정규 확률문제의 신뢰성 해석 (Reliability Analysis of the Non-normal Probability Problem for Limited Area using Convolution Technique)

  • 이현만;김태곤;최원;서교;이정재
    • 한국농공학회논문집
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    • 제55권5호
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    • pp.49-58
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    • 2013
  • Appropriate random variables and probability density functions based on statistical analysis should be defined to execute reliability analysis. Most studies have focused on only normal distributions or assumed that the variables showing non-normal characteristics follow the normal distributions. In this study, the reliability problem with non-normal probability distribution was dealt with using the convolution method in the case that the integration domains of variables are limited to a finite range. The results were compared with the traditional method (linear transformation of normal distribution) and Monte Carlo simulation method to verify that the application was in good agreement with the characteristics of probability density functions with peak shapes. However it was observed that the reproducibility was slightly reduced down in the tail parts of density function.

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.

두꺼운 꼬리를 갖는 연속 확률분포들의 꼬리 확률에 관하여 (On Tail Probabilities of Continuous Probability Distributions with Heavy Tails)

  • 윤석훈
    • 응용통계연구
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    • 제26권5호
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    • pp.759-766
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    • 2013
  • 본 논문에서는 두꺼운 꼬리를 갖는 확률분포들의 여러 부류에 대해서 살펴본다. 주어진 하나의 확률분포가 이들 중 어떤 부류에 속하는 지를 알려면 해당 분포의 꼬리 확률에 대한 (점근) 표현식을 알아야만 한다. 그러나 대다수의 절대 연속 확률분포들은 분포함수가 아닌 확률밀도함수로 명시되기 때문에 통상적으로 이들의 꼬리 확률에 대한 표현식을 얻는 작업은 그리 쉬운 일이 아니다. 본 논문에서는 이러한 경우 확률밀도함수만을 이용하여 꼬리 확률에 대한 점근 표현식을 쉽게 얻을 수 있는 하나의 방법을 제안한다. 또한 제안한 방법을 설명하기 위하여 몇가지 예를 첨부한다.

Joint Probability Density Functions for Direct-Detection Optical Receivers

  • Lee, Jae Seung
    • Journal of the Optical Society of Korea
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    • 제18권2호
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    • pp.124-128
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    • 2014
  • We derive joint probability density functions (JPDFs) for two adjacent data from direct-detection optical receivers in dense wavelength-division multiplexing systems. We show that the decision using two data per bit can increase the receiver sensitivity compared with the conventional decision. Our JPDFs can be used for software-defined optical receivers enhancing the receiver sensitivities for intensity-modulated channels.

Online Probability Density Estimation of Nonstationary Random Signal using Dynamic Bayesian Networks

  • Cho, Hyun-Cheol;Fadali, M. Sami;Lee, Kwon-Soon
    • International Journal of Control, Automation, and Systems
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    • 제6권1호
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    • pp.109-118
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    • 2008
  • We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

추계론적 유한요소해석에서의 확률밀도함수 사용과 수렴치 (Application of Probability Density Function in SFEM and Corresponding Limit Value)

  • 노혁천
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2006년도 정기 학술대회 논문집
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    • pp.857-864
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    • 2006
  • Due to the difficulties in numerical generation of random fields that satisfy not only the probabilistic distribution but the spectral characteristics as well. it is relatively hard to find an exact response variability of a structural response with a specific random field which has its features in the spatial and spectral domains. In this study. focusing on the fact that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for in-plane and plate bending structures. In this procedure, the probability density function is used directly resulting in a semi-exact solution for the random field in the state of random variable. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density functions.

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확률론적 이론에 기초한 동적 통행시간 모형 정립 (Development of Probability Theory based Dynamic Travel Time Models)

  • 양철수
    • 대한교통학회지
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    • 제29권3호
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    • pp.83-91
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    • 2011
  • 이 논문은 확률론적인 방법을 이용하여 동적 통행시간(dynamic travel time) 모형을 도출한다. 동적 통행시간 모형은 차량의 통행시간은 도로 공간상에서의 교통흐름 분포에 따라, 또는 통행구간 출발점에서 시간에 대한 교통흐름의 분포에 따라 결정된다고 가정하여 얻어진다. 이 모형들에서 교통흐름의 분포가 차량의 통행시간에 미치는 정도를 나타내는 확률밀도함수(probability density function)는 여러 가지 형태의 도입될 수 있으나 지수분포를 따른다고 가정한다.