• 제목/요약/키워드: Probability Density function

검색결과 785건 처리시간 0.026초

Theoretical prediction on thickness distribution of cement paste among neighboring aggregates in concrete

  • Chen, Huisu;Sluys, Lambertus Johannes;Stroeven, Piet;Sun, Wei
    • Computers and Concrete
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    • 제8권2호
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    • pp.163-176
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    • 2011
  • By virtue of chord-length density function from the field of statistical physics, this paper introduced a quantitative approach to estimate the distribution of cement paste thickness between aggregates in concrete. Dynamics mixing method based on molecular dynamics was employed to generate one model structure, then image analysis algorithm was used to obtain the distribution of thickness of cement paste in model structure for the purpose of verification. By comparison of probability density curves and cumulative probability curves of the cement paste thickness among neighboring aggregates, it is found that the theoretical results are consistent with the simulation. Furthermore, for the model mortar and concrete mixtures with practical volume fraction of Fuller-type aggregate, this analytical formula was employed to predict the influence of aggregate volume fraction and aggregate fineness. And evolution of its mean values were also investigated with the variation of volume fraction of aggregate as well as the fineness of aggregates in model mortars and concretes.

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.

Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation

  • Yee, Jaeyong;Park, Taesung;Park, Mira
    • Genomics & Informatics
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    • 제20권2호
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    • pp.17.1-17.11
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    • 2022
  • Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

다축 하중 구조물의 동적 피로수명 예측 (The Prediction of Dynamic Fatigue Life of Multi-axial Loaded Structure)

  • 윤문영;김경호;박장수;부광석;김흥섭
    • 한국정밀공학회지
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    • 제30권2호
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    • pp.231-235
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    • 2013
  • The purpose of this paper is to compare with estimation of equivalent fatigue load in time domain and frequency domain and estimate the fatigue life of structure with multi-axial vibration loading. The fatigue analysis with two methods is implemented with various signals like random, sinusoidal signals. Also an equivalent fatigue life estimated by rainflow cycle counting in time domain is compared with results estimated with probability density function of each signal in frequency domain. In case of frequency domain, equivalent fatigue life can estimate through Dirlik's method with probability density function. And the work proposed in this paper compared the fatigue damage accumulated under uni-axial loading to that induced by multi-axial loading. The comparison is preformed for a simple cantilever beam, which is exposed to vibrations of several directions. For verification of estimation performance of fatigue life, results are compared to those of FEM analysis (ANSYS).

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.

  • PDF

Stochastic ship roll motion via path integral method

  • Cottone, G.;Paola, M. Di;Ibrahim, R.;Pirrotta, A.;Santoro, R.
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제2권3호
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    • pp.119-126
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    • 2010
  • The response of ship roll oscillation under random ice impulsive loads modeled by Poisson arrival process is very important in studying the safety of ships navigation in cold regions. Under both external and parametric random excitations the evolution of the probability density function of roll motion is evaluated using the path integral (PI) approach. The PI method relies on the Chapman-Kolmogorov equation, which governs the response transition probability density functions at two close intervals of time. Once the response probability density function at an early close time is specified, its value at later close time can be evaluated. The PI method is first demonstrated via simple dynamical models and then applied for ship roll dynamics under random impulsive white noise excitation.

Euclidian Distance Minimization of Probability Density Functions for Blind Equalization

  • Kim, Nam-Yong
    • Journal of Communications and Networks
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    • 제12권5호
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    • pp.399-405
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    • 2010
  • Blind equalization techniques have been used in broadcast and multipoint communications. In this paper, two criteria of minimizing Euclidian distance between two probability density functions (PDFs) for adaptive blind equalizers are presented. For PDF calculation, Parzen window estimator is used. One criterion is to use a set of randomly generated desired symbols at the receiver so that PDF of the generated symbols matches that of the transmitted symbols. The second method is to use a set of Dirac delta functions in place of the PDF of the transmitted symbols. From the simulation results, the proposed methods significantly outperform the constant modulus algorithm in multipath channel environments.

Dynamical Behavior of Autoassociative Memory Performaing Novelty Filtering

  • Ko, Hanseok
    • The Journal of the Acoustical Society of Korea
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    • 제17권4E호
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    • pp.3-10
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    • 1998
  • This paper concerns the dynamical behavior, in probabilistic sense, of a feedforward neural network performing auto association for novelty. Networks of retinotopic topology having a one-to-one correspondence between and output units can be readily trained using back-propagation algorithm, to perform autoassociative mappings. A novelty filter is obtained by subtracting the network output from the input vector. Then the presentation of a "familiar" pattern tends to evoke a null response ; but any anomalous component is enhanced. Such a behavior exhibits a promising feature for enhancement of weak signals in additive noise. As an analysis of the novelty filtering, this paper shows that the probability density function of the weigh converges to Gaussian when the input time series is statistically characterized by nonsymmetrical probability density functions. After output units are locally linearized, the recursive relation for updating the weight of the neural network is converted into a first-order random differential equation. Based on this equation it is shown that the probability density function of the weight satisfies the Fokker-Planck equation. By solving the Fokker-Planck equation, it is found that the weight is Gaussian distributed with time dependent mean and variance.

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Estimation of Probability Density Functions of Damage Parameter for Valve Leakage Detection in Reciprocating Pump Used in Nuclear Power Plants

  • Lee, Jong Kyeom;Kim, Tae Yun;Kim, Hyun Su;Chai, Jang-Bom;Lee, Jin Woo
    • Nuclear Engineering and Technology
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    • 제48권5호
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    • pp.1280-1290
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    • 2016
  • This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

Naval ship's susceptibility assessment by the probabilistic density function

  • Kim, Kwang Sik;Hwang, Se Yun;Lee, Jang Hyun
    • Journal of Computational Design and Engineering
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    • 제1권4호
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    • pp.266-271
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    • 2014
  • The survivability of the naval ship is the capability of a warship to avoid or withstand a hostile environment. The survivability of the naval ship assessed by three categories (susceptibility, vulnerability and recoverability). The magnitude of susceptibility of a warship encountering with threat is dependent upon the attributes of detection equipment and weapon system. In this paper, as a part of a naval ship's survivability analysis, an assessment process model for the ship's susceptibility analysis technique is developed. Naval ship's survivability emphasizing the susceptibility is assessed by the probability of detection, and the probability of hit. Considering the radar cross section (RCS), the assessment procedure for the susceptibility is described. It's emphasizing the simplified calculation model based on the probability density function for probability of hit. Assuming the probability of hit given a both single-hit and multiple-hit, the susceptibility is accessed for a RCS and the hit probability for a rectangular target is applied for a given threat.