• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.8
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• pp.797-803
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• 2002

In this paper we derive the probability density function of the phase error of the received signal over Rician fading channel and verify its propriety as the probability density function using the zeroth moment. In general, for the error probability over fading channel we compute the error probability in the first place when it is only AWGN, and then we get the final result by averaging the first result and the probability density function of the corresponding fading channel. In this paper, however, we compute the error probability by double integration after the probability density function over fading channel is computed.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.5
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• pp.607-617
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• 1998

Comparisons of joint probability density distribution obtained from the raw data of measured droplet sizes and velocities in a transient diesel fuel spray with computed joint probability density function were made. Simultaneous droplet sizes and velocities were obtained using PDPA. Mathematical probability density functions which can fit the experimental distributions were extracted using the principle of maximum likelihood. Through the statistical process of functions, mean droplet diameters, non-dimensional mass, momentum and kinetic energy were estimated and compared with the experimental ones. A joint log-hyperbolic density function presents quite well the experimental joint density distribution which were extracted from experimental data.

• East Asian mathematical journal
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• v.39 no.5
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• pp.537-547
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• 2023

In this paper, we introduce the optimal approximation by a Gaussian function for a probability density function. We show that the approximation can be obtained by solving a non-linear system of parameters of Gaussian function. Then, to understand the non-normality of the empirical distributions observed in financial markets, we consider the nearly Gaussian function that consists of an optimally approximated Gaussian function and a small periodically oscillating density function. We show that, depending on the parameters of the oscillation, the nearly Gaussian functions can have fairly thick heavy tails.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.4
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• pp.1039-1049
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• 1994

The intermitternt and transient fuel spray have been investigated from the simultaneous measurement of droplet sizes and velocities by using Phase/Doppler Particle Analyzer(PDPA). Measurement have been done on the spray axis and at the edge of the spray near nozzle at various gas-to-liquid density ratios(.rho./sub g//.rho./sub l/) that ranges from those found in free atmospheric jets to conditions typical of diesel engines. Probability density distributions of the droplet size and velocity were obtained from raw data and mathematical probability density functions which can fit the experimental distribations were extracted using the principle of maximum likelihood. In the near nozzle region on the spray axis, droplet sizes ranged from the lower limit of the measurement system to the order of nozzle diameter for all (.rho./sub g/ /.rho./sub l/) and droplet sizes tended to be small on the spray edge. At the edge of spray, average droplet velocity peaked during needle opening and needle closing. The rms intensity is greatly incresed as the radial distance from the nozzle is increased. The probability density function which can best fit the physical breakage process such as breakup of fuel drops is exponecially decreasing log-hypebolic function with 4 parameters.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1338-1341
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• 2002

The Weibull probability density function and the Rayleigh function are compared by analyzing the relations of the capacity factors which are compared the actual wind speed frequency curve with which are modelled using the probability density functions with different mean wind speeds. For this analysis, the wind speed means of arithmetic, root mean square, cubic mean cuberoot, and standard deviations are computed from the measured wind speed data of a specific site and the coefficients of probability density functions are calculated. The capacity factors for Vestas 850[kW] wind turbine are calculated and analyzed. The results shows that the wind speed frequency curve by Rayleigh function is more close to the actual curve than by Weibull function. The more the wind speed frequency curve is close to the actual one, the more the capacity factors become large values.

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.345-353
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• 2008

In order to design storage-based non-point source management facilities, the aspect of statistical features of the entire precipitation time series should be considered since non-point source pollutions are delivered by continuous rainfall runoffs. The 3-parameter mixed exponential probability density function instead of traditional single-parameter exponential probability density function is applied to represent the probabilistic features of long-term precipitation time series and model urban stormwater runoff. Finally, probability density functions of water quality control basin overflow are derived under two extreme intial conditions. The 31-year continuous precipitation time series recorded in Busan are analyzed to show that the 3-parameter mixed exponential probability density function gives better resolution.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.415-428
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• 1999

In this paper, we study the saddlepoint approximations for the ratio of two independent sequences of random variables. In Section 2, we review the saddlepoint approximation to the probability density function. In section 3, we derive an saddlepoint approximation formular for the tail probability by following Daniels'(1987) method. In Section 4, we represent a numerical example which shows that the errors are small even for small sample size.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.1-49
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• 2001

The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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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.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.