• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.325-328
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• 1996

In this paper, we proposed an estimation method of a posterior probability and PDF(Probability density function) using a feed forward neural network and code books of VQ(vector quantization). In this study, We estimates a posterior probability and probability density function, which compose a new parameter with well-known Mel cepstrum and verificate the performance for the five vowels taking from syllables by NN(neural network) and PNN(probabilistic neural network). In case of new parameter, showed the best result by probabilistic neural network and recognition rates are average 83.02%.

• Journal of the Korean Society of Combustion
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• v.2 no.1
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• pp.39-51
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• 1997

A review of probability density function(PDF) methodology and direct numerical simulation for the purpose of modeling turbulent combustion are presented in this study where particular attention is focused on the modeling problem of turbulent molecular mixing term appearing in PDF transport equation. Existing mixing models results were compared to those evaluated by direct numerical simulation in a turbulent premixed medium with finite rate chemistry in which the initial scalar field is composed of pockets of partially burnt gases to simulate autoignition. Two traditional mixing models, the least mean square estimations(LMSE) and Curl#s model are examined to see their prediction capability as well as their modeling approach. Test calculations report that the stochastically based Curl#s approach, though qualitatively demonstrates some unphysical behaviors, predicts scalar evolutions which are found to be in good agreement with statistical data of direct numerical simulation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.6
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• pp.814-822
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• 1986

Flow patterns and its transitions in vertical two phase flow of air-water isothermal flow are identified objectively by void output signals and moments computed from the Probability Density Function which is associated with the statistical measurement for time average local void fractions using conductance probe. It has been shown that the probe output signals, PDF distributions and its moments are deterministic criteria of flow pattern and transition classification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.295-303
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• 2012

Clarify wind energy productivity depends on three factors: the wind probability density function(PDF), the turbine's power curve, and the air density. The wind PDF gives the probability that a variable will take on the wind speed value. Wind shear refers to the change in wind speed with height above ground. The wind speed tends to increase with the height above ground. also, Wind PDF refers to the change with height above ground. Wind analysts typically use the Weibull distribution to characterize the breadth of the distribution of wind speeds. The Weibull distribution has the two-parameter: the scale factor c and the shape factor k. We can use a linear least squares algorithm(or Ln-least method) and moment method to fit a Weibull distribution to measured wind speed data which data was located same site and different height. In this study, find that the scale factor is related to the average wind speed than the shape factor. and also different types of terrain are characterized by different the scale factor slop with height above ground. The gross turbine power output (before accounting for losses) was caculated the power curve whose corresponding air density is closest to the air density. and air desity was choose two way. one is the pressure of the International Standard Atmosphere up to an elevation, the other is the measured air pressure and temperature to calculate the air density. and then each power output was compared.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.317-320
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• 2002

In this paper, an automatic histogram specification method is proposed for image enhancement, Fuzzy membership value is adopted for the representation of image histogram. The desired PDF is automatically constructed by the fuzzy membership value. Fuzzy membership value is extracted from dark membership, bright membership function and original histogram. The effectual results are demonstrated by desired PDF which meet the image enhancement requirements. The performance and effectiveness are shown by the analysis and the resultant image in comparison with histogram equalization method.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.1
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• pp.1-7
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• 2009

Tracking and detecting targets by the M/W seeker is affected by the clutter reflecting from the earth's surface. In order to detect the look-down retreating targets, which appear in the sidelobe clutter region, in the M/W seeker of High PRF mode, it is necessary to understand statistical characteristics of the surface sidelobe clutter. Statistical analysis of sidelobe clutter is conducted for several configurations of the surface using data obtained by the CFT (Captive Flight Test) of the M/W seeker in High PRF mode. The probability density function(PDF) fitting is conducted for several configuration and conditions of the surface. PDFs and PDF parameters, which best describe statistical distribution of sidelobe clutter, are estimated.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.705-712
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• 2005

Entropy is the basic concept of information theory. It is well defined for random varibles with known probability density function(pdf). For given data with unknown pdf, entropy should be estimated. Usually, estimation of entropy is based on the approximations. In this paper, we consider a kernel based approximation and compare it to the cumulant approximation method for several distributions. Monte carlo simulation for various sample size is conducted.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.188-193
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• 2011

In this letter, we have derived another exact performance analysis for the OADF(opportunistic adaptive decode-and-forward) relay systems over Rayleigh fading channels. Based on error-events at relay nodes, the received instantaneous SNR(signal-to-noise ratio) is presented and its PDF(probability density function) is expressed as a more tractable form in which the number of summations and the length of each summation are specified. Then, exact average error rate, outage probability, and average channel capacity are obtained as general forms. Simulation results are finally presented to validate that the proposed analytical expressions can be a unified frame work covering all Rayleigh fading channel conditions. Furthermore, it is confirmed that OADF schemes can outperform the other schemes on the average error rate, outage probability, and average channel capacity.

• ETRI Journal
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• v.32 no.3
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• pp.464-467
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• 2010

In this letter, we analyze the error performance of a mobile communication system with microdiversity and macrodiversity reception in gamma-shadowed Rician fading channels for a binary differential phase-shift keying modulation scheme. Analytical expressions for the probability density function (PDF) and moment-generating function (MGF) are derived. The average bit error probability can be calculated by averaging the conditional bit error probability over the PDF or using the MGF-based approach. Numerical results are graphically presented to show the effects of macrodiversity, correlation, number of diversity branches, and severity of both fading and shadowing.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.408-413
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• 2005

A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).