• Journal of the Korean Statistical Society
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• 제13권2호
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• pp.87-106
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• 1984

It ${X_t}$ is a sequence of independent identically distributed normal random variables, then the conditional probability density of $X_1, X_2, \cdots, X_n$ given the first p+1 sample autocovariances converges to the maximum entropy probability density satisfying the corresponding covariance constraints as the length of the sample sequence tends to infinity. This establishes that the maximum entropy probability density and the associated Gaussian autoregressive process arise naturally as the answers of conditional limit problems.

• Water Engineering Research
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• 제4권3호
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• pp.155-173
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• 2003

Parameters and quantiles of the 2-parameter generalized Pareto distribution were estimated using the methods of regular moments, modified moments, probability weighted moments, linear moments, maximum likelihood, and entropy for Monte Carlo-generated samples. The performance of these seven estimators was statistically compared, with the objective of identifying the most robust estimator. It was found that in general the methods of probability-weighted moments and L-moments performed better than the methods of maximum likelihood estimation, moments and entropy, especially for smaller values of the coefficient of variation and probability of exceedance.

• 한국통신학회논문지
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• 제34권2A호
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• pp.85-90
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• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• 대한전자공학회논문지
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• 제20권2호
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• pp.16-22
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• 1983

본 논문에서는 이진 일차 Markov 정보원에서 하나의 조건부 확률이 주어졌을 때, 엔트로피(entropy)를 최대로 하기 위한 나머지의 조건부 확률(PFME; probability for maximum entropy)과 그때의 언트로피를 구했다. 또한, 평형 상태 확률이 일정할 때 조건부 확률의 변화가 엔트로피에 미치는 영향도 함께 고찰하였다.

• 경영과학
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• 제28권1호
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• pp.159-167
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• 2011

The theory of random utility maximization (RUM) defines the probability of an alternative being chosen as the probability of its utility being perceived as higher than those of all the other competing alternatives in the choice set (Marschak 1960). According to this theory, consumers perceive the utility of an alternative not as a constant but as a probability distribution. Over the last two decades, there have been an increasing number of studies on the effect of utility variance on choice probability. The common result of the previous studies is that as the utility variance increases, the effect of the mean value of the utility (the deterministic component of the utility) on choice probability is reduced. This study provides a theoretical investigation on the effect of utility variance on choice probability without any assumptions on the specific forms of probability distributions. This study suggests that without assumptions of the probability distribution functions, firms cannot apply the marketing strategy of maximizing choice probability (or market share), but can only adopt the strategy of maximizing the minimum or maximum value of the expected choice probability. This study applies the Chebyshef inequality and shows how the changes in utility variances affect the maximum of minimum of choice probabilities and provides managerial implications.

• 한국정보전자통신기술학회논문지
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• 제13권2호
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• pp.95-101
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• 2020

In this paper, we consider a group testing (GT) framework which is to find a set of defective samples out of a large number of samples. To handle this framework, we propose a maximum product detection algorithm (MPDA) which is based on maximum a posteriori probability (MAP). The key idea of this algorithm exploits iterative detection to propagate belief to neighbor samples by exchanging marginal probabilities between samples and output results. The belief propagation algorithm as a conventional approach has been used to detect defective samples, but it has computational complexity to obtain the marginal probability in the output nodes which combine other marginal probabilities from the sample nodes. We show that the our proposed MPDA provides a benefit to reduce computational complexity up to 12% in runtime, while its performance is only slightly degraded compared to the belief propagation algorithm. And we verify the simulations to compare the difference of performance.

• 한국통신학회논문지
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• 제36권12C호
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• Journal of the Korean Data and Information Science Society
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• 제22권4호
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• pp.811-817
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• 2011

We shall introduce a general probability mass function which includes several discrete probability mass functions. Especially, when the random variable X is Poisson, binomial, and negative binomial random variables as some special cases of the introduced distribution, the maximum likelihood estimator (MLE) and the uniformly minimum variance unbiased estimator (UMVUE) of the probability P(X ${\leq}$ t) are considered. And the efficiencies of the MLE and the UMVUE of the reliability ar compared each other.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.1762-1766
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• 2006

In order to protect properties and human lives from disasters such as heavy rainfall, rational Probability Maximum Flood(PMF) estimation procedures for existing dam basins are recently required. This study analyzes the Probable Maximum Flood(PMF) as a part of a counterplan for disaster preventions of hydraulic structures such as dams, according to recent unfavorable weather conditions. In this study, an improvement method of parameter estimation was proposed, being estimated as an appropriate method for application to the unit hydrograph, the time of concentration and storage constant corresponding to the discharge of flood were considered differently when estimating PMF in Hoengseong dam basin.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2004년도 학술발표회
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• pp.479-483
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• 2004

A new calculation method of expected overtopping probability of rubble mound breakwater considering real tide occurrence has been proposed. A calculation method of expected overtopping probability of rubble mound breakwater was proposed by Kweon and Suh (2003). In their calculation, the fluctuation of tidal elevation was expressed by the sinusoidal change that yields the uniform distribution of occurrence frequency. However, the realistic distribution of tidal elevation should influence on the overtopping chance. In this study, the occurrence frequency of tidal elevation obtained from the real sea is included. The tidal elevation used in this study is collected from the east coastal part of Korean peninsular. Analyzing the annual data of the tidal fluctuation measured hourly during 355 days, the distribution of occurrence frequency is formulated utilizing by the normal distribution with one peak. Among the calculation procedures of annual maximum wave height, wave height-period joint distribution, wave run-up height and occurrence frequency of tide, only the annual maximum wave height is again chosen randomly from normal distribution to consider the uncertainty. The others are treated by utilizing the distribution function or relationship itself, It is found that the inclusion of the variability of tidal elevation has great influence on the computation of the expected overtopping probability of rubble mound breakwater. The bigger standard deviation of occurrence frequency is, the lower the overtopping probability of rubble mound breakwater is.