• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.83-91
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• 2020

To use the OneSAF model for the analysis of Defence M&S, the most critical factor is the acquisition of input data. The model user is hard to determine the input data such as the probability of hit(P_h) and the probability of kill(P_k). These data can be obtained directly by live fire during the development test and the operational test. Therefore, this needs more time and resources to get the P_h and P_k. In this paper, we reviewed possible ways to obtain the P_h and P_k. We introduced several data producing methodologies. In particular, the error budget method was presented to convert the P_h(%) data of AWAM model to the error(mil) data of OneSAF model. Also, the conversion method which can get the adjusted results from the JMEM is introduced. The probability of a hit was calculated based on the error budget method in order to prove the usefulness of the given method. More accurate data were obtained when the error budget method and the projected area from the published photo were used simultaneously. The importance of the P_h calculation was demonstrated by sensitivity analysis of the P_h on combat effectiveness. This paper emphasizes the importance of determining the P_h data and improving the reliability of the M&S system though steady collection and analysis of the P_h data.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1E
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• pp.3-6
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• 1999

In digital mobile communication system, the transmission errors affect the quality of output speech seriously. There are many error concealment techniques using a posteriori probability which provides information about any transmitted parameter. They need knowledge about channel transition probability as well as the 1st order Markov transition probability of codec parameters for estimation of transmitted parameters. However, in applications of mobile communication systems, the channel transition probability varies depending on nonstationary channel characteristics. The mismatch of designed channel transition probability of the estimator to actual channel transition probability degrades the performance of the estimator. In this paper, we proposed a new parameter estimator which adapts to the channel characteristics using short time average of maximum a posteriori probabilities(MAPs). The proposed scheme, when applied to the LSP parameter estimation, performed better than the conventional estimator which do not adapt to the channel characteristics.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1798-1802
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• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation.The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall.The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.95-102
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• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation. The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall. The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.119-122
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• 2003

In this paper presents equations which describe an average weighted spectrum of errors and average block error probabilities for noncoherent frequency shift keying (NCFSK) used in D-branch maximal ratio combining (MRC) diversity in independent very slow nonselective Nakagami fading channels. The average is formed over the instantaneous receiver signal to noise ratio (SNR) after combining. the analysis is limited to additive Gaussian noise.

• Journal of the Korean Data and Information Science Society
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• v.19 no.1
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• pp.25-36
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• 2008

Error Correcting Output Codes (ECOC) can improve generalization performance when applied to multicategory classification problem. In this study we propose a new criterion to select hyperparameters included in ECOC scheme. Instead of margins of a data we propose to use the probability of misclassification error since it makes the criterion simple. Using this we obtain an upper bound of leave-one-out error of OVA(one vs all) method. Our experiments from real and synthetic data indicate that the bound leads to good estimates of parameters.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2426-2426
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• 2021

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.982-987
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• 2012

In this paper, the SNR estimation error of Decision Directed SNR estimation method in AWGN is investigated, which uses samples received in reference decision region. In communication system receiver, when SNR estimation scheme using error vectors between ideal sample points and received sample points of reference region is adopted, the samples contain incorrectly received samples due to AWGN. Consequently, the mean of estimated reference constellation point is shifted and Decision Directed SNR estimation is inaccurately performed. These effects are explained by modified probability density function and difference between actual SNR and estimated SNR is theoretically derived and quantatively analyzed. It is proved that SNR estimation error obtained through computer simulation is matched up with derived one, and SNR estimation performance is enhanced significantly by adopting suggested correction scheme.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.3
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• pp.37-45
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• 1982

This paper is a sequel of the Part I paper[1] on the modified digital Costas loop. In this Part II we analyze the performance of the system in the presence of noise. It is shown that, when the input signal is corrupted by additive white Gaussian noise, the noise process in the loop becomes Rician as a result of the tan-1 (.) function of the phase error detector. Steady state probability density functions of phase errors of the first-and second-order loops have been obtained by solving the Chapman-Kolmogorov equation numerically. Also, the mean and variance of phase error in the steady state have been obtained analytically, and are compared with the results obtained by computer simulation.

• Journal of the Korean Statistical Society
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• v.36 no.2
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• pp.201-208
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• 2007

Evolutionary operation (EVOP) proposed by Box (1957) is a method for continuous monitoring and improvement of a full-scale manufacturing process with the objective of moving the operating conditions toward the better ones. EVOP consists of systematically making small changes in the levels of the two or three process variables under consideration. Data are collected on the response variable at each point of two level factorial design with the center point and a cycle is said to have been completed. The cycles are replicated sequentially until the decision is made on whether further cycle of experiments is needed to conclude the significance of any of main effects or interaction effects or the curvature. In this paper, an improved flow chart of EVOP is proposed and how to determine the number of cycles is studied based on the size of type II error. In order to reject the alternative hypothesis of interests with more confidence and conclude that we believe in the null hypothesis of no effects, we propose a counter measure $p^*-value$ corresponding to the p-value. The relationship of $p^*-value$ to the probability of type II error ${\beta}$ under the alternative hypothesis of interests is analogous to that of p-value to the probability of type I error ${\alpha}$. Also the implementation of EVOP with a mixture experiment is discussed.