• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2199-2200
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.567-568
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1233-1234
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.77-80
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• 2002

In this paper, we analyze a physical layer of W-CDMA .system and design a transmitter and receiver by using ADS (Advanced Design System). Also, we simulated a link level performance with different channel estimation algorithm in Jakes fading channel environment. For the channel estimator, we used the WMSA(Weighted Multi-Slot Averaging) algorithm, EGE(Equal Gain Estimation) algorithm and SSE(Symbol-to-Symbol Estimation) algorithm. This study will be useful in the analysis and design of W-CDMA system.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1693-1694
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Korean Management Science Review
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• v.19 no.1
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• pp.117-128
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• 2002

In this Paper we investigate the performance of the five efficiency estimation methods which include the stochastic frontier model estimated by maximum likelihood (SFML), the stochastic frontier model estimated by corrected ordinary least squares (SFCOLS), the data envelopment analysis (DIA) model, the combined estimation of SFML and DEA (SFML + DEA), and the combined estimation of SFCOLS arid DIA (SFCOLS+ DEA) using Monte Carlo analysis. The results include: 1) SFML provides most accurate efficiency estimates for the sample sloe 150 or over,2) SFML+DEAor SFCOLS + DIA Perform better for the cases with sample sloe 25, 50, and low random errors, 3) SFCOLS performs better for the close with sample sloe 25, 50, and very high random errors.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.673-685
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• 2018

Procrustes analysis is a useful technique useful to measure, compare shape differences and estimate a mean shape for objects; however it is based on a least squares criterion and is affected by some outliers. Therefore, we propose two generalized Procrustes analysis methods based on M-estimation and least median of squares estimation that are resistant to object outliers. In addition, two algorithms are given for practical implementation. A simulation study and some examples are used to examine and compared the performances of the algorithms with the least square method. Moreover since these resistant GPA methods are available for higher dimensions, we need some methods to visualize the objects and mean shape effectively. Also since we have concentrated on resistant fitting methods without considering shape distributions, we wish to shape analysis not be sensitive to particular model.

• Korean Journal of Clinical Pharmacy
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• v.23 no.2
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• pp.137-141
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• 2013

Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.2
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• pp.139-146
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• 2018

This work puts forward a theoretical analysis on position estimation performance of interior permanent magnet synchronous motor (IPMSM) according to the injection frequency in carrier-based sensorless operation. The effects of spatial harmonics on inductance and voltage distortion due to the nonideal characteristics of IPMSM and inverter are examined as factors influencing the position estimation performance. Furthermore, the position estimation performance is analyzed by calculating the current at the switching instant in several operating conditions. In summary, the half switching frequency injection is more robust to the nonideal characteristics of IPMSM, especially with light load condition. The validity of the analysis is verified by the simulation and experimental results.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.46-53
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• 2015

This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.