• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.99-107
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• 2018

This article considers a robust Kalman filter from the M-estimation point of view. Pak (Journal of the Korean Statistical Society, 27, 507-514, 1998) proposed a particular M-estimating function which has the data-based shaping constants. The Kalman filter with the proposed M-estimating function is considered. The structure and the estimating algorithm of the Kalman filter accompanying the M-estimating function are mentioned. Kalman filter estimates by the proposed M-estimating function are shown to be well behaved even when data are contaminated.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.189-202
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• 1998

The goat of this paper is to study on variance estimation - Rice variance estimation, Gasser, Sroka and Jennen-Steinmetz's varince estimation - in smoothing goodness-of-fit tests. The comparisons of powers on test statistics are conducted by the change of variance, the number of oscillations, the amplitude of the alternative sample distribution.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.4
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• pp.16-22
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• 2013

This paper presents a method to analyze the voltage sag data obtained from monitoring systems. In order to establish effective countermeasures against voltage sag problems, an assessment of the system performance with respect to voltage sags is needed. Generally, the average annual sag frequency can be estimated by using the recorded voltage sag events for several years. However, the simple average value can not give the information about the errors of estimation. Such an average estimation is not useful for establishing effective solutions for voltage sag problems. Therefore, this paper proposes an effective method based on the Interval Estimation method. The estimation of voltage sag frequency is performed by using the average frequency and Poisson probability model. The proposed method can give the expected annual sag frequency and upper one-sided bound frequency.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.17-22
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• 2018

In massive multiple-input multiple-output (MIMO) systems, linear channel estimation algorithms are widely applied owing to their simple structures. However, they may cause pilot contamination, which affects the subsequent data detection performance. Therefore, herein, for an uplink multicell massive multiuser MIMO system, we consider using an alternating projection (AP) for channel estimation to eliminate the effect of pilot contamination and improve the performance of data detection in terms of the bit error rates as well. Even though the AP is nonlinear, it iteratively searches the best solution in only one dimension, and the computational complexity is thus modest. We have analyzed the mean square error with respect to the signal-to-interference ratios for both the cooperative and non-cooperative multicell scenarios. From the simulation results, we observed that the channel estimation results via the AP benefit the following signal detection more than that via the least squares for both the cooperative and non-cooperative multicell scenarios.

• Journal of the Korean Data and Information Science Society
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• v.3 no.1
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• pp.17-24
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• 1992

The problem of estimating symmetric probability density with high kurtosis is considered. Such densities are often estimated poorly by a global bandwidth kernel estimation since good estimation of the peak of the distribution leads to unsatisfactory estimation of the tails and vice versa. In this paper, we propose a transformation technique before using a global bandwidth kernel estimator. Performance of density estimator based on proposed transformation is investigated through simulation study. It is observed that our method offers a substantial improvement for the densities with high kurtosis. However, its performance is a little worse than that of ordinary kernel estimator in the situation where the kurtosis is not high.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.166-173
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• 2007

In this paper, we propose a model-based approach to estimating production parameters of semiconductor FAB equipment. For FAB scheduling, for example, we need to know equipment's production parameters such as flow time, tact time, setup time, and down time. However, these data are not available, and they have to be estimated from material move data such as loading times and unloading times that are automatically collected in modern automated semiconductor FAB. The proposed estimation method may be regarded as a Bayes estimation method because we use additional information about the production parameters. Namely, it is assumed that the technical ranges of production parameters are known. The proposed estimation method has been applied to a LCD FAB, and found to be valid and useful.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.820-822
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• 2005

The current paper is on a study of the performance estimation fer data processing time and CPU utilization to efficiently develop the real-time system. The analytical modeling and OPNET modeling and benchmarking tests are applied to perform the estimation for data processing time and CPU utilization in real-time system. We demonstrate that the estimation results can be predicted fairly and accurately through the benchmarking test results although there is a small variance between the estimation results and the benchmarking test results.

• Journal of Biomedical Engineering Research
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• v.31 no.4
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• pp.285-291
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• 2010

Recently, advance on various modalities of diagnosing, prostate volume estimation became possible not only by the existing two-dimension medical images data but also by the three-dimensional medical images data. In this study, magnetic resonance image (MRI), computer tomography (CT) and ultrasound (US) were employed to evaluate prostate phantom volume measurements for estimation, comparison and analysis. For the prostate phantoms aimed at estimating the volume, total of 17 models were developed by using devils-tongue jelly and changing each of the 5ml of capacity from 20ml to 100ml. For the volume estimation through 2D US, the calculation of the diameter with C9-5Mhz transducer was conducted by ellipsoid formula. For the volume estimation through 3D US, the Qlab software (Philips Medical) was used to calculate the volume data estimated by 3D9-3Mhz transducer. Moreover, the images by 16 channels CT and 1.5 Tesla MRI were added by the method of continuous cross-section addition and each of imaginary prostate model's volume was yielded. In the statistical analysis for comparing the availability of volume estimation, the correlation coefficient (r) was more than 0.9 for all indicating that there were highly correlated, and there were not statistically significant difference between each of the correlation coefficient (p=0.001). Therefore, the estimation of prostate phantom volume using three-dimensional modalities of diagnosing was quite closed to the actual estimation.