• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.335-345
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• 2000

Most context use the classical norms on function spaces as the error criteria. Since these norms are all based on the vertical distances between the curves, these can be quite inappropriate from a visual notion of distance. Visual errors in Marron and Tsybakov(1995) correspond more closely to "what the eye sees". Simulation is performed to compare the performance of the regression smoothers in view of MISE and the visual error. It shows that the visual error can be used as a possible candidate of error criteria in the kernel regression estimation.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.95-102
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• 2014

This paper presents zero crossing point(ZCP) estimation methods considering discretization error for a high speed brushless DC(BLDC) motor drive. The ZCP is estimated by detecting the change of back-EMF polarity for the BLDC sensorless drive, and the discretization error exist on the estimated ZCP. The discretization error of the ZCP is a cause of the delay of a commutation timing of current and increment of a current ripple factor. Besides a delay of a ZCP estimation brings on the limitation of a speed range for the BLDC sensorless drive. The compensation method based on the error analysis with probability theory for reducing the effects of the discretization error of the ZCP is proposed. Also a ZCP estimation method according to the Back-EMF patterns is proposed to widen the speed range for the BLDC sensorless drive. The proposed methods are verified by the experiment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.147-154
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• 2002

In this paper, we propose an error estimation method based on the Bhattacharyya distance for multimodal data. First, we try to find the empirical relationship between the classification error and the Bhattacharyya distance. Then, we investigate the possibility to derive the error estimation equation based on the Bhattacharyya distance for multimodal data. We assume that the distribution of multimodal data can be approximated as a mixture of several Gaussian distributions. Experimental results with remotely sensed data showed that there exist strong relationships between the Bhattacharyya distance and the classification error and that it is possible to predict the classification error using the Bhattacharyya distance for multimodal data.

• Journal of the Korean Society of Safety
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• v.21 no.3 s.75
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• pp.137-142
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• 2006

Quantification of error possibility, in an HRA process, should be performed so that the result of the qualitative analysis can be utilized in other areas in conjunction with overall safety estimation results. And also, the quantification is an essential process to analyze the error possibility in detail and to obtain countermeasures for the errors through screening procedures. In previous studies for the quantification of error possibility, nominal values were assigned by the experts' judgements and utilized as corresponding probabilities. The values assigned by experts' experiences and judgements, however, require verifications on their reliability. In this study, the validity of new error possibility values in new MCR design was verified by using the Onisawa's model which utilizes fuzzy linguistic values to estimate human error probabilities. With the model of error probabilities are represented as analyst's estimations and natural language expression instead of numerical values. As results, the experts' estimation values about error probabilities are well agreed to the existing error probability estimation model. Thus, it was concluded that the occurrence probabilities of errors derived from the human error analysis process can be assessed by nominal values suggested in the previous studies. It is also expected that our analysis method can supplement the conventional HRA method because the nominal values are based on the consideration of various influencing factors such as PSFs.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.95-101
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• 2020

We studied the Implementation and design of inertial sensor that enables to improve performance by reduce the noise of rotor which Angle of inclination. Analyze model equation including motion equation and error, signal processing filter algorithm on high frequency bandwidth with eliminates error using estimation of error coefficient method is was designed and the prototype inertial sensor showed the pick off noise up to 0.2 mV and bias error performance of about 0.06 deg/hr by the experiments. Accordingly, we confirmed that the design of inertial sensor was valid for high rotation.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.157-166
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• 2023

Several experiments were carried out to analyze the impact of the modernized Global Positioning System (GPS) L2C signal on pseudorange-based point positioning. Three dual-frequency positioning algorithms, ionosphere-free linear combination, ionospheric error estimation, and simple integration, were used, and the results were compared with those of Standard Point Positioning (SPP). An analysis was conducted to determine the characteristics of each dual-frequency positioning method, the impact of the magnitude of ionospheric error, and receiver grade. Ionosphere-free and ionospheric error estimation methods can provide improved positioning accuracy relative to SPP because they are able to significantly reduce the ionospheric error. However, this result was possible only when the ionospheric error reduction effect was greater than the disadvantage of these dual-frequency positioning algorithms such as the increment of multipath and noise, impact of uncertainty of unknown parameter estimation. The RMSE of the simple integration algorithm was larger than that of SPP, because of the remaining ionospheric error. Even though the receiver grade was different, similar results were observed.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.403-414
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• 2009

Many researches have been devoted to the small area estimation related with the area level statistics. Almost all of the small area estimation methods are derived based on minimization of mean squared error(MSE). Recently Hwang and Shin (2008) suggested an alternative small area estimation method by minimizing mean squared percentage error. In this paper we apply this small area estimation method to the labor statistics, especially monthly wages by a branch area of labor department. The Monthly Labor Survey data (2007) is used for analysis and comparison of these methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.8
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• pp.91-97
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• 2008

The conventional WF(water-filling)-MIMO systems assumes that the channel state information is perfectly known at receiver. However, since, generally, the perfect channel state information is not available at receiver, channel estimation error should be considered at the system. Therefore, in this paper 4he performance of the conventional WF-MIMO systems is numerically analyzed when channel estimation error is considered. The analysis results show that mean square error of channel estimation up to $10^{-4}$ is tolerable to get the same performance obtained when perfect channel information is available.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.63-70
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• 2014

Method a target estimation in spatial are mobile wireless communication using network cell and GPS. It have much error that mobile wireless communication depend on cell size. GPS method can't find a target in shadow and inner area. In this paper, we estimate a target as direction of arrival method using adaptive array antenna system. Adaptive array antenna system can obtain desired signal to remove other signal This paper studied digital beamforming method in order to estimation a target. Proposed method is modified optimum weight and antenna error correction to estimation an optimal receive signal. Digital beamforming method decided a signal phase and amplitude from received signal on array antenna element. But if it is not to do error correction of received signal, system performance have decreased. Firstly, we proposed modified optimum weight in order to finding desired target. Secondly, we are error correction of antenna incident signals by optimal weight before digital beamforming method. Thirdly, throughly simulation, we showed that system performance of proposed method compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.172-177
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• 2024

This paper presents a method to overcome the problem of increasing elevation estimation error when estimating elevation in a multipath situation with radar. A multipath situation means that radar reception signals reflected from the same target come from multiple paths. In non-multipath, the monopulse method is accurate. For the opposite case, the least square error method is accurate. In multipath situation and when the elevation angle is very low, a singular occurs where the least square error estimate diverges. This singular was identified based on the propagation factor, and monopulse and least square error estimation methods were selectively used. As a result, we succeeded in increasing the accuracy of elevation estimation. MATLAB simulations were performed to verify the method proposed in this paper.