• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.611-622
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• 2019

This paper considers the estimation of the long memory parameter in nonparametric regression with strongly correlated errors. The key idea is to minimize a unified mean squared error of long memory parameter to select both kernel bandwidth and the number of frequencies used in exact local Whittle estimation. A unified mean squared error framework is more natural because it provides both goodness of fit and measure of strong dependence. The block bootstrap is applied to evaluate the mean squared error. Finite sample performance using Monte Carlo simulations shows the closest performance to the oracle. The proposed method outperforms existing methods especially when dependency and sample size increase. The proposed method is also illustreated to the volatility of exchange rate between Korean Won for US dollar.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.641-648
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• 1997

Mutual information is useful for analyzing nonlinear dependence in time series in much the same way as correlation is used to characterize linear dependence. We use multivariate kernel density estimators for the estimation of mutual information at different time lags for single and multiple time series. This approach is tested on a variety of hydrologic data sets, and suggested an appropriate delay time $ au$ at which the mutual information is almost zerothen multi-dimensional phase portraits could be constructed from measurements of a single scalar time series.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.26-30
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• 2009

We propose an adaptive Recursive Least Rank(RLR) L-filter which uses an L-estimator in order statistics and is based on rank estimate in robust statistics. The proposed RLR L-filter is a non-linear adaptive filter using non-linear adaptive algorithm and adapts itself to optimal filter in the sense of least dispersion measure of errors with non-homogeneous step size. Therefore the filter may be suitable for applications when the transmission channel is nonlinear channels such as Gaussian noise or impulsive noise, or when the signal is non-stationary such as image signal.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.193-201
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) H\ulcorner controller (H\ulcornerC) is extended to the nonlinear feedback linearization-H\ulcorner/sliding mode controller (NFL-H\ulcorner/SMC), to tackle the problem of the unmeasurable state variables as in the conventional SMC, to obtain smooth control as the linearized controller in a linear system, and to improve the time-domain performance under a worst scenario. The proposed controller is obtained by combining the H\ulcorner estimator with the nonlinear feedback linearization-sliding mode controller (NFL-SMC) and it does not need to measure all the state variables as in the traditional SMC. The proposed controller is applied as a nonlinear power system stabilizer (PSS) for the improvement of the power system damping characteristics of an single machine infinite bus system (SMIBS) connected through a double circuit line. The effectiveness of the proposed controller is verified by nonlinear time-domain simulation in case of a 3-cycle line-to-ground fault and in case of the parameter variations for the AVR gain K\ulcorner and for the inertia moment M.

• 한국정보통신설비학회:학술대회논문집
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• 2006.08a
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• pp.145-150
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• 2006

For most of the measuring methods of traditional control theory, measuring equipments are located at the output of the system to measure quantities transformed from non-electrical form into electrical one. This method helps us to define the value of parameters to be measured, but it has limitation because it can only assess the efficiency of a movement process. That means we can not understand the inner kinetics which is the essence of the system. In the modern control theory, states of system are considered as the feedback to the control process, which helps us to assess the elements in the inside of the system. In this paper, we survey methods for estimating states being not exposed to the correct measurements. Using this method, we also suggest an application for giving an estimate of the traffic on the LSPs to adapt the network configuration for changing traffic conditions.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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• pp.879-897
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• 2013

Shannon entropy is one of the widely used randomness measures especially for cryptographic applications. However, the conventional entropy tests are less sensitive to the inter-bit dependency in random samples. In this paper, we propose new online randomness test schemes for true random number generators (TRNGs) based on the mutual information between consecutive ${\kappa}$-bit output blocks for testing of inter-bit dependency in random samples. By estimating the block entropies of distinct lengths at the same time, it is possible to measure the mutual information, which is closely related to the amount of the statistical dependency between two consecutive data blocks. In addition, we propose a new estimation method for entropies, which accumulates intermediate values of the number of frequencies. The proposed method can estimate entropy with less samples than Maurer-Coron type entropy test can. By numerical simulations, it is shown that the new proposed scheme can be used as a reliable online entropy estimator for TRNGs used by cryptographic modules.

• International Journal of Quality Innovation
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• v.6 no.2
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• pp.31-45
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• 2005

The target costing technique, mathematically discussed by Sauers, only uses the $C_p$ index along with Taguchi loss function and ${\bar{X}}-R$ control charts to set up goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p$ value to ${\bar{X}}-R$ control charts to obtain goal control limits. This study further considers the reflected normal loss function as well as the $C_{pk}$ index along with its lower confidence interval in forming goal control limits. With the use of lower confidence interval to replace the point estimator of the $C_{pk}$ index and reflected normal loss function proposed by Spiring to measure the loss to society, this modified and improved target costing technique would become more robust and applicable in practice. Finally, an example is provided to illustrate how this modified and improved target costing technique works.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.3-8
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• 1994

This paper presents a practical method of measuring the cutting force milling process by sensing the feed-drive servo motor current,avoiding the use of a dynamomenter. The relation between the cutting force and the servo motor currents is obtained after the feed-drive system of machining center is modelled. In order to measure the cutting force indirectly, the cutting force in the feed-drive system is regrared as a disturbance, and a disturbance estimator is designed using Kalman filter. A horizontal type machining center is used in the experimental study. A comparison is made between the cutting force measured from the dynamometer and the servo motor current.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.