• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.335-336
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• 2015

본 논문에서는 스위칭 주파수 신호 주입 센서리스 제어를 위한 정밀한 위치 오차 추정 기법을 제안한다. 제안한 방법에서는 위치 오차를 얻을 때에 작은 각도 근사법(Small-Angle Approximation)을 이용하지 않고 Rotation matrix를 이용하여 근사 없이 실제 위치 오차를 계산하였고, 90도까지 회전자 오차 측정 범위를 확대하였다. 이를 통하여 오차가 크게 발생하는 부하 변동이나 가감속 시에 과도상태특성을 개선할 수 있다. 제안한 방법은 실험을 통하여 그 유효성을 검증하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2819-2830
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• 2009

Load bearing structural members in a wide variety of applications accumulate damage over their service life. During experiment much effort and cost is needed for measuring structural safety assessment. The sparseness and errors of measured data have to be considered during the safety estimation of structures. This paper introduces parameter estimation and damage identification algorithm by a system identification using static and dynamic response. The equation error estimator and response error widely used in system identification are based on the minimization of least squared error between measured and calculated responses by a mathematical model of a structure. Since each estimator has a specific form of application in noisy environment and proposes different definitions for these forms. To study the behaviour of the estimators in noisy environment Using Monte Carlo simulation, and a data measured pertubation scheme is adopted to investigate the influence of measurement errors on identification results. The assessment result by static and dynamic response were compared, and the efficiency and applicabilities of the proposed algorithm are demonstrated through simulated static and dynamic responses of a dimensional truss type structures.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.90-97
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• 1996

The optimal mesh refinement has a meaning that error of the every element is within an allowable level and in uniformly distributed. The adaptive mesh generation may be required to achieve the optimal mesh generation. For the purpose of optimal mesh generation, an error estimation and an adaptive mesh refinement are required. Using the adaptive mesh generation the second finite element analysis is performed with the result of the first analysis. In the process the error estimation is required. In this study the adaptive mesh generation program for triangular element is developed, and for a posteriori error estimation the stress projection approach is considered. It has been found the multigrid technique, where the error estimation and the mesh generation are combined in multi-step of analysis, may be used efficiently in the finite element analysis.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1309-1317
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• 2013

There are various parameter estimation methods for the generalized exponential distribution under progressive type I interval censoring. Chen and Lio (2010) studied the parameter estimation method by the maximum likelihood estimation method, mid-point approximation method, expectation maximization algorithm and methods of moments. Among those, mid-point approximation method has the smallest mean square error in the generalized exponential distribution under progressive type I interval censoring. However, this method is difficult to derive closed form of solution for the parameter estimation using by maximum likelihood estimation method. In this paper, we propose two type of approximate maximum likelihood estimate to solve that problem. The simulation results show the obtained estimators have good performance in the sense of the mean square error. And proposed method derive closed form of solution for the parameter estimation from the generalized exponential distribution under progressive type I interval censoring.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.185-194
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• 2002

To extract relative ranges from LOS(line of sight) information, we propose a passive ranging filter which is suitable for anti-ship missiles in HOJ(home on jam) mode. The proposed filter is devised to cope with the case that a passive ranging filter may include a large initial range estimation error since modem jammers are capable of very long range jamming. In addition, under the assumption that the missile motion is dominant over the HOJ engagement situation, the engagement geometry is modeled by a second order system. A new passive ranging filter is proposed by constructing an extended Kalman filter(EKF) based on the model. And then a least square initial state error estimation algorithm is attached to the EKF. Simulation results show that the proposed filter has a good range estimation performance with small computational load.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.437-445
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• 1999

The present paper describes the problem of hydrologic response estimation using non-parametric ridge regression method. The method adapted in this work is based on the minimization of the $C_L$ statistics, which is an estimate of the mean square prediction error. For this method, effects of using both the identity matrix and the Laplacian matrix were considered. In addition, we evaluated methods for estimating the error variance of the impulse response. As a result of analyzing synthetic and real data, a good estimation was made when the Laplacian matrix for the weighting matrix and the bias corrected estimate for the error variance were used. The method and procedure presented in present paper will play a robust and effective role on separating hydrologic response.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.561-566
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• 2021

The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.56-67
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• 2012

In this thesis, to compensate the sweep nonlinearity occurring in the high resolution radar system using FMICW or FMCW, the method of the estimation of the nonlinearity is proposed. The nonlinear phase component caused by the nonlinear characteristic of the radar system is modelled as a linear combination of the sinusoidal functions consisting of various magnitudes and phases(systematic nonlinear phase error) and a random component(stochastic nonlinear phase error). From two IF signals that are measured respectively independently for two reference point targets lying in different distances which are known, a sparse linear equation is made and solved by least squares method to estimate the nonlinear phase component. The estimated component can be used for predistortion method to compensate the sweep nonlinearity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8B
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• pp.1141-1151
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• 2001

본 논문에서는 효과적으로 선택된 초기 탐색 위치를 이용한 움직임 추정의 고속 알고리즘을 제안하였다. 제안된 알고리즘에서는 2$\times$2화소 블록 평균으로 부표본화 영상에서 움직임 벡터를 얻어 원영상 비율로 확대하고, 주위 블록의 움직임으로부터 예측 움직임 벡터를 구하여, 이 중에서 정합오차가 작은 것을 초기 탐색 위치로 선택한다. 그리고 선택된 초기 탐색 위치를 중심으로 회전 탐색을 시작하여, 연속 소거 알고리즘으로 탐색할 후보 블록을 선택하고, 부분 정합 왜곡 소거법을 사용하여 블록간 정합오차 계산량을 줄이면서, 고속으로 움직임 벡터를 추정한다. 알고리즘의 실제 적용에 있어서는 선택된 초기 탐색 위치를 중심으로 회전 탐색 패턴의 탐색 범위를 조절하거나, 매크로 블록 당 복잡도를 제한하여 계산량을 줄일 수 있다. 실험 결과, 제안된 알고리즘은 전역탐색 블록정합 알고리즘에 대하여 0.2dB 이하의 미소한 평균 PSNR 저하만을 발생하면서, FBMA 복잡도의 3% 이하의 평균 복잡도를 소요하였다. 이것은 3단계 탐색법에 대하여 40% 이하의 계산량이다. 그리고 실험 영상들의 각 프레임에 대해서도 비슷한 성능을 보임을 확인하였다.