• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.996-1003
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• 1999

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

• Journal of Animal Science and Technology
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• 제63권1호
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• pp.25-35
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• 2021

The purpose of this study is to estimate the single nucleotide polymorphism (SNP) effect for pH values affecting Berkshire meat quality. A total of 39,603 SNPs from 1,978 heads after quality control and 882 pH values were used estimate SNP effect by single step genomic best linear unbiased prediction (ssGBLUP) method. The average physical distance between adjacent SNP pairs was 61.7kbp and the number and proportion of SNPs whose minor allele frequency was below 10% were 9,573 and 24.2%, respectively. The average of observed heterozygosity and polymorphic information content was 0.32 ± 0.16 and 0.26 ± 0.11, respectively and the estimate for average linkage disequilibrium was 0.40. The heritability of pH45m and pH24h were 0.10 and 0.15 respectively. SNPs with an absolute value more than 4 standard deviations from the mean were selected as threshold markers, among the selected SNPs, protein-coding genes of pH45m and pH24h were detected in 6 and 4 SNPs, respectively. The distribution of coding genes were detected at pH45m and were detected at pH24h.

• 자연과학논문집
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• 제8권1호
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• pp.5-15
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• 1995

IRR 적응 휠터의 공식오차 방식은 지역 최소값에 관계없이 전역 최소값에 수렴하며 안정성이 높다. 그러나 공식오차 방식은 입력 신호에 잡음이 섞여 경우 예측계수가 바이어스 되는 문제가 있다. 본 논문에서는 사전에 잡음에 대한 지식이 없이 바이어스가 없는 예측계수를 얻을 수 있는 새로운 공식 오차 방식을 위한 알고리즘을 제안한다. 이 알고리즘은 공식오차를 스므딩하는 방식을 이용하여 입력에 추가되는 잡음이 백색잡음인 경우 바이어스 없이 계수를 예측할 수 있다. 시뮬레이션을 통해 새로운 알고리즘이 공식오차의 중요한 장점인 빠른 수렴속도와 안정성을 유지하며 바이어스를 효율적으로 제거함을 볼 수 있다.

• Quantitative Bio-Science
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• 제37권2호
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• pp.133-141
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• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• 한국측량학회지
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• 제35권6호
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• pp.573-580
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• 2017

GPS 관측값을 이용하여 측위를 하는 경우 조정계산이 수반되면 이때 관측오차에 대한 정확한 모델링이 필수적이다. 본 연구에서는 GPS 관측타입별 관측오차를 분석하기 위해 MINQUE(Minimum Norm Quadratic Unbiased Estimators) 방법을 사용하였으며 단기선 GPS측위 모델을 기반으로 하였다. C1, P2, L1, L2 관측타입에 대해 각각 단위분산을 계산하였으며 그 결과 관측오차는 각각 22.3cm, 27.6cm, 2.5cm, 2.2cm로 나타났다. 단위분산 계산에는 대용량의 컴퓨터 메모리와 복잡한 계산이 필요하다. 이러한 단점을 극복하기 위해 epoch별로 단위분산을 추정하였으며 결과를 분석함으로써 epoch별 계산방법의 유효성을 검증하였다. 분석 결과, 계산된 결과값에 차이가 있긴 했으나 그 차이가 비교적 작기 때문에 대부분의 GPS 응용분야에서의 활용에는 문제가 없을 것으로 판단된다.

• 농업과학연구
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• 제46권2호
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• pp.293-301
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• 2019

This study was done to estimate the effect of progeny numbers and pedigree depth on the accuracy of the estimated breeding value (EBV) using best linear unbiased prediction (BLUP) method in Hanwoo. The experiment groups (sire = 100, 200, and 300; progeny = 4 and 8) were made by random sampling and by genetic evaluation of the following traits: Body weight (BW), carcass weight (CW), eye muscle area (EMA), back fat thickness (BFT) and marbling score (MS9). As a result of the genetic evaluation, the accuracy of the EBV was roughly 30 - 60% with 4 progenies, and the accuracy of the EBV increased by about 50 - 75% with 8 progenies. In the other words, when the number of progenies increased from 4 to 8, the accuracy of the EBV simultaneously increased by about 15 - 20%. Moreover, when the number of sires was higher, variations in the accuracy of the EBV within the groups for each trait decreased. Therefore, this result indicates that not only the number of progeny but also the number of sires can affect the accuracy of the EBV. Consequently, collecting information on the progeny and careful management of that information are very important things in the Hanwoo breeding system. Therefore, the EBV can show more precise results when conducting genetic evaluations.

• 제어로봇시스템학회논문지
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• 제20권2호
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• pp.170-174
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• 2014

In this paper, an unknown input estimation method via the optimal FIR smoother is proposed for linear discrete-time systems. The unknown inputs are represented by random walk processes and treated as auxiliary states in augmented state space models. In order to estimate augmented states which include unknown inputs, the optimal FIR smoother is applied to the augmented state space model. Since the optimal FIR smoother is unbiased and independent of any a priori information of the augmented state, the estimates of each unknown input are independent of the initial state and of other unknown inputs. Moreover, the proposed method can be applied to stochastic singular systems, since the optimal FIR smoother is derived without the assumption that the system matrix is nonsingular. A numerical example is given to show the performance of the proposed estimation method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1659-1662
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• 1997

The objective of this paper is to estimate the aerodynamic derivatives of a single turbo-prop aircraft at a specified flight condition for the best deduction of the dynamic characteristics using modified maximum likelihood estimation method whcih is known to be unbiased, efficient, and consistent. The flight test data necessary to the estimation of aerodynamic derivatives is obtained by implementing the six degree of freedom nonlinear flight simulation to consider the effects of several control input types, control deflection amplitudes, and intensity of turbulence. The simulated data is added with the measurement noise, which is regarded as the actual flight test data.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.37-46
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• 2020

Recurrent event data frequently occur in clinical studies, demography, engineering reliability and so on (Cook and Lawless, The Statistical Analysis of Recurrent Events, Springer, 2007). Sometimes, two or more different but related type of recurrent events may occur simultaneously. In this study, our interest is to estimate the covariate effect on bivariate recurrent event times with zero inflations. Such zero inflation can be related with susceptibility. In the context of bivariate recurrent event data, furthermore, such susceptibilities may be different according to the type of event. We propose a joint model including both two intensity functions and two cure rate functions. Bivariate frailty effects are adopted to model the correlation between recurrent events. Parameter estimates are obtained by maximizing the likelihood derived under a piecewise constant hazard assumption. According to simulation results, the proposed method brings unbiased estimates while the model ignoring cure rate models gives underestimated covariate effects and overestimated variance estimates. We apply the proposed method to a set of bivariate recurrent infection data in a study of child patients with leukemia.

• 응용통계연구
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• 제23권6호
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.