• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.22-27
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• 1989

In this paper influences of disturbances and Modeling errors are qualitatively for the linear approximation model of turret servo system, and then LQG/LTR Control theory is applied to linear approximation model in order to design a controller which satisfies robustneas/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 II
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• pp.939-942
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• 2003

Design verification problem is emerging as an important issue to detect any design errors at the early stage of the design. Conventionally, design verifications have been done using a simulation technique. However, this technique has been proved not to cover all potential design errors. Therefore, formal technique is often used to verify digital circuits as an alternative. In this paper we adopted formal verification technique and verified some important properties derived from our pipelined digital systems, using SMV (Symbolic Model Verifier). Our example shows that model checking method (one of formal verification techniques) can be effectively performed in verifying the large digital systems.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.233-237
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• 2003

An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

• 한국경영공학회지
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• 제23권4호
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• pp.159-164
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• 2018

Human-machine serial systems must be normal in both systems. Though the failure of machine is irreducible by itself, the human errors are of recurring type. When the human performance is described quantitatively, non-homogeneous Poisson Process model of human errors can be developed. And the model parameters can be estimated by maximum likelihood estimation and numerical analysis method. System reliability is obtained by multiplying machine reliability by human reliability.

• 한국신뢰성학회지:신뢰성응용연구
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• 제3권2호
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• pp.127-136
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• 2003

This paper investigates the effect of individual observations in regression models with MA(1) errors through the 'hat matrix' It shows that the first observation has the largest hat matrix diagonal component for $\theta$＜0 in the regression model with an intercept. This provides additional evidence for retaining the first observation in performing estimation in this setting. When the regression model goes to the origin and the independent variable has a deterministic trend, the last observation has the greatest leverage for │$\theta$│＜1 and may have potentially large impact on parameter estimation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.69.2-69
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• 2002

Process measurements contain random and gross errors and the size estimation of gross errors is required for production accounting. Mixed integer programming technique had been applied to identify and estimate the gross errors simultaneously. However, the compensate model based on mixed integer programming used all measured variables or spanning tree as gross error candidates. This makes gross error estimation problem combinatorial or computationally expensive. Mixed integer programming with test statistics is proposed for computationally inexpensive gross error identification /estimation. The gross error candidates are identified by measurement test and the set of gross error candidates are...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.98-98
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• 2000

In this paper, we present a Multiheading Method for INS initial. The system is not observable for initial alignment however using pseudo tilt angles and pseudo sensor errors become observable. We suggest a new Multiple Method to find the real sensor errors by using the converted system dynamics. The results show that we can find the sensor errors very accurately by the proposed method.

• 한국대기환경학회지
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• 제18권1호
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• pp.59-65
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• 2002

The application of local air circulation models in the field of air pollution research has become more and more popular with increasing demands of detailed wind data for obtaining precise information on spatial and temporal variations. However the prediction of air circulation near the surface is generally not a simple task because of intricate interactions between surface and air. Particularly in Korea, many areas are mountainous with a complicated shoreline. Because considerable errors could be introduced into the model predictions, it is necessary to confirm their feasibility by comparing model predictions with observations. In this paper, the results from the evaluation of model predictions in selected publications in Korea as well as their procedures were reviewed. Various aspects of errors in the model predictions. such as possible sources, vulnerable conditions, and reduction methods, were discussed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.985-990
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• 2001

The Frequency Response Function(FRF)s of FE Model reduced by SEREP methods accurately estimate the full model at resonance frequencies, However these FRFs are not accurate at antiresonance frequencies, Additionally, the truncation errors may he significant in the reduction mode1. So this paper considers the possibility of SERFP method through a numerical method to preserve dynamic behavior at antiresonance and appliers the static or dynamic compensation methods for truncation errors to the reduction model. This compensated reduction model is redesigned for pole-zero cancellation methods the objective of reducing a resonance frequency.

• 대한원격탐사학회지
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• 제26권6호
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.