• Journal of the Korean Statistical Society
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• 제36권1호
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• pp.57-76
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• 2007

Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

• 제어로봇시스템학회논문지
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• 제9권8호
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• pp.616-622
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• 2003

This paper deals with the problem of estimating the asymptotic stability region(ASR) of uncertain variable structure systems with bounded controllers. Using linear matrix inequalities(LMIs) we estimate the ASR and show the exponential stability of the closed-loop control system in the estimated ASR. We give a simple LMI-based algorithm to get estimates of the ASR. We also give a synthesis algorithm to design a switching surface which will make the estimated ASR big. Finally, we give numerical examples in order to show that our method can give better results than the previous ones for a certain class of uncertain variable structure systems with bounded controllers.

• Kyungpook Mathematical Journal
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• 제48권2호
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• pp.173-181
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• 2008

We give the necessary and sufficient conditions for the asymptotic stability of the linear delay difference equation $x_{n+1}\;-\;a^2x_{n-1}\;+\;bx_{n-k}\;=\;0$, n = 0, 1,$\cdots$, where a and b are arbitrary real numbers and k is a positive integer greater than 1. The obtained conditions are given in terms of parameters a and b of difference equations. The method of proof is based on arithematic of complex numbers as well as properties of analytic functions.

• 한국산업정보학회논문지
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• 제7권1호
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• pp.75-80
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• 2002

미분시스템의 안정성에 관한 이론에서 페론 방법은 각 개념의 정의와 적분부등식을 통해서 해의 정성적 규명을 연구하는 최근에 가장 일반적 형식 중의 하나이다. 이 논문을 통해서는 특히, 두 개의 섭동 e(t,x)와 f(t,x)를 수반하는 미분 시스템의 자명해와 접근적 안정성의 여러 가지 양태를 페론 방법을 써서 조사해 보고 이들의 충분조건을 찾아 몇 가지 정리를 얻었다.

• Communications for Statistical Applications and Methods
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• 제3권2호
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• pp.175-185
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• 1996

For the Change-point problem in a sequence of binomial variables we consider the maximum likelihood estimator (MLE) of unknown change-point. Its asymptotic distribution is quite limited in the case of binomial variables with different numver of trials at each time point. Hinkley and Hinkley (1970) gives an asymptotic distribution of the MLE for a sequence of Bernoulli random variables. To find the asymptotic distribution a numerical method such as bootstrap can be used. Another concern of our interest in the inference on the change-point and we derive confidence sets based on the liklihood ratio test(LRT). We find approximate confidence sets from the bootstrap distribution and compare the two results through an example.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 제5회 학술대회 논문집 일렉트렛트 및 응용기술연구회
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• pp.96-99
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• 2003

In this paper, it presents a method to calculate the escape frequency factor$(\nu)$ and its verification from TSC(Thermally Stimulated Current) equation and their simulation curves. To apply calculation method of $\nu$ using asymptotic estimation, it utilized TSC data with 1K interval. This method enables one to get the exact value of $\nu$ and activation energy at the same time by using computer programming. So, it regards their calculation method as a useful process to obtain the value of physical behavior.

• Journal of applied mathematics & informatics
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• 제27권1_2호
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• pp.315-326
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• 2009

The unknown parameters in regression models are usually estimated by using various existing methods. There are several existing methods, such as the least squares method, which is the most common one, the least absolute deviation method, the regression quantile method, and the asymmetric least squares method. For the nonlinear time series regression models, which do not satisfy the general conditions, we will compare them in two ways: 1) a theoretical comparison in the asymptotic sense and 2) an empirical comparison using Monte Carlo simulation for a small sample size.

• 소음진동
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• 제7권1호
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• pp.55-60
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• 1997

In order to examine the validity of an asymptotic solution obtained from the method of multiple scales, we investigate a third-order subharmonic resonance response of a bar constrained by a nonlinear spring to a harmonic excitation. The motion of the bar is governed by a linear partial differential equation with a nonlinear boundary condition. The nonlinear boundary value problem is solved by using the finite difference method. The numerical solution is compared with the asymptotic solution.

• 충청수학회지
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• 제22권2호
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• pp.217-227
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• 2009

Assuming that a given nonlinear function f : $\mathbf{R}{\rightarrow}\mathbf{R}$ has a zero $\alpha$with integer multiplicity $m{\geq}1$ and is sufficiently smooth in a small neighborhood of $\alpha$, we define extended leap-frogging Newton's method. We investigate the order of convergence and the asymptotic error constant of the proposed method as a function of multiplicity m. Numerical experiments for various test functions show a satisfactory agreement with the theory presented in this paper and are throughly verified via Mathematica programming with its high-precision computability.

• 충청수학회지
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• 제20권1호
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• pp.11-21
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• 2007

Given a nonlinear function f : $\mathbb{R}{\rightarrow}\mathbb{R}$ that has a simple real zero ${\alpha}$, a new numerical method to be called k-fold pseudo- Halley's method is proposed and it's error analysis is under investigation to confirm the convergence behavior near ${\alpha}$. Under the assumption that f is sufficiently smooth in a small neighborhood of ${\alpha}$, the order of convergence is found to be at least k+3. In addition, the corresponding asymptotic error constant is explicitly expressed in terms of k, ${\alpha}$ and f as well as the derivatives of f. A zero-finding algorithm is written and has been successfully implemented for numerous examples with Mathematica.