• Journal of the Korean Statistical Society
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• 제31권1호
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• pp.33-43
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• 2002

The empirical Bayes linear loss two-action problem is studied. An empirical Bayes test $\delta$$_{n}$ $^{*}$ is proposed. It is shown that $\delta$$_{n}$ $^{*}$ is asymptotically optimal in the sense that its regret converges to zero at a rate $n^{-1}$ over a class of priors and the rate $n^{-1}$ is the optimal rate of convergence of empirical Bayes tests.sts.

• 전기의세계
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• 제17권1호
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• pp.48-50
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• 1968

The convergence rate of Bayes' learning process is investigated for a binomial random variable. A measure of the rate of convergence is proposed and it is found that such a measure can be approximated by an exponential function of the number of observations.

• 터널과지하공간
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• 제23권2호
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• pp.110-119
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• 2013

터널 시공 중 천단침하와 내공변위를 측정하는 것이 일반화되어 있다. 터널 시공 중 계측기를 설치한 후 첫 번째로 측정한 천단침하와 내공변위의 1일간 변위량을 각각 초기천단침하속도와 초기내공변위속도로 또 마지막으로 계측한 천단침하와 내공변위를 각각 최종천단침하와 최종내공변위로 정의하고 계측한 최종변위와 초기변위속도의 관계를 분석하였다. 이를 위한 분석용 자료는 서울지하철 906공구에서 터널 시공 중 계측한 것이다. 이 터널의 폭과 높이는 각각 약 11.5 m, 10 m이며 지표에서 터널천단까지의 깊이는 약 10-20 m의 저심도 터널이다. 또 터널이 시공된 지층은 풍화토 또는 풍화암으로 연약한 지반이다. 터널은 상하반으로 나누어 시공되었고 길이는 1,820 m이다. 이번 분석에 이용한 계측치는 터널 상하반 시공 중에 얻은 것으로 천단침하계측 결과가 184개, 내공변위계측 결과는 258개이다. 분석결과 풍화토의 터널에서 초기변위속도와 최종변위가 상대적으로 큰 경향이 있었다.

• 품질경영학회지
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• 제30권4호
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• pp.68-77
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• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• Journal of information and communication convergence engineering
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• 제2권3호
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• pp.177-181
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• 2004

In this paper, we suggest an Iris recognition system with an excellent recognition rate and confidence as an alternative biometric recognition technique that solves the limit in an existing individual discrimination. For its implementation, we extracted coefficients feature values with the wavelet transformation mainly used in the signal processing, and we used neural network to see a recognition rate. However, Scale Conjugate Gradient of nonlinear optimum method mainly used in neural network is not suitable to solve the optimum problem for its slow velocity of convergence. So we intended to enhance the recognition rate by using Levenberg-Marquardt Back-propagation which supplements existing Scale Conjugate Gradient for an implementation of the iris recognition system. We improved convergence velocity, efficiency, and stability by changing properly the size according to both convergence rate of solution and variation rate of variable vector with the implementation of an applied algorithm.

• Korean Journal of Mathematics
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• 제22권4호
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• pp.671-681
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• 2014

In this paper, we consider general Beta operators, which is a general sequence of integral type operators including Beta function. We study the King type Beta operators which preserves the third test function $x^2$. We obtain some approximation properties, which include rate of convergence and statistical convergence. Finally, we show how to reach best estimation by these operators.

• 대한수학회지
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• 제33권4호
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• pp.865-878
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• 1996

We consider numerical methods for finding a solution to a nonlinear system of algebraic equations $$ (1) f(x) = 0, $$ where the function $f : R^n \to R^n$ is ain $x \in R^n$. In [10], a quasi-Gauss-Newton method is proposed and shown the computational efficiency over SQRT algorithm by numerical experiments. The convergence rate of the method has not been proved theoretically. In this paper, we show theoretically that the iterate $x_k$ obtained from the quasi-Gauss-Newton method for the problem (1) actually converges to a root by Kantorovich-type convergence analysis. We also show the rate of convergence of the method is superlinear.

• Journal of applied mathematics & informatics
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• 제14권1_2호
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• pp.329-341
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• 2004

We consider the rate of convergence for a class of perturbed hemivariational inequalities in reflexive Banach Spaces. Our results can be viewed as an extension and refinement of some previous known results in this area.

• Journal of applied mathematics & informatics
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• 제6권2호
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• pp.393-406
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• 1999

Affine invariant sufficient conditions are given for two local convergence theorems involving inexact Newton-like methods. The first uses conditions on the first Frechet-derivative whereas the second theorem employs hypotheses on the second. Radius of con-vergence as well as rate of convergence results are derived. Results involving superlinear convergence and known to be true for inexact Newton methods are extended here. Moreover we show that under hypotheses on the second Frechet-derivation our radius of convergence results are derived. Results involving superlinear convergence and known to be true or inexact Newton methods are extended here. Moreover we show that under hypotheses on the second Frechet-derivative our radius of conver-gence is larger than the corresponding one in [10]. This allows a wider choice for the initial guess. A numerical example is also pro-vided to show that our radius of convergence is larger then the one in [10].

• Journal of applied mathematics & informatics
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• 제8권2호
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• pp.345-360
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• 2001

Affine invariant sufficient conditions are given for two local convergence theorems involving inexact Newton-like methods. The first uses conditions on the first Frechet-derivative whereas the second theorem employs hypotheses on the mth(m≥2 an integer). Radius of convergence as well as rate of convergence results are derived. Results involving superlinear convergence and known to be true for inexact Newton methods are extended here. Moreover, we show that under hypotheses on the mth Frechet-derivative our radius of convergence can sometimes be larger than the corresponding one in [10]. This allows a wider choice for the initial guess. A numerical example is also provided to show that our radius of convergence is larger than the one in [10].