• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.551-562
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• 1995

We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

• Journal of applied mathematics & informatics
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• v.38 no.5_6
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• pp.559-577
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• 2020

We present uniform and L_p left Caputo-Bochner abstract iterated fractional Landau inequalities over ℝ₊. These estimate the size of second and third iterated left abstract fractional derivates of a Banach space valued function over ℝ₊. We give an application when the basic fractional order is ${\frac{1}{2}}$.

• Honam Mathematical Journal
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• v.38 no.1
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• pp.169-212
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• 2016

Entire functions have been investigated so popularly to have been divided into a large number of specialized subjects. Even the limited subject of entire functions is too vast to be dealt with in a single volume with any approach to completeness. Here, in this paper, we choose to investigate certain interesting results associated with the comparative growth properties of iterated entire functions using (p, q)-th order and (p, q)-th lower order, in a rather comprehensive and systematic manner.

• Bulletin of the Korean Mathematical Society
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• v.43 no.4
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• pp.791-804
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• 2006

This paper is concerned with a second-order iterated differential equation of the form $c_0x'(Z)+c_1x'(z)+c_2x(z)=x(az+bx(z))+h(z)$ with the distinctive feature that the argument of the unknown function depends on the state. By constructing a convergent power series solution of an auxiliary equation, analytic solutions of the original equation are obtained.

• Korean Journal of Mathematics
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• v.26 no.4
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• pp.629-663
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• 2018

Let us suppose that ${\mathbb{K}}$ be a complete ultrametric algebraically closed field and $\mathcal{A}$ (${\mathbb{K}}$) be the ${\mathbb{K}}$-algebra of entire functions on K. The main aim of this paper is to study some newly developed results related to the growth rates of iterated p-adic entire functions on the basis of their relative orders, relative type and relative weak type.

• Kyungpook Mathematical Journal
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• v.62 no.2
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• pp.389-405
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• 2022

We study the Fisher Information (FI) of m-generalized order statistics (m-GOSs) and their concomitants about the shape-parameter vector of the Iterated Farlie-Gumbel-Morgenstern (IFGM) bivariate distribution. We carry out a computational study and show how the FI matrix (FIM) helps in finding information contained in singly or multiply censored bivariate samples from the IFGM. We also run numerical computations about the FIM for the sub-models of order statistics (OSs) and sequential order statistics (SOSs). We evaluate FI about the mean and the shape-parameter of exponential and power distributions, respectively. Finally, we investigate the Kullback-Leibler distance in concomitants of m-GOSs.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.125-128
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• 2000

The conventional fractal decoding was required a vast amount computational complexity. Since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested to that each range block was classified to iterated and non-iterated regions. If IFS region is contractive, then it can be performed a fast decoding. In this paper, a searched region of the domain in the encoding is limited to the range region that is similar with the domain block, and IFS region is a minimum. So, it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2091-2101
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• 1997

Conventional method for fractal image decoding requires high-degree computational complexity in decoding propocess, because of iterated contractive transformations applied to whole range blocks. In this paper, we propose a fast decoding algorithm of fractal image using data depence in order to reduce computational complexity for iterated contractive transformations. Range of reconstruction image is divided into a region referenced with domain, called referenced range, and a region without reference to domain, called unreferenced range. The referenced range is converged with iterated contractive transformations, and the unreferenced range can be decoded by convergence of the referenced range. Thus the unreferenced range is called data dependence region. We show that the data dependence region can be deconded by one transformation when the referenced range is converged. Consequently, the proposed method reduces computational complexity in decoding process by executing iterated contractive transformations for the referenced range only.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.13-19
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• 2001

The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Kyungpook Mathematical Journal
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• v.48 no.1
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• pp.123-132
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• 2008

In this paper, we investigate higher-order linear differential equations with entire coefficients of iterated order. We improve and extend the result of L. Z. Yang by using the estimates for the logarithmic derivative of a transcendental meromorphic function due to Gundersen and the extended Wiman-Valiron theory by Wang and Yi. We also consider the nonhomogeneous linear differential equations.