• 충청수학회지
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• 제27권2호
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• pp.211-218
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• 2014

In 3-dimensional Euclidean space, the geometric figures of a regular curve are completely determined by the curvature function and the torsion function of the curve, and surfaces are the fundamental curved spaces for pioneering study in modern geometry as well as in classical differential geometry. In this paper, we define parametrizations for surface by using parametric functions whose images are in the normal plane of each point on a given curve, and then obtain some results relating the Gaussian curvature of the surface with curvature and torsion of the given curve. In particular, we find some conditions for the surface to have either nonpositive Gaussian curvature or nonnegative Gaussian curvature.

• Transactions on Electrical and Electronic Materials
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• 제17권5호
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• pp.270-274
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• 2016

This article investigates the use of the Gaussian-channel doping profile for the control of the short-channel effects in the double-gate MOSFET whereby a two-dimensional (2D) quantum simulation was used. The simulations were completed through a self-consistent solving of the 2D Poisson equation and the Schrodinger equation within the non-equilibrium Green’s function (NEGF) formalism. The impacts of the p-type-channel Gaussian-doping profile parameters such as the peak doping concentration and the straggle parameter were studied in terms of the drain current, on-current, off-current, sub-threshold swing (SS), and drain-induced barrier lowering (DIBL). The simulation results show that the short-channel effects were improved in correspondence with incremental changes of the straggle parameter and the peak doping concentration.

• 반도체디스플레이기술학회지
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• 제11권3호
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• pp.19-25
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• 2012

The accuracy of Shape From Focus (SFF) technique depends on the quality of the focus measurements which are computed through a focus measure operator. In this paper, we introduce a new approach to estimate 3D shape of an object based on Gaussian process regression. First, initial depth is estimated by applying a conventional focus measure on image sequence and maximizing it in the optical direction. In second step, input feature vectors consisting of eginvalues are computed from 3D neighborhood around the initial depth. Finally, by utilizing these features, a latent function is developed through Gaussian process regression to estimate accurate depth. The proposed approach takes advantages of the multivariate statistical features and covariance function. The proposed method is tested by using image sequences of various objects. Experimental results demonstrate the efficacy of the proposed scheme.

• 대한수학회지
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• 제53권5호
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• pp.991-1017
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• 2016

In this paper we define a generalized analytic Fourier-Feynman transform associated with Gaussian process on the function space $C_{a,b}[0,T]$. We establish the existence of the generalized analytic Fourier-Feynman transform for certain bounded functionals on $C_{a,b}[0,T]$. We then proceed to establish a translation theorem for the generalized transform associated with Gaussian process.

• 융합신호처리학회논문지
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• 제10권1호
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• pp.60-65
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• 2009

본 논문에서는 Chebychev 항등식과 Bessel 계수로부터 유도 될 수 있는 새로운 지수펄스모형함수를 제안하고 그 특성을 고찰한다. 제안된 지수펄스모형함수는 매개변수 변화에 따라 시간과 주파수영역에서 서로 다른 특성을 갖는 다양한 펄스 모형함수를 발생시킬 수 있다. 그리고 지수펄스모형함수의 미분함수로부터 여러 형태를 갖는 새로운 펄스모형함수를 얻을 수 있다. 미분으로부터 얻어지는 지수펄스함수의 짝수 계와 홀수 계 미분 함수간은 직교성을 유지한다. 이러한 기본적인 특성을 통상적인 Gaussian 펄스 모형함수와 비교 분석함으로써 그 유용성을 확인한다. 통신시스템의 요구 설계조건에 따라 최적의 지수펄스파형을 선택하여 사용할 수 있다.

• Journal of Magnetics
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• 제2권3호
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• pp.105-109
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• 1997

The Preisach model neds a density function or Everett function for the hysterisis operator to simulate the hysteresis phenomena. To obtain the function, many experimental data for the first order transition curves are required. However, it needs so much efforts to measure the curves, especially for the hard magnetic materials. By the way, it is well known that the density function has the Gaussian distribution for the interaction axis on the Preisach plane. In this paper, we propose a simple technique to determine the distribution function or Everett function analytically. The initial magnetization curve is used for the distribution of the Everett function for the coercivity axis. A major, minor loop and the initial curve are used to get the Everett function for the interaction axis using the Gaussian distribution function and acceptable results were obtained.

• 충청수학회지
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• 제26권2호
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• pp.411-420
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• 2013

We consider fractional Gussian noise and FARIMA sequence with Gaussian innovations and show that the suitably scaled distributions of the FARIMA sequences converge to fractional Gaussian noise in the sense of finite dimensional distributions. Finally, we figure out ACF function and estimate the self-similarity parameter H of FARIMA(0, $d$, 0) by using R/S method.

• 호남수학학술지
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• 제34권3호
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• pp.341-349
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• 2012

In this paper, we discuss a constructive approximation by Gaussian neural networks. We show that it is possible to construct Gaussian neural networks with integer weights that approximate arbitrarily well for functions in $C_c(\mathbb{R}^s)$. We demonstrate numerical experiments to support our theoretical results.

• 대한수학회지
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• 제42권6호
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• pp.1265-1278
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• 2005

In this paper, we establish limit theorems containing both the moduli of continuity and the large incremental results for finite dimensional Gaussian processes with N parameters, via estimating upper bounds of large deviation probabilities on suprema of the Gaussian processes.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.515-527
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• 1996

It has been known for mean field models that the limiting distribution reflecting the asymptotic behavior of the system is non-Gaussian at the critical state. Recently, however, Papangelow showed for the critical Curie-Weiss mean field model that there exist Gaussian structures in the asymptotic behavior of the total magnetization. We construct Gaussian structures existing in the internal fluctuation of the system for the critical case of a generalized Curie-Weiss mean field model.