• 대한전자공학회논문지
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• 제25권4호
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• pp.453-459
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• 1988

A new interpolation function, named modified raised-cosine interpolation, is proposed. This function is derived from the linear combination of weighted triangular and raised-cosine functions to reduce the effect of side lobes which incur the interpolation error. Interpolation error reduces significantly for higher-order convolutional interpolation functions of linear operators, but at the expense of resolution error due to the attenuation of main lobe. However, the proposed interpolation function enables us to reduce the side lobes as well as to preserve the main lobe. To prove practicality, this function is applied in image reconstruction and enlargement.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.266-270
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• 2004

The image interpolation is one of an image preprocessing process to heighten a resolution. The conventional image interpolation used much to concept that it put in other pixel to select the nearest value in a pixel simply, and use much the temporal object interpolation techniques to do the image interpolation by detecting motion in a moving picture presently. In this paper, it is proposed the image interpolation techniques using the fuzzy wavelet base function. This is applied to embody a correct edge image and a natural image when expand part of the still image by applying the fuzzy wavelet base function coefficient to the conventional B-spline function. And the proposal algorithm in this paper is confirmed to improve about 1.2831 than the image applying the conventional B-spline function through the computer simulation.

• Journal of applied mathematics & informatics
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• 제23권1_2호
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• pp.563-570
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• 2007

There has been a considerable research interest in medical communities for neuronal fiber tracking with magnetic resonance diffusion tensor imaging(DTI). DTI data have abundant structural boundaries that need to be preserved during interpolation to facilitate fiber tracking. Sigmoid function has been used in recent papers but the sigmoid function still is not good enough to be served as an positive interpolation in mathematical point of view. In this paper, we construct and provide two families positive cardinal interpolation functions.

• Journal of applied mathematics & informatics
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• 제24권1_2호
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• pp.95-104
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• 2007

We study stationary subdivision schemes based on radial basis function interpolation. Each scheme has a tension parameter, say ${\lambda}$, which actually belongs to the radial basis function. In particular, adapted subdivision rules on bounded intervals are developed.

• 호남수학학술지
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• 제41권4호
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• pp.823-835
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• 2019

A solution for Nevanlinna-Pick interpolation problem with low complexity is constructed via non-recursive method. More precisely, a stable rational function satifying the given interpolation data in the complex right half plane is found by solving a homogeneous interpolation problem related to a minial interpolation problem for the given data in the right half plane together with its mirror-image data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.35.1-35
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• 2002

$\textbullet$ Sliding mode control (SMC) with nonlinear interpolation in variable boundary layer (VBL) is proposed $\textbullet$ A sigmoid function is used for nonlinear interpolation in VBL. $\textbullet$ The Parameter of the sigmoid function is tuned by fuzzy controller $\textbullet$ The choice of parameter for the sigmoid function is guided by FC. $\textbullet$ The parameter is continuously updated as boundary layer thickness varies. $\textbullet$ The proposed method hasbetter tracking performance than the conventional linear interpolation $\textbullet$ To demonstrate its performance the proposed control algorithm is applied to a nonlinear system.

• Journal of applied mathematics & informatics
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• 제14권1_2호
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• pp.365-376
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• 2004

The purpose of this study is to show that the accuracy of the interpolation method can be at least doubled when additional smoothness requirements and boundary conditions are met. In particular, as a basis function, we are interested in using a conditionally positive definite function $\Phi$ whose generalized Fourier transform is of the form $\Phi(\theta)\;=\;F(\theta)$\mid$\theta$\mid$^{-2m}$ with a bounded function F > 0.

• 대한전기학회논문지
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• 제40권4호
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• pp.394-401
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• 1991

B-spline function is generally used for an image interpolation because of its smoothness and continuity, but it accompanies a large amount of blurring effect. In this paper, a space-variant B-spline interpolation function is proposed through deblurring process followed by de-aliasing process. The proposed function has parametric expression and performs smoothing and edge-enhancement adaptively in the interpolation process according to local property of the image. Application of this function to image enlargement, rotation, and curve representation producted good results. Even in the presence of noise, noise smoothing effect as well as edge-enhancement were observed in the image interpolation process.

• 한국해안·해양공학회논문집
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• 제21권2호
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• pp.108-116
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• 2009

유한요소법에 사용되어 효율적으로 파랑변형을 해석할 수 있는 (Legendre 보간 함수) 방법을 소개하였다. 고차의 보간함수를 사용하는 유한요소모형은 대부분이 Lagrangian 보간 함수를 사용한다. 이 경우, 적은 수의 요소를 사용하고도 정확한 결과를 얻을 수 있다는 장점이 있지만 결과를 얻기 위해 소요되는 시간이 증가한다는 단점이 있다. Mass lumping을 통하여 계산 시간을 절약할 수는 있지만 이 경우에는 해의 정확성이 떨어진다는 단점이 있어 정확도를 향상시키기 위하여 요소의 수를 증가시켜 다시 계산시간이 증대되는 문제가 생기게 된다. 본 연구에서 Lagrangian 보간 함수의 변형된 형태인 Legendre 보간함수에 수치적분을 사용하여 mass lumping을 수행한 것과 같이 대각 행렬을 만들어 시간 절약의 효과를 얻으면서도 정확도가 어느 정도 유지되는 방법을 소개하였다. Boussinesq 방정식을 이용한 다양한 수치 계산을 통하여 본 연구에서 제안하는 방법의 우수성을 검증하였다.

• 디지털산업정보학회논문지
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• 제16권3호
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.