• 대한수학회보
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• 제54권3호
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• pp.935-952
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• 2017

It is natural to try to find a kernel such that its convolution of integrable functions converges faster than that of the $Fej{\acute{e}}r$ kernel. In this paper, we introduce a weighted Fourier partial sums which are written as the convolution of signed good kernels and prove that the weighted Fourier partial sum converges in $L^2$ much faster than that of the $Ces{\grave{a}}ro$ means. In addition, we present two numerical experiments.

• 전산구조공학
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• 제8권1호
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• pp.147-160
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• 1995

종속변수와 기본 탄성방정식의 가중잔차 근사식의 Fourier 급수 전개를 이용한 3차원 판이론을 제시하였다. 판의 가중잔차 평형방정식은 가중된 변위로 표시되며, 그 결과는 다시 위치에너지 Functional을 이용하여 유한요소해석을 수행하였다. 본 해석은 Strip판에 적용되어 2가지 예를 분석하였으며, 예제의 결과는 이론해와 잘 일치하였다.

• Kyungpook Mathematical Journal
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• 제50권4호
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• pp.545-556
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• 2010

A good amount of work has been done on degree of approximation of functions belonging to Lip${\alpha}$, Lip($\xi$(t),r) and W($L_r,\xi(t)$) and classes using Ces$\`{a}$ro, N$\"{o}$rlund and generalised N$\"{o}$rlund single summability methods by a number of researchers ([1], [10], [8], [6], [7], [2], [3], [4], [9]). But till now, nothing seems to have been done so far to obtain the degree of approximation of functions using (N,$p_n$)(C, 1) product summability method. Therefore the purpose of present paper is to establish two quite new theorems on degree of approximation of function $f\;\in\;Lip({\alpha},r)$ class and $f\;\in\;W(L_r,\;\xi(t))$ class by (N, $p_n$)(C, 1) product summability means of its Fourier series.

• 대한의생명과학회지
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• 제11권2호
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• pp.129-134
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• 2005

Three different deconvolution techniques for quantifying cerebral blood flow (CBF) from whole brain $T2^{\ast}-weighted$ bolus tracking images were implemented (parametric Fourier transform P-FT, parametric single value decomposition P-SVD and nonparametric single value decomposition NP-SVD). The techniques were tested on 206 regions from 38 hyperacute stroke patients. In the P-FT and P-SVD techniques, the tissue and arterial concentration time curves were fit to a gamma variate function and the resulting CBF values correlated very well $(CBF_{P-FT}\;=\;1.02{\cdot}CBF_{p-SVD},\;r^2\;=\;0.96)$. The NP-SVD CBF values correlated well with the P-FT CBF values only when a sufficient number of time series volumes were acquired to minimize tracer time curve truncation $(CBF_{P-FT}\;=\;0.92{\cdot}CBF_{NP-SVD},\;r^2\;=\;0.88)$. The correlation between the fitted CBV and the unfitted CBV values was also maximized in regions with minimal tracer time curve truncation $(CBV_{fit}\;=\;1.00{\cdot}CBV_{ Unfit},\;^r^2\;=\;0.89)$. When a sufficient number of time series volumes could not be acquired (due to scanner limitations) to avoid tracer time curve truncation, the P-FT and P-SVD techniques gave more reliable estimates of CBF than the NP-SVD technique.

• 한국도로학회논문집
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• 제16권5호
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• pp.59-66
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• 2014

PURPOSES : This study is to predict the Sound Pressure Level(SPL) obtained from the Noble Close ProXimity(NCPX) method by using the Extended Kalman Filter Algorithm employing the taylor series and Linear Regression Analysis based on the least square method. The objective of utilizing EKF Algorithm is to consider stochastically the effect of error because the Regression analysis is not the method for the statical approach. METHODS : For measuring the friction noise between the surface and vehicle's tire, NCPX method was used. With NCPX method, SPL can be obtained using the frequency analysis such as Discrete Fourier Transform(DFT), Fast Fourier Transform(FFT) and Constant Percentage Bandwidth(CPB) Analysis. In this research, CPB analysis was only conducted for deriving A-weighted SPL from the sound power level in terms of frequencies. EKF Algorithm and Regression analysis were performed for estimating the SPL regarding the vehicle velocities. RESULTS : The study has shown that the results related to the coefficient of determination and RMSE from EKF Algorithm have been improved by comparing to Regression analysis. CONCLUSIONS : The more the vehicle is fast, the more the SPL must be high. But in the results of EKF Algorithm, SPLs are irregular. The reason of that is the EKF algorithm can be reflected by the error covariance from the measurements.

• Journal of Astronomy and Space Sciences
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• 제25권1호
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• pp.1-18
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• 2008

이 연구에서는 장주기 변광쌍성 ${\in}$ Aurigae의 주성에 대한 측광 관측자료를 바탕으로 그 별의 변광주기를 분석하였다. 이를 위하여 1842년부터 2006년까지 약 160여년에 걸쳐서 여러 관측소에서 관측된 자료를 이용하였다. 식 바깥 부분의 자료를 선별하여 CLEANest와 Wavelet 알고리즘으로 주기를 분석한 결과 ${\in}$ Aurigae의 주성 F별은 시간에 따라서 진폭이 변하기는 하지만 몇개의 특정 주파수가 일정하게 유지되는 진동 특성을 가지고 있음을 알 수 있었다. 특히 두 개의 주기(67일과 123일)가 지속적으로 나타난 것은 지금까지 부분적으로 주기를 구하였던 결과에서 주기가 시간에 따라서 불규칙하게 변한다고 판단되어졌던 것과는 달리 ${\in}$ Aurigae의 주성이 이중 모드 또는 다주기적 변광을 하고 있다는 것을 말해준다고 하겠다. 이는 ${\in}$ Aurigae의 주성이 post-AGB의 단계에 있다기 보다는 질량이 큰 초거성 상태임을 암시하는 결과라고도 할 수 있다. 또한 황색 초거성의 변광기작에 대해 명확하게 이해되지 못하고 있는 현재의 입장에서 ${\in}$ Aurigae의 식 바깥부분에서의 추가적인 관측이 필요함을 논의하였다.