• Communications of the Korean Mathematical Society
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• v.12 no.1
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• pp.59-67
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• 1997

Let $K'_M$ be the space of distributions on $R^m$ which grow no faster than $e^{M(kx)}$ for some k > 0 and an index function M(x) and $K'_M$ be the Fourier transform of $K'_M$. We establish the characterizations of the space $O_M(K'_m;K'_M)$ of multipliers in $K'_M$.

• Bulletin of the Korean Mathematical Society
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• v.50 no.5
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• pp.1659-1671
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• 2013

In this paper, we are concerned with the analysis of the waiting time distribution in the M/M/m retrial queue. We give expressions for the Laplace-Stieltjes transform (LST) of the waiting time distribution and then provide a numerical algorithm for calculating the LST of the waiting time distribution. Numerical inversion of the LSTs is used to calculate the waiting time distribution. Numerical results are presented to illustrate our results.

• Communications of the Korean Mathematical Society
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• v.32 no.3
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• pp.779-787
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• 2017

Let m be the Lebesgue measure on ${\mathbb{C}}$ normalized to $m(D)=1,{\mu}$ be an invariant measure on D defined by $d_{\mu}(z)=(1-{\mid}z{\mid}^2)^{-2}dm(z)$. For $f{\in}L^1(D^n,m{\times}{\cdots}{\times}m)$, Bf the Berezin transform of f is defined by, $$(Bf)(z_1,{\ldots},z_n)={\displaystyle\smashmargin{2}{\int\nolimits_D}{\cdots}{\int\nolimits_D}}f({\varphi}_{z_1}(x_1),{\ldots},{\varphi}_{z_n}(x_n))dm(x_1){\cdots}dm(x_n)$$. We prove that if $f{\in}L^1(D^2,{\mu}{\times}{\mu})$ is radial and satisfies ${\int}{\int_{D^2}}fd{\mu}{\times}d{\mu}=0$, then for every bounded radial function ${\ell}$ on $D^2$ we have $$\lim_{n{\rightarrow}{\infty}}{\displaystyle\smashmargin{2}{\int\int\nolimits_{D^2}}}(B^nf)(z,w){\ell}(z,w)d{\mu}(z)d{\mu}(w)=0$$. Then, using the above property we prove n-harmonicity of bounded function which is invariant under the Berezin transform. And we show the same results for the weighted the Berezin transform in the polydisc.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.29-37
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the diagnosis of grinding conditions in grinding process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. STD11 workpiece was 85 times of machined pieces cut by the WA wheel and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At dressing time, the approximation signals were slowly increased and 45 machined times noticed dressing time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1063-1066
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• Nonlinear Functional Analysis and Applications
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• v.28 no.4
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• pp.1069-1086
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• 2023

The natural transform is represented by two (p, q)-analogues, and their comparative characteristics are established. To resolve some (p, q)-difference and functional equations, applications are carried out.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.275-279
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• 1998

In this paper, the authors propose a new method for improving identification method of linear system by us-ing M-transform. The authors has recently proposed a new mettled for linear system identification by use of M-transform. In this method, the input signal n(i) must have the same period N as that of the M-sequence. When N becomes large, it will take a long time to compute. To overcome this difficulty, we propose a new approach of system identification by using a small size matrix. The results of simulation show a good agreement with the theoretical considerations.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.37-43
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• 2016

This note discusses the inter-loss time ofan M/G/1/1 queuing system. The inter-loss time is defined as the time duration between two consecutive losses of arriving customers. In this study, we present the explicit Laplace transform of the inter-loss time distribution of an M/G/1/1 queuing system.

• Journal of Broadcast Engineering
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• v.14 no.5
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• pp.543-550
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• 2009

The most widely used block convolution method is the overlap save algorithm (OSA), where a block of M data to be convolved with a filter is concatenated with the previous block and 2M-point FFT and multiplications are performed for this overlapped block. By discarding half of the results, we obtain linear convolution results from the circular convolution. This paper proposes a new transform which reduces the block size to only M for the block convolution. The proposed transform can be implemented as the M multiplications followed by M-point FFT Hence, existing efficient FFT libraries and hardware can be exploited for the implementation of proposed method. Since the required transform size is half that of the conventional method, the overall computational complexity is reduced. Also the reduced transform size results in the reduction of data access time and cash miss-hit ratio, and thus the overall CPU time is reduced. Experiments show that the proposed method requires less computation time than the conventional OSA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.59-68
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• 2009

This paper addresses a hybrid multi-focus image fusion scheme using the recent curvelet transform constructions. Hybridization is obtained by combining the MS fusion rule with a novel "copy" method. The proposed scheme use MS rule to fuse the m most significant terms in spectrum of an image at each decomposition level. The scheme is dubbed in this work as m-term fusion in adherence to its use of the MSC (most significant coefficients) in the transform set at any given scale, orientation, and translation. We applied the edge-sensitive objective quality measure proposed by Xydeas and Petrovic to evaluate the method. Experimental results show that the proposed scheme is a potential alternative to the redundant, shift-invariant Dual-Tree Complex Wavelet transforms. In particular, it was confirmed that a 50% m-term fusion produces outputs with no visible quality degradation.