• Korean Journal of Mathematics
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• v.14 no.1
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• pp.35-46
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• 2006

The concept of convolution is a fundamental mathematical concept in a wide variety of disciplines and applications including probability, image processing, physics, and many more. The visualization of convolution for the continuous case is generally predetermined. On the other hand, the convolution structure embedded in the discrete case is often subtle and its visualization is non- trivial. This paper purports to develop the CAS techniques in visualizing the logical structure in the concept of a discrete convolution.

• Bulletin of the Korean Mathematical Society
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• v.48 no.2
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• pp.223-245
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• 2011

In this paper, we de ne an $L_p$ analytic generalized Fourier Feynman transform and a convolution product of functionals in a Ba-nach algebra $\cal{F}$($C_{a,b}$[0, T]) which is called the Fresnel type class, and in more general class $\cal{F}_{A_1;A_2}$ of functionals de ned on general functio space $C_{a,b}$[0, T] rather than on classical Wiener space. Also we obtain some relationships between the $L_p$ analytic generalized Fourier-Feynman transform and convolution product for functionals in $\cal{F}$($C_{a,b}$[0, T]) and in $\cal{F}_{A_1,A_2}$.

• Bulletin of the Korean Mathematical Society
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• v.48 no.5
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• pp.1003-1014
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• 2011

Motivated by the convolution product of white noise functionals, we introduce a new notion of convolution products of white noise operators. Then we study several interesting relations between the convolution products and the quantum generalized Fourier-Mehler transforms, and study a quantum-classical correspondence.

• Korean Journal of Mathematics
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• v.20 no.1
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• pp.1-18
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• 2012

We study various relationships that exist among generalized conditional integral transform, generalized conditional convolution and generalized first variation for a class of functionals defined on K[0, T], the space of complex-valued continuous functions on [0, T] which vanish at zero.

• Journal for History of Mathematics
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• v.21 no.1
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• pp.97-108
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• 2008

In this paper, we investigate the analytic Feynman integral, the analytic Fourier-Feynman transform and convolution product on Wiener space. We then consider various results between these concepts.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.341-348
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• 1990

This paper describes an algorithm for evaluating the Loss of Load Probability (LOLP) and calculating the production cost for all the generators in the system using Fast Hartley Transform (FHT). It also suggests the deconvolution procedure which is necessary for the generation expansion planning. The FHT is as fast as or faster than the Fast Fourier Transform (FFT) and serves for all the uses such as spectral, digital processing, and convolution to which the FFT is normally applied. The transformed function using FFT has complex numbers. However, the transformed function using FHT has real numbers and the convolution become quite simple. This method has been applied for the IEEE reliability test system and practical size model system. The test results show the effectiveness of the proposed method.

• MALSORI
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• no.47
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• pp.85-96
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• 2003

It is difficult to implement sound field effect on real time using linear convolution in time domain because linear convolution needs much multiply operations. In this paper three ways is introduced to reduce multiplication operations. Firstly, linear convolution in time domain is replaced with circular convolution in frequency domain. It means that it operates multiplication in place of convolution. Secondly, one frame will be divided into several frames. It will reduce the multiplication operation in processing that transforms time domain into frequency domain. Finally, QFT will be used in place of FFT. Three ways result much reduction in multiplication operations. The reduction of the multiplication operation makes the real time implementation possible.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.17-36
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• 1998

The Radon transform has been widely used in various techniques of digital image processing such as the computerized topography, lineament analysis in a remotely sensed image, slant-stack processing of seismic data, and so on. Compared to the Fourier transform, the utility of two-dimensional convolutional or correlational properties of the Radon transform, however, has been underestimated. We show that the two-dimensional convolution and correlation is respectively reduced to be one-dimensional convolution and correlation with respect to ρ in the Radon space. Therefore, one can achieve a two dimensional filtering by applying a simple one-dimensional convolution in the Radon space followed by an inverse Radon transform. Tests of the approach using FIR filters are carried out specifically for enhancing the ship wake in a RADARSAT SAR image. The test results demonstrate that the two-dimensional filtering through the Radon transform effectively enhance the ship wake features as well as reducing sea speckle in the image. Although two-dimensional convolution and correlation through the Radon transform are not so much useful as those through the courier transform in views of efficiency and effectiveness, it can be utilized to improve the quality of a digitally processed output when the process should be accompanied by the Radon transform such as topography and lineament analysis of SAR image.

• Journal of the Korean Mathematical Society
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• v.40 no.6
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• pp.999-1014
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• 2003

For a fixed function h we deal with a class of convolution transforms $f\;{\rightarrow}\;f\;*\;h$, where $(f\;*\;h)(x)\;=\frac{1}{2x}\;{\int_{{R_{+}}^2}}^{e^1{\frac{1}{2}}(x\frac{u^2+y^2}{uy}+\frac{yu}{x})}\;f(u)h(y)dudy,\;x\;\in\;R_{+}$ as integral operators $L_p(R_{+};xdx)\;\rightarrow\;L_r(R_{+};xdx),\;p,\;r\;{\geq}\;1$. The Young type inequality is proved. Boundedness properties are investigated. Certain examples of these operators are considered and inversion formulas in $L_2(R_{+};xdx)$ are obtained.

• Korean Journal of Mathematics
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• v.8 no.2
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• pp.187-191
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• 2000

In the present paper we shall first introduce the timewidth of a signal, and then we shall investigate the relation between the timewidths of a signal $f$ and of the convolution $f*h$ for some other signal $h$.