• Journal of KIISE:Databases
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• v.32 no.4
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• pp.345-361
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• 2005

A transform-space index indexes objects represented as points in the transform space An advantage of a transform-space index is that optimization of join algorithms using these indexes becomes relatively simple. However, the disadvantage is that these algorithms cannot be applied to original-space indexes such as the R-tree. As a way of overcoming this disadvantages, the authors earlier proposed the transform-space view join algorithm that joins two original- space indexes in the transform space through the notion of the transform-space view. A transform-space view is a virtual transform-space index that allows us to perform join in the transform space using original-space indexes. In a transform-space view join algorithm, the order of accessing disk pages -for which various space filling curves could be used -makes a significant impact on the performance of joins. In this paper, we Propose a new space filling curve called the adaptive row major order (ARM order). The ARM order adaptively controls the order of accessing pages and significantly reduces the one-pass buffer size (the minimum buffer size required for guaranteeing one disk access per page) and the number of disk accesses for a given buffer size. Through analysis and experiments, we verify the excellence of the ARM order when used with the transform-space view join. The transform-space view join with the ARM order always outperforms existing ones in terms of both measures used: the one-pass buffer size and the number of disk accesses for a given buffer size. Compared to other conventional space filling curves used with the transform-space view join, it reduces the one-pass buffer size by up to 21.3 times and the number of disk accesses by up to $74.6\%$. In addition, compared to existing spatial join algorithms that use R-trees in the original space, it reduces the one-pass buffer size by up to 15.7 times and the number of disk accesses by up to $65.3\%$.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.1-8
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• 2001

This paper presents a discrete wavelet transform approach for detecting voltage sags initialized by fault conditions and starting of larger motors. The proposed technique is based on utilizing the summation value of D1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. In this paper, the proposed technique is tested under various cases of voltage sags. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• Information and Communications Magazine
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• v.11 no.8
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• pp.60-77
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• 1994

This paper presents a survey of video coding schemes which use wavelet transform for the videophone on very low bit rate commun ication chan nel( ego 10 Kbps Public Service Telephone Network). Firstly, we introduce the standardization efforts to make the low bit rate videophone architecture and the typical application of low bit rate video coding scheme. Secondly, we summarize the several requirements on videophone, delay, encoder/decoder complexity, low bitrate, and progressive transmission capability. Third, we review the basic theory of wavelet transform without much mathematics. We compare the wavelet transform with short-time fourier transform and subband filters. Fourth, we summarize the video coding schemes proposed so far, and evaluate them with Ule requirements. Lastly, we conclude with fu¬ture research directions.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.302-305
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• 2005

Recently, many methods to analyze signal have been proposed and representative methods are the Fourier transform and wavelet transform. In these methods, the Fourier transform represents signal with combination cosine and sine at all locations in the frequency domain. However, it doesn't provide time information that particular frequency occurs in signal and denpends on only the global feature of the signal. So, to improve these points the wavelet transform which is capable of multiresolution analysis has been applied to many fields such as speech processing, image processing and computer vision. And the wavelet transform, which uses changing window according to scale parameter, presents time-frequency localization. In this paper, we proposed a new approach using a wavelet of cosine and sine type and analyzed features of signal in a limited point of frequency-time plane.

• Journal of applied mathematics & informatics
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• v.31 no.1_2
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• pp.165-177
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• 2013

In this paper, we apply Homotopy perturbation transform method (HPTM) for solving singular fourth order parabolic partial differential equations with variable coefficients. This method is the combination of the Laplace transform method and Homotopy perturbation method. The nonlinear terms can be easily handled by the use of He's polynomials. The aim of using the Laplace transform is to overcome the deficiency that is mainly caused by unsatisfied conditions in other semi-analytical methods such as Homotopy perturbation method (HPM), Variational iteration method (VIM) and Adomain Decomposition method (ADM). The proposed scheme finds the solutions without any discretization or restrictive assumptions and avoids the round-off errors. The comparison shows a precise agreement between the results and introduces this method as an applicable one which it needs fewer computations and is much easier and more convenient than others, so it can be widely used in engineering too.

• Korean Journal of Mathematics
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• v.9 no.2
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• pp.133-147
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• 2001

In this paper, we introduce the concepts of multiple $L_p$ analytic Fourier-Feynman transform ($1{\leq}p$ < ${\infty})$ and a convolution product of functionals on abstract Wiener space and verify the existence of the multiple $L_p$ analytic Fourier-Feynman transform for functionls in the Fresnel class. Moreover, we verify that the Fresnel class is closed under the $L_p$ analytic Fourier-Feynman transformation and the convolution product, respectively. And we establish some relationships among the multiple $L_p$ analytic Fourier-Feynman transform and the convolution product on the Fresnel class.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1662-1665
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• 2004

A real-time joint transform correlator by using JPEG-compressed reference images is proposed as practical solution to storage problem and improvement of processing time of automatic target recognition system [1]. Effects of compression on recognition performance of join transform correlator are quantitatively investigated under situations where the target is suffered from noise and has contrast difference with respect to the reference. Two images with different spatial-frequency contents and contrast were used as the test scenes. The simulation results show that, the recognition performance of joint transform correlator by using the compressed reference images with high spatial-frequency components is more sensitive to noise and contrast difference than the low spatial-frequency image.

• Journal of the Chungcheong Mathematical Society
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• v.19 no.1
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• pp.79-99
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• 2006

In this paper, we define a class of functional defined on a very general function space $C_{a,b}[0,T]$ like a Fresnel class of an abstract Wiener space. We then define the multiple $L_p$ analytic generalized Fourier-Feynman transform and the generalized convolution product of functionals on function space $C_{a,b}[0,T]$. Finally, we establish some relationships between the multiple $L_p$ analytic generalized Fourier-Feynman transform and the generalized convolution product for functionals in $\mathcal{F}(C_{a,b}[0,T])$.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.89-92
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• 2000

In this paper, an effective image restoration using Genetic Algorithm(GA) in wavelet transform region is proposed. First, a wavelet transform is used for decomposition of a blurred image with white Gaussian noise as a preprocessing of the proposed method. The wavelet transform decomposes a degraded image into a wavelet subband coefficient planes. In this wavelet transformed subband coefficient planes, three highest subbands is composed entirely of noise elements on a degraded image. So, these subbands are removed. And remained subbands except for the lowest subband are individually applied to GA. For the performance evaluation, the proposed method is compared with a conventional single GA algorithm and a conventional hybrid method of wavelet transform and GA for a Lenna image and a boat image. As an experimental result, the proposed algorithm is prior to a conventional methods as each PSNR 3.4dB, 1.3dB.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.49-52
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• 2000

This paper is to propose an algorithm to reduce the calculation time to perform the 2-dimensional Discrete Wavelet Transform(2DWT). We call this algorithm as Reduced 2-dimensional Discrete Wavelet Transformation(R2DWT). This algorithm uses a modified Mallat-tree such that in each level, the column transform is performed only with the low-pass filtered row transform result. The resulting number of sub-band regions is 2L＋1, meanwhile the original(2DWT) has 3L＋1 sub-regions, where L is the transform level. To show the proposed algorithm is useful without much loss in SNR(Signal-to-Noise Ratio), we performed experiments with various images. The results showed that above 5:1 in compression ratio, the proposed algorithm has less than 0.SdB difference in SNR from 2DWT with about 25% reduction in calculation time.