• Journal of Korea Multimedia Society
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• 제3권5호
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• pp.542-549
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• 2000

This Paper presents the development of multiresolution model for the analysis and visualization of two-dimensional flows over curvilinear grids. Multiresolution analysis provides a useful and efficient tool to represent shape and to analyze features at multiple level of detail. Applying multiresolution analysis to vector field visualization is very useful and powerful as the vector field's data sets are usually huge and complex. Using approximation at lower resolution, brief outline of topology can be extracted in short periods of time. Local reconstruction allows the user to zoom in or out, only by reconstructing the portion of interest. This new model is based upon nested spaces of piecewise defined function over nested curvilinear grid domains. The nested domains are selected so as to maintain the original geometry of the inner boundary. This paper presents the refinement and decomposition equations for Haar wavelet over these domains and shows some examples.

• Structural Engineering and Mechanics
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• 제33권2호
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• pp.179-191
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• 2009

This paper is aimed at combining wavelet multiresolution analysis and nonstationary Kanai-Tajimi model for the simulation of earthquake accelerograms. The proposed approach decomposes earthquake accelerograms using wavelet multiresolution analysis for the simulation of earthquake accelerograms. This study is on the basis of some Iranian earthquake records, namely Naghan 1977, Tabas 1978, Manjil 1990 and Bam 2003. The obtained results indicate that the simulated records preserve the significant properties of the actual accelerograms. In order to investigate the efficiency of the model, the spectral response curves obtained from the simulated accelerograms have been compared with those from the actual records. The results revealed that there is a good agreement between the response spectra of simulated and actual records.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 한국조명전기설비학회 2000년도 학술대회논문집
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• pp.183-187
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• 2000

This paper deals with multiresolution analysis of wavelet transform for partial discharge(PD), both corona and surface discharge. Multiresolution analysis was used for performing discrete wavelet transform. PD signals was decomposed into "approximation" and "detail" components until 4 levels by using discrete wavelet analysis. In this paper, daubechies family is adopted for the research of the characteristics of PD signals. The results show that in corona discharge the segment 7, 8, 9, 10, 11 values of defined variable is increased with discharge process, so phase distribution is characterized by 210~330 ranges. In case surface discharge in expoxy insulator inserted, defined variable values is fairly symmetric discharge pattern because coupled both corona and dielectric bounded discharges. We can confirmly discriminate the type PD source. the type PD source.

• KIEE International Transactions on Power Engineering
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• 제11A권4호
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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.

• KIEE International Transactions on Power Engineering
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• 제3A권3호
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• pp.130-138
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• 2003

This paper presents a discrete wavelet transform approach for determining the beginning and end times of voltage sags. Firstly, investigations in the use of some typical mother wavelets, namely Daubechies, Symlets, Coiflets and Biorthogonal are carried out and the most appropriate mother wavelet is selected. The proposed technique is based on utilizing the maximum value of Dl (at scale 1) coefficients in multiresolution analysis (MRA) based on the discrete wavelet transform. The results are compared with other methods for determining voltage sag duration, such as the Root Mean Square (RMS) voltage and Short Time Fourier Transform (STFT) methods. 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.

• Proceedings of the KSME Conference
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• 대한기계학회 2003년도 추계학술대회
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• pp.1291-1296
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• 2003

The objective of the present research is to develop a wavelet-based multiscale adaptive Galerkin method for membrane eigenvalue analysis. Since approximate eigensolutions at a certain resolution level can be good guesses, which play an important role in typical iterative solvers, at the next resolution level, the multiresolution iterative solution approach by wavelets can improve the solutionconvergence rate substantially. The intrinsic difference checking nature of wavelets can be also utilized effectively to develop an adaptive strategy. The present wavelet-based approach will be implemented for the simplest vector iteration method, but some important aspects, such as convergence speedup, and the reduction in the number of nodes can be clearly demonstrated.

• Korean Journal of Computational Design and Engineering
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• 제6권3호
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• pp.184-192
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• 2001

In this paper we present a remeshing algorithm for irregular meshes with boundaries. The irregular meshes are approximated by regular meshes where the topological regularity is essential for the multiresolutional analysis of the given meshes. Normal meshes are utilized to reduce the necessary data size at each resolution level of the regularized meshes. The normal mesh uses one scalar value, i.e., normal offset value which is based on the regular rule of a uniform subdivision, while other remeshing schemes use one 3D vector at each vertex. Since the normal offset cannot be properly used for the boundaries of meshes, we use a combined subdivision scheme which resolves a problem of the proposed normal offset method at the boundaries. Finally, we show an example to see the effectiveness of the proposed scheme to reduce the data size of a mesh model.

• Journal of the Korean Mathematical Society
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• 제42권2호
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• pp.305-334
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• 2005

The objective of this study is to analyze the decay characteristics of the hat interpolation wavelet coefficients of some smooth functions defined in a two-dimensional space. The motivation of this research is to establish some fundamental mathematical foundations needed in justifying the adaptive multiresolution analysis of the hat-interpolation wavelet-Galerkin method. Though the hat-interpolation wavelet-Galerkin method has been successful in some classes of problems, no complete error analysis has been given yet. As an effort towards this direction, we give estimates on the decaying ratios of the wavelet coefficients at children interpolation points to the wavelet coefficient at the parent interpolation point. We also give an estimate for the difference between non-adaptively and adaptively interpolated representations.

• Bulletin of the Korean Mathematical Society
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• 제47권3호
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• pp.563-573
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• 2010

Using the fiberization technique of a shift-invariant space and the matrix characterization of the decomposition of a shift-invariant space of finite length into an orthogonal sum of singly generated shift-invariant spaces, we show that the main result in [13] can be interpreted as a statement about the length of a shift-invariant space, and give a more natural construction of multiwavelet frames from a frame multiresolution analysis of $L^2(\mathbb{R}^d)$.

• Structural Engineering and Mechanics
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• 제28권2호
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• pp.153-166
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• 2008

This paper suggests the use of wavelet multiresolution analysis (WMRA) and neural network for generation of artificial earthquake accelerograms from target spectrum. This procedure uses the learning capabilities of radial basis function (RBF) neural network to expand the knowledge of the inverse mapping from response spectrum to earthquake accelerogram. In the first step, WMRA is used to decompose earthquake accelerograms to several levels that each level covers a special range of frequencies, and then for every level a RBF neural network is trained to learn to relate the response spectrum to wavelet coefficients. Finally the generated accelerogram using inverse discrete wavelet transform is obtained. An example is presented to demonstrate the effectiveness of the method.