• Journal of the Korean earth science society
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• v.33 no.5
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• pp.408-421
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• 2012

The objective of this paper is to apply a newly developed wavelet-based semblance filtering and eigenvalue analysis to investigate the geomagnetic variations in some micro-earthquakes that had occurred in the Korean Peninsula. The wavelet-based filtering showed improved results in delineating the geomagnetic variations in relation to earthquake events from their background field. In addition, the eigenvalues analysis was also useful for the interpretation of three components geomagnetic fields during the earthquake events. The wavelet-based semblance analysis showed a prominent result for short-term geomagnetic variation related to the earthquake event, and the eigenvalue analysis was feasible to long-term geomagnetic variation. Considering the fact that the basement rock of the Korean Peninsula has a highly resistive electrical structure, it seems to be possible for small magnitude earthquakes to generate some distinguished geomagnetic variations.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.143-150
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• 2002

This paper presents the application of continuous wavelet transform for determination of dynamic parameters of continuous beam subjected to moving load. Morlet wavelet is used as mother wavelet in wavelet transform. Dynamic parameters are estimated from the magnitudes and arguments of the wavelet coefficients obtained by wavelet transforming the response time histories of joints on the beam. This study shows that the estimated parameters such as natural frequencies, dmping ratios and mode shapes are to be well-compared with those of the finite element analysis.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.145-147
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• 2003

The wavelet transform has attracted considerable attention in the field of power quality analysis recently. This paper discuss the voltage sag and harmonic disturbances by using wavelet analysis. A discrete wavelet-based approach is applied for determining the characteristics of these disturbances.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.831-842
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• 1999

We propose a wavelet decomposition feature extraction method for the hand-written character recognition. Comparing the recognition rates of which methods with original image features and with selected features by the wavelet decomposition we study the characteristics of the proposed method. LDA(Linear Discriminant Analysis) QDA(Quadratic Discriminant Analysis) RDA(Regularized Discriminant Analysis) and NN(Neural network) are used for the calculation of recognition rates. 6000 hand-written numerals from CENPARMI at Concordia University are used for the experiment. We found that the set of significantly selected wavelet decomposed features generates higher recognition rate than the original image features.

• The Pure and Applied Mathematics
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• v.12 no.4 s.30
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• pp.237-251
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• 2005

In this paper, a new wavelet analysis of differential operator spline is generated, and it is of the symmetry and (3 -$\epsilon$ )-order regula.ity (0 < $\epsilon$ < 3). Finally, using this wavelet basis, we expand Lebesgue square integrable functions efficiently and quickly.

• Bulletin of the Korean Mathematical Society
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• v.38 no.3
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• pp.517-526
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• 2001

In this paper, we study the continuous wavelet transform on the Heisenberg group H$^n$, and describe the related continuous multiscale analysis. By using the wavelet packet transform we obtain a reconstruction formula on L$^2$(H$^n$).

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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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 Korean Geotechical Society Conference
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• 2003.03a
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• pp.309-314
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• 2003

Impact Echo method has been successful in detecting a variety of defects in concrete structure. This study has the objectives to show important aspects of applying the Discrete Wavelet Transform(DWT) to signal processing of Modified Impact Echo(ModIE) Measurement systems and to the understanding of the seismic wave propagation. The data of ModIE were processed by DWT and compared with the results of conventional ModIE Analysis. Although it is inconsistent in the evaluated thickness of concrete lining, the DWT provides the features of separation, synthesis and de-noising in the original signal. The application of technique by wavelet was explained numerically with ABAQUS and performed experimentally with a real scale model in this work. Further works on the possible ways for creating new mother wavelet are specially needed for the enhancement of seismic signal analysis.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.219-223
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• 2002

Voltage and current signals during impulse tests on transformer are treated as non-stationary signals. A new method incorporating signal-processing method such as Wavelets and courier transform is proposed for failure identification. It is now possible to distinguish failure during impulse tests. The method is experimentally validated on a transformer winding. The wavelet transforms enables the detection of the time of occurrence of switching or failure events. After establishing the time of occurrence, the original waveform is split into two or more sections. The wavelet transform has ability to analysis the failure signal on time domain as well as frequency domain. Therefore, the wavelet transform is superior than courier transform to analysis the failure signal. In this paper, the fact was proved by real data which was achieved.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2327-2330
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• 2003

This paper deals with face detection and recognition using ellipsodal information and wavelet packet analysis. We proposed two methods. First, Face detection method uses general ellipsodal information of human face contour and we find eye position on wavelet transformed face images A novel method for recognition of views of human faces under roughly constant illumination is presented. Second, The proposed Face recognition scheme is based on the analysis of a wavelet packet decomposition of the face images. Each face image is first located and then, described by a subset of band filtered images containing wavelet coefficients. From these wavelet coefficients, which characterize the face texture, the Euclidian distance can be used in order to classify the face feature vectors into person classes. Experimental results are presented using images from the FERET and the MIT FACES databases. The efficiency of the proposed approach is analyzed according to the FERET evaluation procedure and by comparing our results with those obtained using the well-known Eigenfaces method. The proposed system achieved an rate of 97％(MIT data), 95.8％(FERET databace)