• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2442-2444
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• 1998

This paper presents a method for designing a multiresolution orthogonal wavelet transform matrix and it is extended to the establishment of the wavelet transform domain sign algorithms(SA). It outperforms the conventional sign algorithm, with performance comparable to the LMS algorithm. Together with Daubechies type 1 wavelet, we could also save additional computations which are required in transforming data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.272-275
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• 1999

In this paper, a wavelet transform-based adaptive interference excision scheme using the adaptive algorithm which suppresses narrow band interference in the wavelet transform domain for the direct spread modulation system application, is introduced. Using the Monte-Carlo simulation, the bit error probabilities of the direct spread communication systems with the excision systems of two kinds of Daubechies wavelets (db2, db8) in the transform domain, are analysed. With these results, it is shown that the performance of a system depends on the characteristics of wavelet being used. And with this scheme, we expect effective improvements in the direct spread communication system performance.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.362-364
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• 2001

This paper presents the establishment of the wavelet transform domain sign algorithm and performance analysis by using wavelet filter such as multiplier-free QMF which don't require multiple computation.

• ETRI Journal
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• v.28 no.1
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• pp.51-58
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• 2006

In this paper, we propose a method of applying a lifting-based wavelet domain e-median filter (LBWDEMF) for image restoration. LBWDEMF helps in reducing the number of computations. An e-median filter is a type of modified median filter that processes each pixel of the output of a standard median filter in a binary manner, keeping the output of the median filter unchanged or replacing it with the original pixel value. Binary decision-making is controlled by comparing the absolute difference of the median filter output and the original image to a preset threshold. In addition, the advantage of LBWDEMF is that probabilities of encountering root images are spread over sub-band images, and therefore the e-median filter is unlikely to encounter root images at an early stage of iterations and generates a better result as iteration increases. The proposed method transforms an image into the wavelet domain using lifting-based wavelet filters, then applies an e-median filter in the wavelet domain, transforms the result into the spatial domain, and finally goes through one spatial domain e-median filter to produce the final restored image. Moreover, in order to validate the effectiveness of the proposed method we compare the result obtained using the proposed method to those using a spatial domain median filter (SDMF), spatial domain e-median filter (SDEMF), and wavelet thresholding method. Experimental results show that the proposed method is superior to SDMF, SDEMF, and wavelet thresholding in terms of image restoration.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.26-32
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• 2007

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.342-348
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• 2005

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2333-2338
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• 2011

In this paper, we develope a wavelet transform based time-frequency domain reflectometry (WTFDR) for the fault localization of underground power cable. The conventional TFDR (CTFDR) is more accurate than other reflectometries to localize the cable fault. However, the CTFDR has some weak points such as long computation time and hard implementation because of the nonlinearity of the Wigner-Ville distribution used in the CTFDR. To solve the problem, we use the complex wavelet transform (CWT) because the CWT has the linearity and the reference signal in the TFDR has a complex form. To confirm the effectiveness and accuracy of the proposed method, the actual experiments are carried out for various fault types of the underground power cable.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1679-1681
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electromagnetic wave detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, inclued noise signal in detected PD signal is well elimiated. we can propose the true shape of PD signal.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.62-68
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electrical detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, included noise signal in detected PD signal is well eliminated. we can propose the true shine of PD signal.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.1
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• pp.25-34
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• 2003

Gas insulated switchgear(GIS) is an important equipment in a substation. It is highly desirable to measure a partial discharge(PD) in GIS which is a symptom before insulation breakdown occurs. The issue is that the PD signal is weak and sensitive to external noise. In this paper, the algorithm for detection of PD in GIS using wavelet transform is proposed. The wavelet transform provides a direct quantitative measure of spectral content, "dynamic spectrum", in the time-frequency domain. The recommended mother wavelet is 'Daubechies' wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, can be used most properly in disturbance phenomena which occurs rapidly for a short time. Through the procedure of wavelet transform, noise extraction and reconstruction, the signal is Analyzed to determine the magnitude of PD in GIS. In experimental results, we can know that partial discharge is exactly detected in combination of Dl and D2 using wavelet transform.transform.