• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.1
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• pp.135-141
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• 1999

Recently, advance signal analysis which is called "Time-Frequency Analysis" has been developed. Wavelet and Wigner Distribution are used to the method. Wavelet transform(WT) is applied to time-frequency analysis of waveforms obtained by an ultrasonic pulse-echo technique. The Gabor function is adopted as the analyzing wavelet. Wavelet analysis method is an attractive technique for evolution of material characterization evoluation. In this paper, the feasibility of suppression of ultrasonic background noise signal using WT has been presented. These results suggest that ultrasonic background noise ginal can be suppressed and enhanced even for SNR of 20.8 dB. This property of the WT is extremely useful for the detecting flaw echos embedded in background noise.und noise.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.133-145
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• 2012

This paper describes the high density discrete wavelet transformation which is one that expands an N point signal to M transform coefficients with M > N. The double-density discrete wavelet transform is one of the high density discrete wavelet transformation. This transformation employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is nearly shift-invariant. Similarly, triple-density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. Specifically, the spectrum of the first wavelet is concentrated halfway between the spectrum of the second wavelet and the spectrum of its dilated version. In addition, the second wavelet is translated by half-integers rather than whole-integers in the frame construction. This arrangement leads to high density wavelet transformation. But this new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard and double-density discrete wavelet transformation in terms of multiple directions. Resultingly, the proposed wavelet transformation services good performance in image and video processing fields.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1129-1144
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• 2020

The thangka image inpainting method based on wavelet transform is not ideal for contour curves when the high frequency information is repaired. In order to solve the problem, a new image inpainting algorithm is proposed based on edge structural constraints and wavelet transform coefficients. Firstly, a damaged thangka image is decomposed into low frequency subgraphs and high frequency subgraphs with different resolutions using wavelet transform. Then, the improved fast marching method is used to repair the low frequency subgraphs which represent structural information of the image. At the same time, for the high frequency subgraphs which represent textural information of the image, the extracted and repaired edge contour information is used to constrain structure inpainting in the proposed algorithm. Finally, the texture part is repaired using texture synthesis based on the wavelet coefficient characteristic of each subgraph. In this paper, the improved method is compared with the existing three methods. It is found that the improved method is superior to them in inpainting accuracy, especially in the case of contour curve. The experimental results show that the hierarchical method combined with structural constraints has a good effect on the edge damage of thangka images.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.507-514
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• 1996

The automated ECG diagnostic systems in hospital have a low P-wave detection capacity in case of some diseases like conduction block. The purpose of this study is to improve the P-wave detection ca- pacity using wavelet transform. The first procedure is to remove baseline drift by subtracting the median filtered signal from the original signal. The second procedure is to cancel ECG's QRS-T complex from median filtered signal to get P-wave candidate. Before we subtracted the templete from QRS-T complex, we estimated the best matching between templete and QRS-T complex to minimize the error. Then, wavelet transform was applied to confirm P-wave. In particular, haiti wavelet was used to magnify P-wave that consisted of low frequency components and to reject high frequency noise of QRS-T complex cancelled signal. Finally, p-wave was discriminated and confirmed by threshold value. By using this method, We can got the around 95.1% P-wave detection. It was compared with contextual information.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.959-962
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• 2000

A heart sound algorithm, which separates the heart sound signal into four parts; the first heart sound, the systolic period, the second heart sound, and the diastolic period has been developed. The algorithm uses discrete intensity envelopes of approximations of the wavelet transform analysis method to the phonocard-iogram(PCG)signal. Heart sound a highly nonstation-ary signal, so in the analysis of heart sound, it is important to study the frequency and time information. Further more, Wavelet Transform provides more features and characteristics of the PCG signal that will help physician to obtain qualitative and quantitative measurements of the heart sound.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.85-88
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• 2000

With the rapid growth of network distributions of digitized media(audio, image, and video), there is an urgent need for copyright protection. For now watermarking is a well-known technique for copyright protection of digital data. To embed a digital watermark to the image, discrete cosine transform(DCT) and wavelet transform are commonly used. In this paper, the performance of the DCT based watermarking technique and wavelet based watermarking technique were compared and the influences of the parameter a that decides the strength of the watermarking data were considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1715-1721
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• 1997

Wavelet transform is not applicable to arbitrarily-shaped region (or object) in images, due to the nature of its global decomposition. In this paper, the arbitrarily-shaped wavelet transform(ASWT) is proposed in order to solve this problem and its properties are investigated. Computation complexity of the ASWT is also examined and it is shown that the ASWT requires significantly fewer computations than conventional wavelet transform, since the ASWT processes only the object region in the original image. Experimental resutls show that any arbitrarily-shaped image segment can be decomposed using the ASWT and perfectly reconstructed using the inverse ASWT.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.282-287
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• 1996

We. develop in this study a wavelet transform method to apply to the flux reconstruction problem in reactor analysis. When we reconstruct pinwise heterogeneous flux by iterative methods, a difficulty arises due to the near singularity of the matrix as the mesh size becomes finer. Here we suggest a wavelet transform to tower the spectral radius of the near singular matrix and thus to converge by a standard iterative scheme. We find that the spectral radios becomes smatter than one after the wavelet transform is performed on sample problems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.83-95
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• 1999

Wavelet transform has localization for time or frequency. It is useful to analyze a nonstationary signal. Basic function on wavelet transform is generated dilating and translating the original wavelet(mother wavelet). In this paper, time-frequency analysis method using linear combination wavelet transform is proposed. And it is applied to diagnostic monitoring system using the proposed linear combination wavelet transform. The stationary and nonstationary signal is used linear chirp signal, fan noise signal, a sinusoid signal from revolution body, electronic signal. Transform applied to signal analysis use fast Fourier transform (FFT), Daubechies, Haar and proposed linear combination method. The result of time-frequency analysis using linear combination wavelet transform is suited for portraying nonstationary time signal as well as stationary signal. Also the diagnostic monitoring system carry out the effective the signal analysis.