• 한국수자원학회논문집
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• 제38권6호
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• pp.439-448
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• 2005

본 논문은 수문시계열에서 나타나는 주기성 및 경향성 등을 평가하기 위한 방법으로 Fourier Transform을 개선한 Wavelet Transform방법을 제시하고 이에 대한 타당성 및 적용성을 월강수량 및 연강수량 자료와 대표적인 기상인자인 남방진동지수(SOI)와 해수면온도(SST)를 대상으로 평가해 보았다. Fourier Transform은 시간적인 특성을 파악하지 못하는 반면에 Wavelet Transform은 수문시계열이 갖는 시간적인 특성을 유지하면서 빈도에 대한 스펙트럼을 보다 효율적으로 평가할 수 있었다. Wavelet Transform을 이용하여 분석한 결과 국내 월강수량은 1년을 중심으로 강한 스펙트럼을 나타내고 있으며 연강수량은 2-8년 주기에서 통계적으로 유의한 주기를 확인할 수 있었다. SOI와 SST에서는 2-8년 주기가 지배적임을 확인할 수 있었다.

• 한국해안·해양공학회논문집
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• 제20권6호
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• pp.583-588
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• 2008

2008년 2월에 동해안에서 발생하였던 너울 관측 자료에 대하여 웨이블릿 방법을 사용하여 분석하였다. 시간에 따른 파군, 첨두 주파수 및 스펙트럼의 변화를 볼 수 있었으며 그 결과를 시간에 따라 평균하여 푸리에 스펙트럼과 비교한 결과 시간에 따른 형태나 첨두 주기의 변화는 유사하게 나왔으나 첨두 주파수 에너지와 유의 파고에 있어서는 차이를 나타냈다. 웨이블릿 분석 방법은 주파수 뿐 만 아니라 시간에 따른 스펙트럼의 변화를 볼 수 있어서 이상 파랑이나 갑작스러운 너울과 같은 일시적이고 불규칙적인 현상 연구에 효과적 것인으로 보이며 향후 우리나라 파랑 자료에 대한 많은 적용과 분석 연구가 필요하다.

• Structural Engineering and Mechanics
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• 제27권2호
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• pp.173-197
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• 2007

A wavelet-based procedure to generate artificial accelerograms compatible with a prescribed seismic design spectrum is described. A procedure to perform a baseline correction of the compatible accelerograms is also described. To examine how the frequency content of the modified records evolves with time, they are analyzed in the time and frequency using the wavelet transform. The changes in the strong motion duration and input energy spectrum are also investigated. An alternative way to match the design spectrum, termed the "two-band matching procedure", is proposed with the objective of preserving the non-stationary characteristics of the original record in the modified accelerogram.

• 디지털산업정보학회논문지
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• 제8권3호
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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.

• 한국자기공명학회논문지
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• 제4권2호
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• pp.103-115
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• 2000

Wavelet transforms are introduced as a new tool to distinguish real peaks from the noise contaminated NMR data in this paper. New algorithms of two wavelet transforms including Daubechies wavelet transform as a discrete and orthogonal wavelet transform (DWT) and Morlet wavelet transform as a continuous and nonorthogonal wavelet transform(CWT) were developed fer noise elimination. DWT and CWT method were successfully applied to the noise reduction in spectrum. The inevitable distortion of NMR spectral baseline and the imperfection in noise elimination were observed in DWT method while CWT method gives a better baseline ahape and a well noise suppressed spectrum.

• Nuclear Engineering and Technology
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• 제52권8호
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• pp.1771-1776
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• 2020

Adverse effects in the measured gamma spectrum caused by radioactive statistical fluctuations, gamma ray scattering, and electronic noise can be reduced by energy spectrum denoising. Wavelet threshold denoising can be used to perform multi-scale and multi-resolution analysis on noisy signals with small root mean square errors and high signal-to-noise ratios. However, in traditional wavelet threshold denoising methods, there are signal oscillations in hard threshold denoising and constant deviations in soft threshold denoising. An improved wavelet threshold calculation method and threshold processing function are proposed in this paper. The improved threshold calculation method takes into account the influence of the number of wavelet decomposition layers and reduces the deviation caused by the inaccuracy of the threshold. The improved threshold processing function can be continuously guided, which solves the discontinuity of the traditional hard threshold function, avoids the constant deviation caused by the traditional soft threshold method. The examples show that the proposed method can accurately denoise and preserves the characteristic signals well in the gamma energy spectrum.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(5)
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• pp.127-130
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• 2000

Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.5-9
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• 2001

In this paper, we propose the new audio watermarking method and can be used on line processing. Instead of the wavelet transform, we use the integer wavelet transform for the reduction of the computational load. The watermark associated with the chi-square distribution is inserted into the signal on the integer wavelet domain. When extracting the watermark, the spread spectrum methods are used with the coefficients associated with the covariance sequence. We show that the chi-square distribution is a good tool for the spread spectrum method on the wavelet domain. This watermarking technique may be used for the control of the electrical product which can be controlled with the hidden signals and can be moved according to the audible signals simultaneously.

• 한국지능시스템학회논문지
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• 제11권8호
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• pp.731-735
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• 2001

본 논문은 새로운 워터마킹기법을 제안하고 이 기법은 실시간 처리에 이용될 수 있다. 웨이브릿변환 대신에 계산량을 줄이기 위해 정수 웨이브릿변환을 이용한다. 본 논문에서 정수 웨이브릿 공간에서 카이자승분포와 관련한 워터마크를 삽입한다. 워터마크를 추출할 때 확산스펙트럼 기법을 이용하고 유사도는 공분산 수열에서 결정하낟. 실험을 통하여 카이 자승분포를 이용한 워터마크를 이용하는 것이 소음에 강인함을 보인다. 이 워터마킹 기법은 동시에 은닉된 정보에 제어되고 오디오 신호에 따라 움직일 수 있는 전기 기기의 제작에 쓰일 수 있다.