• 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.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.879-880
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• 2006

The subject of this paper is to recognize the stable state of EEG using wavelet transform and power spectrum analysis. An alpha wave, showed in stable state, is dominant wave for a human EEG and a beta wave displayed excited state. We decomposed EEG signal into an alpha wave and a beta wave in the process of wavelet transform. And we calculated each power spectrum of EEG signal, an alpha wave and a beta wave using Fast Fourier Transform. We recognized the stable state by making a comparison between power spectrum ratios respectively.

• 한국인터넷방송통신학회논문지
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• 제16권2호
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• pp.113-122
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• 2016

본 연구에서는, 웨이블릿 노이즈 감쇠에 고속 푸리에 역 변환을 포함하는 방법을 제안한다. 위너 필터링에 인자를 채용하여 역 필터링을 나타내고, 최적의 계수는 전체 평균 제곱 오차를 최소화하도록 선택된다. 위너 필터를 적용하기 위해, 손상된 그림에서 원 화상의 파워 스펙트럼을 계산한다. 위너 필터링은 역 필터링 처리를 포함하기 때문에 블링 필터가 반전되지 않을 때 노이즈는 확장한다. 큰 노이즈를 제거하려면 최고의 웨이블릿 임계값을 사용하여 노이즈를 제거하는 것이다. 웨이블릿 노이즈 감쇠 단계는 역 필터링 및 웨이블릿 기능으로 노이즈 감소로 구성된다. 실험결과는 전체 재생 성능 이상의 다른 방법을 능가하지는 않았다.

• Journal of the Optical Society of Korea
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• 제15권1호
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• pp.103-108
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• 2011

Recently reported asynchronous-optical-sampling terahertz (THz) time-domain spectroscopy enables high-resolution spectroscopy due to a long time-delay window. However, a long-lasting tail signal following the main pulse is often measured in a time-domain waveform, resulting in spectral fluctuation above a background noise level on a high-resolution THz amplitude spectrum. Here, we adopt the wavelet power spectrum estimation technique (WPSET) to effectively remove the spectral fluctuation without sacrificing spectral features. Effectiveness of the WPSET is verified by investigating a transmission spectrum of water vapor.

• 한국임상보건과학회지
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• 제4권4호
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• pp.756-761
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• 2016

Purpose. Noise occurs at measuring Electoretinogram(ERG) signals as the other bio-signal measurement. It is compared the denoising performance according to the mother function of wavelet transforms. Methods. The ERG signal that generated power supply noise and white noise was used as a sampling signal. The noise of ERG signal was filtered by using haar, db7, bior mother function. The filtering performance of each mother functions was compared using Fourier transform spectrum and SNR(signal to noise ratio). Results. In the haar functioin, the result of the Fourier transform spectrum was that the power supply noise is removed and the white noise performance is not good. The SNR was 27.0404. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is good. The SNR was 35.1729. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is the bset. The SNR was 35.4445. Conclusions. The db7, bior function was good results in power supply noise and white noise filtered. The bior function is suitable for filtering noise of the ERG signal.

• 융합신호처리학회논문지
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• 제8권3호
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• pp.178-184
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• 2007

일반적으로 EEG 신호는 Alpha파, Beta파, Theta파, Delta파로 구분할 수 있다. Alpha파는 사람에게 있어서 가장 우세한 파형으로써 정신적으로 안정 시 잘 나타나는 뇌파이며, Beta파는 흥분 시 우세하게 나타난다. 본 연구에서는 EEG의 안정 상태를 정량적으로 나타내기 위해 웨이브렛 변환과 파워 스펙트럼 분석을 이용하였다. EEG신호를 웨이브렛 변환을 통해 Alpha파와 Beta파만 검출하여 고속 푸리에 변환을 이용 Alpha파와 Beta파의 파워 스펙트럼을 구하였다. 이후 Beta파의 파워 스펙트럼에 대한 Alpha파의 파워 스펙트럼 비율로 정의되는 상대적 안정상태비(Stable State Ratio)를 계산하였다. 그 결과 피험자가 정상적인 활동 상태에서 정신적으로 편안한 안정 상태에 이르기까지 5분 이내가 16%, $5{\sim}10$분 사이가 9%, 그리고 최소 10분 이상의 시간이 소요되는 피험자집단이 총 69%로 우세하게 나타났다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2003년도 봄 학술발표회 논문집
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• pp.249-256
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• 2003

To investigate the safety and stability of the concrete lining, numerous studies have been conducted over the years and several methods have been developed. Most signal processing method of NDT techniques has based on the Fourier analysis. However, the application of Fourier analysis to analyze recorded signal shows results only in frequency domain, it is not enough to analyze transient waves precisely. In this study, a new NDT technique .using the wavelet theory was employed for the analysis of non-stationary wave propagation induced by mechanical impact in the concrete lining. The wavelet transform of transient signals provides a method for mapping the frequency spectrum as a function of time. To verify the availability of wavelet transform as a time- frequency analysis tool, model experiments have been conducted on the concrete lining model. From this study, it was found that the contour map by Wavelet transform provides more distinct results than the power spectrum by Fourier transform and it was concluded that Wavelet transform was an effective tool for the experimental analysis of dispersive waves in concrete structures.

• Earthquakes and Structures
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• 제11권6호
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• pp.1143-1164
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• 2016

Time Delay of Arrival (TDOA) estimation methods based on correlation function analysis play an important role in the micro-seismic event monitoring. It makes full use of the similarity in the recorded signals that are from the same source. However, those methods are subjected to the noise effect, particularly when the global similarity of the signals is low. This paper proposes a new approach for micro-seismic monitoring based on cross wavelet transform. The cross wavelet transform is utilized to analyse the measured signals under micro-seismic events, and the cross wavelet power spectrum is used to measure the similarity of two signals in a multi-scale dimension and subsequently identify TDOA. The offset time instant associated with the maximum cross wavelet transform spectrum power is identified as TDOA, and then the location of micro-seismic event can be identified. Individual and statistical identification tests are performed with measurement data from an in-field mine. Experimental studies demonstrate that the proposed approach significantly improves the robustness and accuracy of micro-seismic source locating in mines compared to several existing methods, such as the cross-correlation, multi-correlation, STA/LTA and Kurtosis methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.969-971
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• 1999

Wavelet analysis is applying to many fields such as the time-frequency localization of a time series and a time varying data. In this paper, a statistical testing based Wavelet power spectrum analysis for the stationary Nino3 Sea Surface Temperature(SST) data was executed. Specially, the 95% confidence level for SST was effective in searching the periods of El-Nino using various wavelet basis functions.