• 반도체디스플레이기술학회지
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• 제19권4호
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• pp.77-83
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• 2020

The Linear system analysis for physical system is very powerful tool for system diagnostic utilizing relationship between the input signal and output signal. This method utilized generally to investigate physical properties of system and the nondestructive test by ultrasonic signals. This method can be explained by linear system theory. In this paper the Continuous Wavelets Transform is utilized to search the relation between the linear system and continuous wavelets transform.

• 정보보호학회논문지
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• 제31권6호
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• pp.1127-1136
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• 2021

전력 분석 공격에서 소비 전력 파형의 잡음과 정렬 불량은 공격 성공 여부를 좌우하는 주요한 요인이다. 따라서 이를 완화하기 위한 여러 연구가 수행되고 있으며 웨이블릿 변환 기반의 신호처리 방법도 그중 하나이다. 대부분의 웨이블릿을 사용한 연구에서는 파형 압축할 수 있는 이산 웨이블릿 변환을 사용해 왔는데, 그 이유는 연속 웨이블릿변환 기법이 선택된 스케일의 개수에 따라 데이터 크기 및 분석 시간이 증가할 뿐만 아니라 효율적인 스케일 선택 방법도 없기 때문이다. 본 논문에서는 전력 분석 공격에 최적화된 연속 웨이블릿 변환의 효율적인 스케일 선택 방법을 제안하며 이를 이용해 파형을 인코딩할 경우 분석 성능이 크게 향상될 수 있음을 보인다. 비프로파일링 공격인 CPA(Correlation Power Analysis) 및 DDLA(Differential Deep Learning Analysis) 공격 실험 결과, 제안하는 방법이 잡음 감쇄와 파형 정렬에 효과적임을 확인하였다.

• 대한의용생체공학회:의공학회지
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• 제24권6호
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• pp.487-494
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• 2003

수면뇌파의 해석에 있어서 수면단계는 뇌파의 특성파 검출에 특히 중요하다. 수면단계는 여러 수면질환의 진단에 가장 기초적일 단서를 제공한다. 본 연구에서 수면뇌파 신호를 이산 웨이브렛 변환 뿐 만 아니라 퓨우리에 변환, 연속 웨이브렛 변환을 이용해서 해석하였다. 제안된 시스템 방범인 퓨우리에와 웨이브렛은 수면뇌파의 중요한 특성파(유파, 수면방추파, K복합, 구파 REM) 검출을 위해서 수면상태를 분석했다. 수면뇌파 분석에는 Daubechies 웨이브렛 변환 방법과 고속 퓨우리에를 이용했다. 모의실험결과 신경망 시스템이 특성 파형의 분류에 높은 성능을 발휘함을 알 수 있었다.

• 비파괴검사학회지
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• 제21권1호
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• pp.54-61
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• 2001

웨이블릿 변환과 인공신경망을 이용하여 AE 신호를 분류하는 소프트웨어 패키지를 개발하였다. 웨이블릿 변환으로는 연속 웨이블릿 변환과 이산 웨이블릿 변환을 모두 고려하였으며, 인공신경망의 모델로는 오류 역전파 인공신경망을 사용하였다. 분류에 사용된 AE 신호는 용접부에 인공결함을 가진 시편의 3점 굽힘시험에서 발생한 신호이다. 개발된 소프트웨어 패키지를 이용하여 이 신호를 웨이블릿 변환시켜 생성된 시간-주파수 평면상에서 특징값을 추출하고 이를 인공신경망에 학습하여 인공신경망 분류기를 설계하고 검증하였다. 본 연구에서 개발된 소프트웨어 패키지를 이용한 AE 신호 분류법이 유용함을 보이고, 또한 연속 웨이블릿 변환과 이산 웨이블릿 변환에 의한 분류 결과를 비교하였다.

• 대한의용생체공학회:의공학회지
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• 제29권4호
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• pp.278-285
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• 2008

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

• 산업기술연구
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• 제21권A호
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• pp.105-110
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• 2001

A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paler describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.176-181
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• 2002

The continuous Gabor wavelet transform (GWT) has been utilized as a useful time-frequency analysis tool to identify the rapidly-varying characteristics of some wave signals. In the application of GWT, it is important to select the Gabor wavelet with the optimal shape factor by which the time-frequency distribution of a signal can be accurately estimated. To find the signal-dependent optimal Gabor wavelet shape factor, the notion of the Shannon entropy which mesures the extent of signal energy concentration in the time-frequency plane is employed. To verify the validity of the present entropy-based scheme, we have applied it to the time-frequency analysis of a set of elastic bending wave signals generated by an impact in a solid cylinder.

• Structural Engineering and Mechanics
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• 제38권1호
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• pp.81-97
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• 2011

In this research, the wavelet transform is used to analyze time response of a cracked beam carrying moving mass for damage detection. In this respect, a new damage detection method based on the combined use of continuous and discrete wavelet transforms is proposed. It is shown that this method is more capable in making damage signature evident than the traditional two approaches based on direct investigation of the wavelet coefficients of structural response. By the proposed method, it is concluded that strain data outperforms displacement data at the same point in revealing damage signature. In addition, influence of moving mass-induced terms such as gravitational, Coriolis, centrifuge forces, and pure inertia force along the deflection direction to damage detection is investigated on a sample case. From this analysis it is concluded that centrifuge force has the most influence on making both displacement and strain data damage-sensitive. The Coriolis effect is the second to improve the damage-sensitivity of data. However, its impact is considerably less than the former. The rest, on the other hand, are observed to be insufficient alone.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.324.1-324
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• 2002

The continuous Gabor wavelet transform (GWT) has been utilized as a useful time-frequency analysis tool to identify the rapidly-varying characteristics of some wave signals. In the application of GWT, it is important to select the Gabor wavelet with the optimal shape factor by which the time-frequency distribution of a signal can be accurately estimated. To find the signal-dependent optimal Gator wavelet shape factor, the notion of the Shannon entropy which measures the extent of signal energy concentration in the time-frequency plane is employed. (omitted)

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2001년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Fall 2001
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• pp.391-398
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• 2001

This paper presents the application method of a wavelet theory for identification of the structural dynamic properties of a bridge, which is based on the ambient vibration signal caused by the traffic loadings. The method utilizes the time-scale decomposition of the ambient vibration signal , i . e. the continuous wavelet transform using the Morlet wavelet is used to decompose the ambient vibration signal into the time-scale domain. The applicability of the proposed approach is verified through the reduced scale bridge and automobile system in the laboratory. The results of verification shows that the use of the Morlet wavelet to identify the structural dynamic properties is reasonable and practicable.