• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.24-28
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• 2001

Wavelet transforms are used for implementing digital watermarking methods in the frequency domain. In this paper, we construct the digital watermarking using various wavelet transforms such as the Daubechies transform, Coiflets transform, Symlets transform and the biorthogonal transform, and we compare each digital watermarking method with the others. We investigate the preservation of the watermark after the data compression attack based on the discrete on the discrete cosine transform. We show that the biorthogonal wavelet, denoted by bior3.5, has the best performance among the wavelet types we selected in an experiment.

• Structural Engineering and Mechanics
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• 제60권4호
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• pp.667-691
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• 2016

This study focuses on the damage detection of defect types in plate structures based on wavelet transform (WT) and curvelet transform (CT). In particular, for damage detection of structures these transforms have been developed since the last few years. In recent years, the CT approach has been also introduced in an attempt to overcome inherent limitations of traditional multi-scale representations such as wavelets. In this study, the performance of CT is compared with WT in order to demonstrate the capability of WT and CT in detection of defect types in plate structures. To achieve this purpose, the damage detection of defect types through defect shape in rectangular plate is investigated. By using the first mode shape of plate structure and the distribution of the coefficients of the transforms, the damage existence, the defect location and the approximate shape of defect are detected. Moreover, the accuracy and performance generality of the transforms are verified through using experimental modal data of a plate.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• 제6권1호
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• pp.1-6
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• 2003

This study presents the results of series of studies, which are mainly devoted to the application of wavelet transforms to various problems in ocean engineering. Both continuous and discrete wavelet transforms were used. These studies attempted to solve detection of wave directionality, detection of wave profile, and decoupling of the rolling component from free roll decay tests. The results of these analysis, using wavelet transform, demonstrated that the wavelet transform can be a useful tool in analyzing many problems in the filed of ocean engineering.

• 한국해양공학회지
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• 제17권3호
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• pp.1-6
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• 2003

This study presents the results of series of studies, which are mainly devoted to the application of wavelet transforms to various problems in ocean engineering. Both continuous and discrete wavelet transforms were used. These studies attempted to solve detection of wave directionality, detection of wave profile, and decoupling of the rolling component from free roll decay tests. The results of these analysis, using wavelet transform, demonstrated that the wavelet transform can be a useful tool in analyzing many problems in the filed of ocean engineering.

• The Journal of the Acoustical Society of Korea
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• 제18권1E호
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• pp.13-19
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• 1999

This paper introduces an adaptive wavelet transform based on the lifting scheme, which is applied to signal denoising. The wavelet representation using orthogonal wavelet bases has received widespread attention. Recently the lifting scheme has been developed for the construction of biorthogonal wavelets in the spatial domain. Wavelet transforms are performed through three stages: the first stage or Lazy wavelet splits the data into two subsets, even and odd, the second stage calculates the wavelet coefficients (highpass) as the failure to interpolate or predict the odd set using the even, and the third stage updates the even set using neighboring odd points (wavelet coefficients) to compute the scaling function coefficients (lowpass). In this paper, we adaptively find some of the prediction coefficients for better representation of signals and this customizes wavelet transforms to provide an efficient framework for denoising. Special care has been given to the boundaries, where we design a set of different prediction coefficients to reduce the prediction error.

• 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.

• 한국콘텐츠학회논문지
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• 제9권7호
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• pp.19-26
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• 2009

본 논문은 가중 퍼지소속함수 기반 신경망(Neural Network with weighted Fuzzy Membership Functions, NEWFM)과 웨이블릿 변환(wavelet transforms, WT)을 이용하여 Creighton University Ventricular Tachyarrhythmia Database(CUBD)의 심전도 신호로부터 정상리듬(normal sinus rhythm, NSR)과 심실 빈맥/세동(Ventricular tachycardia/fibrillation VT/VF)을 검출하는 방안을 제시하고 있다. NEWFM에서 사용할 특정입력을 추출하기 위해서 첫 번째 단계에서는 웨이블릿 변환을 이용하여 스케일 레벨 3과 레벨 4의 주파수 대역에서 d3과 d4의 계수들을 각각 선택하였다. 두 번째 단계에서는 d3과 d4의 계수들에 대한 구간별 표준편차를 이용하여 8개의 특징입력을 추출하였다. NEWFM은 이들 8개의 특정입력을 이용하여 정상리듬과 심실 빈맥/세동을 검출하였고 그 결과로 90.1%의 검출성능을 나타내었다.

• 한국안광학회지
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• 제17권2호
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• pp.203-207
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• 2012

목적: 다른 생체신호와 마찬가지로 망막전도(electroretinogram, ERG) 신호도 측정시 잡음이 발생한다. 이 잡음을 효과적으로 제거하여 망막관련 진단의 정확도를 높이고자 하였다. 방법: ERG 신호에 60 Hz 잡음과 백색잡음을 발생시켜 샘플링 신호를 만들었다. 웨이브렛 변환과 대역통과 필터를 이용하여 잡음를 제거하였다. 푸리에 변환 스펙트럼을 이용하여 제거된 주파수를 비교하였다. 신호대잡음비(signal to noise ratio, SNR)를 이용하여 제거된 잡음을 수치적으로 비교하였다. 결과: 푸리에 변환 스펙트럼을 비교한 결과 웨이브렛 변환에서는 60 Hz 잡음은 완전히 제거 되었으며 백색잡음도 많이 제거되었다. 대역통과필터에서는 60 Hz와 백색잡음 남아 있었다. 신호대잡음비를 비교한 결과에서는 웨이브렛 변환은 22.8638, 대역통과 필터는 4.0961로 나타났다. 결론: 웨이브렛 변환을 이용하여 잡음 제거시 신호의 왜곡을 적게 발생시켜 제거할 수 있었다. 망막전도 신호를 이용한 망막 진단에 정확도를 높일 수 있을 것으로 기대된다.

• International Journal of Control, Automation, and Systems
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• 제4권3호
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• pp.365-371
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• 2006

This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and neural networks for detection and classification of internal faults in a two-winding three-phase transformer. Fault conditions of the transformer are simulated using ATP/EMTP in order to obtain current signals. The training process for the neural network and fault diagnosis decision are implemented using toolboxes on MATLAB/Simulink. Various cases and fault types based on Thailand electricity transmission and distribution systems are studied to verify the validity of the algorithm. It is found that the proposed method gives a satisfactory accuracy, and will be particularly useful in a development of a modern differential relay for a transformer protection scheme.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.387-390
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• 2005

Parameter estimation for the probability model of wavelet coefficients is essential to the wavelet-domain interpolation. However, phase uncertainty, one well-known drawback of the orthogonal wavelet transforms, make it difficult to estimate parameters. In this paper, we exploit a phase shifting matrix in order to improve the accuracy of estimation. Nonlinear modeling to capture the interscale characteristics is also described. The experimental results show that the proposed method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.