• 한국정보통신학회논문지
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• 제4권2호
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• pp.461-468
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• 2000

디지털 기술 발전에 따른 오디오 데이터의 증가는 여러 컴퓨터 응용에 사용되면서 데이터를 관리하고 사용하기 위해, 내용기반 질의와 유사성 검색과 같은 새로운 기능을 갖는 데이터베이스 시스템의 개발이 불가피하게 됐다. 내용 기반 질의를 위한 빠르고 정확한 검색은 이러한 응용 시스템들에 필요하다. 효율적인 내용기반 색인과 유사성 검색의 설계는 관련성 있는 데이터의 빠른 검색을 제공하기 위한 주된 요소이다. 본 논문에서는 소파(Wavelet) 변환을 이용한 한국 전통 음악 데이터베이스의 오디오 색인을 위한 방법을 제안한다. 또한 소파 변환을 이용해 오디오 데이터에 대한 색인의 가능성을 보인다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.459-460
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• 2001

In this paper, we analyze algorithms for diagnosing of VEP(visual evoked potential) signal. We used wavelet transform for the preprocessing of VEP signal data and back propagation neural network for the pattern recognition. We used several wavelets to study their effects and efficiency in the preprocessing of VEP. The diagnosis system led to good results. We obtained the noise reduced and compressed signal with the wavelet transform of the training VEP signal. So it is possible to train the neural network faster and exact diagnosis processing is possible in the neural network. From the experimental results, we know that the discrimination ability of the neural network is changed by the type of basis vector and the proposed system is good to the diagnosis of VEP.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.305-312
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• 2006

K-means clustering algorithm 에서 주로 이루어지는 랜덤 초기화 (random initialization) 방법은 전역 최적화된 해(global minimum)를 찾아내기에 문제점을 지니고 있다. 즉, 여러 횟수의 알고리듬 반복(iteration)을 실행하더라도 전역 최적화된 해를 찾아내기가 매우 힘들며 주어진 자료의 크기(data size)가 큰 경우에 있어서 이는 거의 불가능하다. 본 논문은 이러한 문제점들을 극복하기 위한 방안으로, wavelet을 이용하여 최적의 초기 군집 중심점(initial clustering center)들을 선택하는 방법을 제시한다. 즉, 웨이블릿을 이용한 효과적인 초기화 (initialization)를 통해서 작은 알고리듬 반복 횟수만으로도 전역 최적화에 도달하는 초기화 방법을 기술한다. 이런 초기화 방법이 군집 알고리즘에 사용될 경우, 온라인상에서 실시간 이루어지는 군집 분석에 큰 도움이 된 수 있다.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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• pp.219-223
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• 2002

Voltage and current signals during impulse tests on transformer are treated as non-stationary signals. A new method incorporating signal-processing method such as Wavelets and courier transform is proposed for failure identification. It is now possible to distinguish failure during impulse tests. The method is experimentally validated on a transformer winding. The wavelet transforms enables the detection of the time of occurrence of switching or failure events. After establishing the time of occurrence, the original waveform is split into two or more sections. The wavelet transform has ability to analysis the failure signal on time domain as well as frequency domain. Therefore, the wavelet transform is superior than courier transform to analysis the failure signal. In this paper, the fact was proved by real data which was achieved.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.239-256
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• 2015

An adaptive-scale damage detection strategy based on a wavelet finite element model (WFEM) for thin plate structures is established in this study. Equations of motion and corresponding lifting schemes for thin plate structures are derived with the tensor products of cubic Hermite multi-wavelets as the elemental interpolation functions. Sub-element damages are localized by using of the change ratio of modal strain energy. Subsequently, such damages are adaptively quantified by a damage quantification equation deduced from differential equations of plate structure motion. WFEM scales vary spatially and change dynamically according to actual needs. Numerical examples clearly demonstrate that the proposed strategy can progressively locate and quantify plate damages. The strategy can operate efficiently in terms of the degrees-of-freedom in WFEM and sensors in the vibration test.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제17권4호
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• pp.279-294
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• 2013

We are interested in an adaptive grid method for hyperbolic equations. A multiresolution analysis, based on a biorthogonal family of interpolating scaling functions and lifted interpolating wavelets, is used to dynamically adapt grid points according to the physical field profile in each time step. Traditional finite-difference schemes with fixed stencils produce high oscillations around sharp discontinuities. In this paper, we hybridize high-resolution schemes, which are suitable for capturing singularities, and apply a finite-difference approach to the scaling functions at non-singular points. We use a total variation diminishing Runge-Kutta method for the time integration. The computational cost is proportional to the number of points present after compression. We provide several numerical examples to verify our approach.

• 응용통계연구
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• 제23권2호
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• pp.249-261
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• 2010

Long-term forecasting of seasonal time series is critical in many applications such as planning business strategies and resolving possible problems of a business company. Unlike the traditional approach that depends solely on dynamic models, Li and Hinich (2002) introduced a combination of stochastic dynamic modeling with filter bank approach for forecasting seasonal patterns using highly coherent(High-C) waveforms. We modify the filter selection and forecasting procedure on wavelet domain to be more feasible and compare the resulting predictor with one that obtained from the wavelet variance estimation method. An improvement over other seasonal pattern extraction and forecasting methods based on such as wavelet scalogram, Holt-Winters, and seasonal autoregressive integrated moving average(SARIMA) is shown in terms of the prediction error. The performance of the proposed method is illustrated by a simulation study and an application to the real stock price data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.173-174
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• 2008

Wavelet transform is a new method for power system analysis. On the basis of extensive investigation, optimal mother wavelets for the detection of leakage current are chosen. The recommended mother wavelet is 'Daubechies 4' wavelet. This paper proposes a technique for modeling toe finding point of leakage current in distribution system using wavelet transform and EMTP MODELS.

• 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.

• Journal of applied mathematics & informatics
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• 제29권1_2호
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• pp.145-159
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• 2011

The numerical solution to the linear and nonlinear and linear system of Fredholm and Volterra integral equations of the second kind are investigated. We have used crooked lines which includ the nodes specified by modified rationalized Haar functions. This method differs from using nominal Haar or Walsh wavelets. The accuracy of the solution is improved and the simplicity of the method of using nominal Haar functions is preserved. In this paper, the crooked lines with unknown coefficients under the specified conditions change the system of integral equations to a system of equations. By solving this system the unknowns are obtained and the crooked lines are determined. Finally, error analysis of the procedure are considered and this procedure is applied to the numerical examples, which illustrate the accuracy and simplicity of this method in comparison with the methods proposed by these authors.