• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.2
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• pp.94-103
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• 1997

The WCHF-FSJTC (wavelet circular harmonic function frequency selective joint transform correlator) using th wavelet transformed CHF as the reference image in FSJTC is proposed for rotation invariant pattern recognition. Since the wavelet transform has the property of feature extraction, the proposed system can have the better DC (discrimination cpability) and the higher SNR(signal to noise ratio) compared with the conventional CHF-CJTC(circular harmonic function conventional joint transform correlator). And since the structure of the proposed system is FSJTC which can eliminate auto-correlation and cross-correlation between input images, it can eliminate false alarm caused by the overlapping among correlation peaks. The used wavelet functio is the morlet function, which is proper for the reference image used in this paper. the optimal dialation parameter and oscillation frequency of the wavelet function are also achieved with varying the parameters of the wavelet function. The computer simulation shows that the proposed system has the best performance when the dilation parameter is 0.8 and the oscillation frequency is 0.48.

• Journal of the Korean Magnetic Resonance Society
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• v.4 no.2
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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.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.377-380
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• 2002

This paper presents the results of a study investigating methods of interpretation of wave directionality based on wavelet transforms. Two-dimensional discrete wavelet was used for the analysis. The proposed scheme utilizes a single frame of ocean waves to detect their directionality. This fact is striking considering the fact that traditional methods require long time histories of ocean wave elevation measured at various locations. The developed schemes were applied to the data generated from numerical simulations and video images to test the efficiency of the proposed scheme in detecting the directionality of ocean waves.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.753-759
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• 2009

Feed-forward neural networks have been widely used as function approximation tools in the context of global approximate optimization. In the present study, a wavelet neural network (WNN) which is based on wavelet transform theory is suggested as an alternative to a traditional back-propagation neural network (BPN). The basic theory of wavelet neural network is briefly described, and approximation performance is tested using a nonlinear multimodal function and a composite rotor blade analysis problem. Laplacian of Gaussian function, Mexican function, and Morlet function are considered during the construction of WNN architectures. In addition, approximation results from WNN are compared with those from BPN.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3050-3052
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• 2000

Recently. the subject of "wavelet analysis" has drawn much attention from both mathematical and engineering application fields such as Signal Processing, Compression/ Decomposition, Statistics and etc. Analogous to Fourier analysis, wavelets is a versatile tool with very rich mathematical content and great potential for applications. Specially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. In this paper, discrimination analyses of acquired electrical current signals for each and mixed loads were tried by using Morlet wavelet transform. Their representative loads were classified as TV, DRY, REF, and FL.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.81-87
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• 2001

The human auditory system is appropriate for the "constant Q"system. The STFT (Short Time Fourier Transform) is not suitable for the auditory perception model since it has constant bandwidth. In this paper, the CWT (continuous wavelet transform) is employed for the auditory filter model. In the CWT, the frequency resolution can be adjusted for auditory sensation models. The proposed CWT is applied to the modeling of the JNVF. In addition, other signal processing methods such as STFT, VER-FFT and VFR-STFT are discussed. Among these methods, the model of JNVF (Just Noticeable Variation in Frequency) by using the CWT fits in with the JNVF of auditory model although it requires quite a long time.

• Structural Engineering and Mechanics
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• v.56 no.3
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• pp.423-442
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• 2015

This study examines the wavelet transform for output-only system identification of ambient excited engineering structures with emphasis on its utilization for modal parameter estimation of high-order and closely-spaced modes. Sophisticated time-frequency resolution analysis has been carried out by employing the modified complex Morlet wavelet function for better adaption and flexibility of the time-frequency resolution to extract two closely-spaced frequencies. Furthermore, bandwidth refinement techniques such as a bandwidth resolution adaptation, a broadband filtering technique and a narrowband filtering one have been proposed in the study for the special treatments of high-order and closely-spaced modal parameter estimation. Ambient responses of a 5-story steel frame building have been used in the numerical example, using the proposed bandwidth refinement techniques, for estimating the modal parameters of the high-order and closely-spaced modes. The first five natural frequencies and damping ratios of the structure have been estimated; furthermore, the comparison among the various proposed bandwidth refinement techniques has also been examined.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.259-259
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• 2019

시계열 자료들을 분석하고자 하는 경우 자료가 정상성(stationarity)을 만족하는 경우는 드물다. 특히 계절성을 제거한 자료들에서는 정량화하기 어려운 주기성이 많이 관찰된다. 즉, 어떤 특정지역에서 나타나는 현상이 다른 기상 현상에 영향을 미칠 것은 자명한 일이나 그 관련성이 선형(linearity)일 가능성은 극히 드물다. 따라서 그들 사이의 관련성이 선형성에 근거한 지표들로 정량화되어야 한다. 이러한 문제점을 해결하기 위해서 다양한 방법이 사용되며 그중에서 웨이블릿 분석을 통해 본 연구를 진행하였다. 웨이블릿 변환(wavelet transforms)은 특수한 함수의 집합으로 구성되어 기존 웨이블릿 신호의 분석을 위해 사용되는 방법이다. 이 변환은 푸리에 변환에서 변형된 방법으로 특정한 기저 함수(base function)를 이용하여 기존의 시계열 자료를 주파수로 바꾸는 변환이다. 웨이블릿 변환에서 기저 함수를 모 웨이블릿이라고 하며 이를 천이, 확대 및 축소 과정을 통해 주파수를 구성한다. 웨이블릿 분석은 모 웨이블릿을 분해하고 재결합하여 시계열 분석을 할 수 있다. 모 웨이블릿 함수에는 Haar, Daubechies, Coiflets, Symlets, Morlet, Mexican Hat, Meyer 등의 여러 가지 종류의 모 웨이블릿 함수가 있으며 모 웨이블릿이 달라지면 결과가 다르게 나타난다. 기존에는 Morlet 웨이블릿을 주로 이용하여 주파수분석에 사용하여 결과를 도출하였다. 그리고 시계열 자료는 크게 백색잡음(White Noise), 장기기억(Long Term Memory), 단기기억(Short Term Memory)으로 나뉜다. 각 시계열 자료의 종류에 따라 임의의 시계열 자료를 산정하여 그에 따른 웨이블릿 분석을 통해 모 웨이블릿의 특성을 도출하였다. 본 연구에서는 웨이블릿 분석을 통해 시계열 자료의 최적 모 웨이블릿을 결정하고자 남방진동지수(SOI), 북극진동지수(AOI)의 자료를 이용하여 웨이블릿 분석을 시도하였다. 웨이블릿 분석은 모 웨이블릿에 따라 달라지는 결과를 토대로 분석하였으며 이를 정상성과 지속성에 따라 분류된 시계열에 적용하여 최적 모 웨이블릿을 결정하고자 하였다. 본 연구에서는 임의의 시계열 자료에서 설정한 최적의 모 웨이블릿을 AOI와 SOI와 같은 실제 시계열 자료에 대입하여 분석을 진행하였다. 본 연구에서는 시계열 자료의 종류를 구분하고 자료의 특성에 따라 가장 적합한 모 웨이블릿을 구하고자 하였다.

• Smart Structures and Systems
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• v.20 no.4
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• pp.415-426
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• 2017

Traditional experimental verification for nonlinear system identification often faces the problem of experiment model repeatability. In our research, a steel frame experimental model is developed to imitate the behavior of a single story steel frame under horizontal excitation. Two adjustable rotational dampers are used to simulate the plastic hinge effect of the damaged beam-column joint. This model is suggested as a benchmark model for nonlinear dynamics study. Since the nonlinear form provided by the damper is unknown, a Morlet wavelet based method is introduced to identify the mathematical model of this structure under different damping cases. After the model identification, earthquake excitation tests are carried out to verify the generality of the identified model. The results show the extensive applicability and effectiveness of the identification method.

• Journal of the Korean Society for Railway
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• v.9 no.2 s.33
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• pp.187-192
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• 2006

The regularity of railway track alignment is a crucial component fur maintaining travel safety and the smoothness of passenger ride. The conventional spectral analysis has been considered to estimate the severity of the track irregularity from measured data. The time domain data used to be changed into the frequency domain by Fourier transform. Because the measuring points can be regarded as the time points, the spatial-frequency can be introduced instead of the time-frequency. Although FFT(Fast Fourier Transform) and/or PSD(Power Spectral Density) function could provide fairly localized information within frequency domain, but chronical configurations of data could be missed. In this study, we attempt to apply the Morlet wavelet transform for the purpose of a frequency-time-domain analysis rather than a frequency-domain analysis. The applicability of wavelet transform is examined for the estimation of the track irregularity with real measured track data on the section of Kyoung-bu line by EM-120 measuring vehicle. It is shown that the wavelet transform can be an effective tool to manage the track irregularity.