• Journal of Korean Clinical Health Science
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• v.4 no.4
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.456-459
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• 2001

In this paper, a wavelet neural network for adaptive control was proposed. The structure of this network is similar to that of the multilayer perceptron(MLP), except that here the sigmoid functions are replated by mother wavelet function in the hidden units. The simulation result showed the effectiveness of using the wavelet neural network structure in the adaptive control of one-link manipulator.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.265-267
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• 2003

The wavelet transform(WT) has been extensively applied in solving many problems in applied science and engineering following its introduction in early 1980's. The WT analyzes a signal in a changeable frequency range by employing a moving window whereby along time window is used to obtain low frequency information and short time window is used to obtain high frequency information. In this paper, after various fault types in 154 KV transmission system was simulated by using EMTP, and the RMS values by changing Mother wavelet was calculated by applying wavelet transform to the simulated voltage and current signal.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.463-464
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• 2015

이산 웨이블릿 변환(DWT;discrete wavelet transform)의 다해상도 분석(MRA;multi resolution analysis)을 효율적으로 수행하기 위해서는 적절한 모함수(mother wavelet)의 선택이 필수적이다. 본 논문에서는, 노이즈가 포함된 충방전 전압의 디노이징(denoising)을 구현할 때, 모함수에 따른 디노이징 성능을 비교 및 분석한다. 고정된 MRA 레벨에서 6개의 모함수를 비교하되, 각 모함수에서 최대 SNR(signal-to-noise ratio)을 가지는 타입을 대푯값으로 정하여 모함수에 따른 디노이징 성능을 비교한다. 이를 위해, 하드 임계화(hard-thresholding) 및 소프트 임계화(soft-thresholding) 기법을 적용한다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.62_63
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• 2009

This paper is distribution utility to generation of analysis fault several cases on the ground of substation in a energy meter three phase current, voltage data measurement to fault type and characteristics. Mother wavelet transformation of suitable to method algorism from the distribution utility to generation of fault in image impedance etc several parameter for utility characteristics effective to probatory.

• Journal of Mechanical Science and Technology
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• v.15 no.5
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• pp.535-543
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• 2001

This paper presents the ride comfort analysis of a vehicle based on wavelet transform. Traditionally, the objective evaluation of impact harshness is based on the vibration dose value (VDV) and frequency weighting method. These methods do not consider the damping effect of the suspension system of a vehicle. In this paper, the damping is estimated using wavelet transform based on Morlet mother wavelet and its effect is considered for the subjective evaluation of impact harshness of a car.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.213-217
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.1
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• pp.35-40
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• 2015

Generators are the most complex and expensive single element in a power system. The generator protection relays should to minimize damage during fault states and must be designed for maximum reliability. A conventional CDR(Current Differential Relaying) technique based on DFT(Discrete Fourier Transform) filter have the disadvantages that the time information can lead to loss in the process of converting the signal from the time domain to the frequency domain. A WT(Wavelet transform) and WT analysis is known that it is possible with the local analysis of the fault and transient signal. In this paper, to overcome the defects in the DFT process, an application of WT for fault detection of generator is presented. This paper describes an selection of mother Wavelet to detect faults of generator. Using collected data from the fault simulation with ATPdraw, we analyzed the several mother Wavelet through the course of MLD(multi-level decomposition) using MATLAB software. Finally, it can be seen that the proposed technique using detail coefficient of Daubechies level 2 which can be fault discriminant of generator.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.118-122
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• 2000

In this study, Ringing is investigated by continuous wavelet transform. Ringing is considered to be one of the typical transient phenomena in the field of ocean engineering. The wavelet analysis is adopted to analyze ringing from the point that wavelet analysis is capable of frequency analysis as well as time domain analysis. The use mother wavelet is the Morlet wavelet. The relation between the frequency of the time series and that of wavelet can be clearly defined with Mor1et wavelet. Experimental data obtained by other researchers was used. The wave height time series and acceleration times series of the surface piercing cylinder were analyzed. The results show that the proposed scheme can detect typical frequency region by the time domain analysis which could hardly be detected if one relied on the frequency analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.113-118
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• 2024

In this paper, we propose an optimal wavelet in a system for canceling background noise of acoustic signals. This system performed Discrete Wavelet Transform(DWT) instead of the existing Short Time Fourier Transform(STFT) and then improved noise cancellation performance through a deep learning process. DWT functions as a multi-resolution band-pass filter and obtains transformation parameters by time-shifting the parent wavelet at each level and using several wavelets whose sizes are scaled. Here, the noise cancellation performance of several wavelets was tested to select the most suitable mother wavelet for analyzing the speech. In this study, to verify the performance of the noise cancellation system for various wavelets, a simulation program using Tensorflow and Keras libraries was created and simulation experiments were performed for the four most commonly used wavelets. As a result of the experiment, the case of using Haar or Daubechies wavelets showed the best noise cancellation performance, and the mean square error(MSE) was significantly improved compared to the case of using other wavelets.