• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.137-138
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• 2008

수많은 방식의 ECG 압축 코딩 알고리즘이 개발되어왔고 현재도 개발 중이지만 각자의 알고리즘의 성능에 유리한 특정 데이터만을 분석하고 압축율이 다름으로 인해 다른 알고리즘과의 성능 비교를 객관화하고 있지 못하였다. 본 연구에서는 기존의 MIT-BIH에서 제공하는 ECG 신호와 달리 시뮬레이션된 ECG 신호를 기반으로 각각의 알고리즘에 대한 성능비교를 하여 ECG신호의 특성에 따른 코딩 알고리즘의 압축율 및 평균 오차 에러의 정도를 분석비교하였다. 비교 대상 알고리즘으로는 상용화되어 널리 사용되는 Delta 코팅 방식의 문턱치를 갖는 Discrete Pulse Code Modulation과 Discrete Cosine Transform, Lifting Wavelet Transform과 Wavelet 기반 Linear Prediction 4가지 알고리즘을 대상으로 분석하였다. Compression Ratio (CR)을 2,4로 고정하고 Percentage of Root-mean-square difference (PDR)를 분석 한 결과, EMG 잡음의 진폭변 화에는 0.1mV이하의 경우 OCT, Wavelet Lifiting Transform이 낮은 PDR을 보였고, 01.mV이상의 경우 Wavelet based Linear Prediction (WLP)이 낮은 PDR을 보였다. Heart Rate의 간격에 변화를 주어 불규칙성이 있는 경우 WLP가 가장 안좋은 PDR 결과를 보였으며, DCT가 가장 낮고 안정된 PDR 결과를 보였다. DPCM은 노이즈와 진폭간격의 변화에 상관없이 압축율에 의해 크게 PDR 성능 결과가 변화함을 나타내었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.272-275
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• 1999

In this paper, a wavelet transform-based adaptive interference excision scheme using the adaptive algorithm which suppresses narrow band interference in the wavelet transform domain for the direct spread modulation system application, is introduced. Using the Monte-Carlo simulation, the bit error probabilities of the direct spread communication systems with the excision systems of two kinds of Daubechies wavelets (db2, db8) in the transform domain, are analysed. With these results, it is shown that the performance of a system depends on the characteristics of wavelet being used. And with this scheme, we expect effective improvements in the direct spread communication system performance.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.152-153
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• 2014

본 논문에서는 이차전지의 특성비교/분석을 위해 이산 웨이블릿 변환(DWT;discrete wavelet transform)과 웨이블릿 패킷 변환(WPT;wavelet packet transform)을 적용한 연구를 소개한다. 다해상도 분석(MRA; multi resolution analysis)의 시간-주파수 분석을 통해 저주파 성분(approximation;$A_n$)과 고주파 성분(detail;$D_n$)로 분해되는 것은 두 방법 동일하다. 하지만, 이산 웨이블릿 변환이 단순히 저대역 부분만 계속 분해하는 것과 달리 웨이블릿 패킷 변환은 저대역과 고대역을 모두 분해하여 높은 분해성능을 가지는 웨이블릿의 일반화이다. 웨이블릿 패킷 변환을 자세히 소개하고 이를 이차전지에 적용하여 이산 웨이블릿 변환과의 상관성을 정리하였다.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.461-469
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• 2000

A wavelet analysis in a field of analytics is to create a reconstruction theorem of Plancherel form. And a series of wavelet is to create a discrete is to create a discrete reconstruction theorem for a frame theory and a multiresolution analysis theory. As a generation of reconstruction theorem, a wavelet correspond to it is generated. That is to be like a basic wavelet which is satisfied an admissibility condition in CWT and a Daubechies wavelet using MRA in wavelet series and a Meyer wavelet using a frame theory. In this paper, we discover a discrete reconstruction theorem which is superior to a conventional discrete reconstruction theorem by extending admissibility condition used in CWT and develop a New $L^1$-wavelet group. A new $L^1$-wavelet is applied to a signal reconstruction and a signal analysis in time-frequency region.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.3
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• pp.75-81
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• 2007

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 Fourier 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 Fast Fourier Transform(FFT).

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.960-962
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• 2017

This thesis suggests method that How sound sources used to simulation that can be used to military training and education divide each frequency and each bandwidth filtering method. method for frequency dividing and denoising are suggested into Wavelet analysis. And We materialize authoring tool about filtering that design for wavelet job.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.758-763
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• 2006

In various fields of basic science and engineering, in order to present signals and systems exactly and acquire useful information from spatial and timely changes, many researches have been processed. In these methods, the Fourier transform which represents signal as the combination of the frequency component has been applied to the most fields. But as transform not to consider time information, the Fourier transform has its limitations of application. To overcome this problem, a variety of methods including the wavelet transform have been proposed. As transform to represent signal by using the changing window, according to scale parameter in time-scale domain, the wavelet transform is capable of multiresolution analysis and defines various functions according to the application environments. In this paper, to detect features of signal we analyzed wavelet the spectrum by using the basis function of the fourier transform.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.311-320
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• 2006

Digital filters designed using wavelet theory are applied to bathymetry data acquired from KR5 area of Korea Deepsea Mining Area. The filters used in this study are the linear B-spline wavelet filter and derivative of a Cubic B-spline filter. With proper tuning of the digital filters, we can identify the location and orientation of the abyssal hill and abyssal trough in bathymetry. These features obtained from the digital filters are well correlated with bathymetric image. This quantitative information, which can be used to understand the underlying geophysical processes, can be further processed to obtain the spacing, orientation and distribution of the abyssal hill. This wavelet analysis of bathymetry provides good data to select the mining site.

• Explosives and Blasting
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• v.38 no.1
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• pp.14-22
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• 2020

Bit damage is one of the primary causes of decreasing drilling efficacy. Nevertheless the management of bit ware and failure are often left for field engineers' experience. Thus it is imperative to establish a proper system to predict and manage the bit damage during the rock drilling process. In this study, the drilling sound signal has been recorded and analyzed using wavelet transform analysis to identify the exact moment of bit failure. Through the analysis wavelet time-frequency spectrums have been constructed and an abnormal point has been identified with 0.9 of wavelet transform value at the 652.8s on a frequency band around 500Hz. Furthermore it is also observed that the penetration rate of the damaged bit has been decreased to 23mm/s which is 9mm/sec lower than the average of undamaged bit. The study verifies that wavelet transform analysis can be used to build a system to diagnose the bit damage while drilling.