• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.611-611
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• 2015

One of the hazard of nature is a drought. Its impact varies from region to region and it is difficult for people to understand and define due to differences in hydrometeorological and social economic aspects across much of the country. In the most general sense, drought originates from a deficiency of precipitation over an extended period of time, usually month, season or more, resulting in a water shortage for some activity, group, or environmental sector. Palmer Drought Severity Index (PDSI) is well known and has been used to study aridity changes in modern and past climates. The PDSI index is estimated over US using USHCN historical data.(e.g. precipitation, temperature, latitude and soil moisture). In this study, low frequency drought variability associated with climate variability such as El-Nino and ENSO is mainly investigated. With respect to the multi-scale analysis, wavelet transform analysis is applied to the PDSI index in order to extract the low frequency band corresponding to 2-8 years. Finally, low frequency patterns associated with drought by comparing global wavelet power, with significance test are explored.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.311-314
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• 2002

This paper has been studied a Image watermarking using PN coding operation where frequency band. By using wavelet transformation, This gets high frequency place HH2 where image watermark puts. Also this places that PN code and binary image are operated. And then, this paper has designed image watermarking index process and extract process, watermarked image which are to add noise is able to extract watermark.

• 한국인터넷방송통신학회논문지
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• 제12권1호
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• pp.1-6
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• 2012

본 논문에서는 다중 환경에서의 Wavelet Pulse를 이용한 TR-UWB 시스템의 성능에 대하여 DPSS 펄스와 2차 가우시안 펄스와 비교 분석하였다. TR-UWB 시스템은 데이터 신호와 레퍼런스 신호를 일정 시간 간격을 두고 같이 보낸다. 이때 두 개의 신호는 동일한 채널을 통과 하므로 수신기에서는 이 레퍼런스 신호를 템플릿으로 사용하여 채널 추정 없이 복조 할 수 있어 수신기의 복잡도를 낮출 수 있는 장점이 있다. 하지만 기존의 가우시안 신호기반의 TR-UWB 시스템은 다중 사용자 환경에서 사용자간의 간섭으로 인한 수신기 성능이 저하되는 단점이 있다. 이 단점을 극복하기 위해 DPSS(Discrete Prolate Shperoidal Sequence)를 이용한 사용자간의 간섭을 줄이는 방법이 있다. 본 논문에서 제안하는 기법은 다 해상도 기법을 이용하여 직교 하는 Wavelet 기저 함수를 생성하고 이 함수를 전송 펄스로 이용하여 사용자간의 간섭을 없애 다중 사용자 환경에서 비트 오율 성능이 향상된 시스템을 제안한다.

• 대한원격탐사학회지
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• 제31권2호
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• pp.149-160
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• 2015

원격탐사 자료 기반의 식생지수 시계열 자료를 이용함에 있어서 가장 중요한 것은 구름이나 에어로졸에 의한 자료의 품질저하 문제이다. 이 연구에서는 MODIS09 지표 분광반사도 자료를 이용하여 구름영향에 의한 저품질 자료를 제거한 뒤 결손자료를 내삽, 평활하여 연속적인 Normalized Difference Vegetation Index (NDVI) 시계열 자료를 생산하였다. 구름에 의한 영향을 제거하기 위한 방법으로 MODIS 분광반사도 자료를 이용한 5가지의 구름탐지기법을 선정하여 비교, 평가하였다. 위성자료에서 제공하는 품질관리정보 (Quality Assessment, QA)에서 구름이라고 판단한 경우, MODIS09 Band 3 반사도가 10% 이상인 경우와 20% 이상인 경우, Cloud Detection Index (CDI)가 임계값 이상인 경우, 센서 천정각이 $32.25^{\circ}$ 이상인 경우를 각각 구름으로 판단하였다. 구름탐지로 인해 발생한 자료의 결손은 선형적 내삽 기법을 이용하여 보정한 뒤 Savitzky-Golay (S-G) 필터와 웨이브렛 변환을 각각 적용하여 평활하였다. 구름 탐지 기법은 10% 이상 Band 3 반사도 제거 기법(85%), Quality Control (QC) (82%), 20% 이상 Band 3 반사도 제거 기법(81%)의 순으로 높은 구름탐지율을 보였다. 웨이브렛 변환은 선형의 시계열 패턴을 얻을 수 있지만 원 자료의 최대값을 반영하지 못하는 반면 S-G 필터는 구름에 의한 신뢰도 낮은 값은 제거하면서도 NDVI 원 자료의 최대값을 유지하여 시계열 자료의 계절적 특성을 잘 보여주는 것을 확인하였다. 이 연구에서는 구름의 탐지, 결손 내삽, 평활 기법의 순차적인 자료처리기법을 적용하여 구름 영향을 제거한 고품질의 시계열 자료의 생산이 가능함을 확인하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2013년도 추계학술대회 논문집
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• pp.63-64
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• 2013

Induction motors' faults detection is almost a popular topic among researchers. Monitoring the output of motors is a key factor in detecting these faults. (Short-time) Fourier, (continuous, discrete) wavelet, and extended Park vector transformations are among the methods for fault detection. One major deficiency of these methods is not being able to detect the severity of faults that carry low energy information, e.g. in ball bearing system failure, there is absolutely no way to detect the severity of fault using Fourier or wavelet transformations. In this paper, the authors have applied the Discrete Wavelet Transform (DWT) frequency-domain analysis to detect bearing faults in an induction motor. In other words, in discrete transform which the output signal is decomposed in several steps and frequency resolution increases considerably, the frequency-band analysis is performed and it will be verified that first of all, fault sidebands become more recognizable for detection in higher levels of decomposition, and secondly, the inner race bearing faults turn out easier in these levels; and all these matter because of eliminating the not-required high energy components in lower levels of decomposing.

• Journal of Electrical Engineering and Technology
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• 제10권6호
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• pp.2315-2325
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• 2015

Induction motors are widely used in industrial processes since they offer a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored, might lead to an unexpected interruption at the industrial plant. Therefore, the condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in induction-motor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the digital implementation of the monitoring algorithm based on the association of the Time Synchronous Averaging technique and Discrete Wavelet Transform. Experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the combined “Time Synchronous Averaging – Discrete Wavelet Transform” approach.

• 한국컴퓨터산업학회논문지
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• 제4권4호
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• pp.589-598
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• 2003

기존의 DWT(Discrete Wavelet Transform) 영역에서 프랙탈 영상압축은 B${\times}$B 블록 크기로 정의역과 치역블록을 구분한 후, 임의의 치역 블록에 대하여 모든 정의역 블록을 탐색하였다. 이러한 기존의 방법은 전체영상 대하여 정의역을 탐색함으로 부호화시 많은 시간이 소요되었다. 이러한 단점을 개선하고 화질을 개선하기 위해 본 논문에서는 DWT 영역에서 레벨과 대역별로 스케일 인자를 갖는 웨이브릿 기반 프랙탈 영상압축 방법을 제안한다. 제안한 방법은 웨이브릿 기반 영역에서 셀프 아핀 시스템을 이용하여 각각의 치역 블록에 대하여 정의역 블록을 선택할 때, 공간적으로 같은 위치에 있는 상위 레벨과 대역별로 AC 계수를 정의역으로 선택한다. 그래서 부호화 시간과 화질을 개선할 수 있다.

• 대한의용생체공학회:의공학회지
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• 제30권4호
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• pp.294-305
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• 2009

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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• pp.269-272
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• 2000

It is need to develop and apply a human pulse diagnosis system providing a quantitative and automatic analysis in the the oriental medicine. In order to analyze quantitatively the characteristic of pulsation, each of points had to be recognized accurately notifying the existence and the position of feature point in the wave form. And getting the period of human pulse. Thus, in this paper, it is proposed the preprocessing method of human pulse and the detection method of period by Wavelet Transformation. The human pulse is seprated from each band through Wavelet Transformation and feature points can be recognized through over the fact, and then the parameter of proposed Mac-Jin parameter is measured. Commonly, Human pulse signal has often various noises which are baseline drift, high frequency noise and so on. So it is significant to remove that noises. Thus, in this paper, the one period of human pulse is deciede and the feature points are detected after doing the preprocessing by wavelet transformation. As a result, it could be confirmed that this method is effective as a real program for the auto-diagnosis of human pulse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2434-2453
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• 2019

To improve the separation performance of time-frequency overlapped radar and communication signals from a single channel, this paper proposes an effective separation method based on an improved empirical wavelet transform (EWT) that introduces a fast boundary detection mechanism. The fast boundary detection mechanism can be regarded as a process of searching, difference optimization, and continuity detection of the important local minima in the Fourier spectrum that enables determination of the sub-band boundary and thus allows multiple signal components to be distinguished. An orthogonal empirical wavelet filter bank that was designed for signal adaptive reconstruction is then used to separate the input time-frequency overlapped signals. The experimental results show that if two source components are completely overlapped within the time domain and the spectrum overlap ratio is less than 60%, the average separation performance is improved by approximately 32.3% when compared with the classic EWT; the proposed method also improves the suitability for multiple frequency shift keying (MFSK) and reduces the algorithm complexity.