• 대한원격탐사학회지
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• 제26권6호
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• pp.681-691
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• 2010

LiDAR waveform decomposition plays an important role in LiDAR data processing since the resulting decomposed components are assumed to represent reflection surfaces within waveform footprints and the decomposition results ultimately affect the interpretation of LiDAR waveform data. Decomposing the waveform into a mixture of Gaussians involves two related problems; 1) determining the number of Gaussian components in the waveform, and 2) estimating the parameters of each Gaussian component of the mixture. Previous studies estimated the number of components in the mixture before the parameter optimization step, and it tended to suggest a larger number of components than is required due to the inherent noise embedded in the waveform data. In order to tackle these issues, a new LiDAR waveform decomposition algorithm based on the sequential approach has been proposed in this study and applied to the ICESat waveform data. Experimental results indicated that the proposed algorithm utilized a smaller number of components to decompose waveforms, while resulting IMP value is higher than the GLA14 products.

• 대한원격탐사학회지
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• 제25권6호
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• pp.547-557
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• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• 대한원격탐사학회지
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• 제37권6_1호
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• pp.1709-1718
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• 2021

항공수심라이다[airborne bathymetric LiDAR (Light Detection And Ranging)] 시스템의 웨이브폼(waveform) 데이터는 기존의 이산반환(discrete-return) 데이터에 비해 정확도, 해상도, 신뢰도가 향상된 데이터를 제공하며, 사용자의 데이터 처리 통제력을 강화하며 반환신호에 대한 추가적인 정보 추출을 가능하게 한다. 웨이브폼 분해(waveform decomposition)는 수면과 해저 반사, 수중산란 및 각종 노이즈가 혼재되어 수신된 웨이브폼으로부터 각각의 에코(echo)를 분리하는 기술로, 지형 포인트 추출을 위해 선행되어야 하는 처리 과정이자 측량 성과를 좌우하는 주요 기술이다. 본 연구에서는 항공수심라이다 원시 데이터로부터의 포인트 추출 성능을 향상시키 위해 새로운 웨이브폼 분해 기술을 개발하였다. 기존의 웨이브폼 분해 기술들이 웨이브폼 피크(peak)들을 가우시안(Gaussian) 분해의 초기값으로 사용하여 분해된 에코의 개수와 분해 성능이 피크 탐지 결과에 좌우되는데 반해, 제안한 기술은 최초 피크들 외에 잠재적인 피크 후보들을 추정하여 추가함으로써, 분해 모델의 근사 정확도를 향상시켰다. 국내 개발된 항공수심라이다 장비인 씨호크(Seahawk)로부터 동해안에서 취득된 웨이브폼 데이터를 이용한 실험 결과, 가우시안 분해 방법 대비 제안한 방법의 모델 근사 적합도(RMSE 기준)가 약 37% 향상된 결과를 얻었다.

• 한국항공우주학회지
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• 제50권3호
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• pp.193-201
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• 2022

SOQPSK-TG는 주파수 효율과 전력 효율이 매우 우수한 항공기 텔레메트리용 변조신호이다. 본 논문에서는 부분응답 SOQPSK-TG 변조방식의 위상파형을 선형 근사하여 완전응답 이중 듀오바이너리 SOQPSK(SOQPSK-DD) 신호로 모델링하였다. 그리고 XTCQM 기법과 롤랑분해 기법을 사용하여 SOQPSK-DD 신호를 선형 펄스 파형을 갖는 OQPSK로 근사 모델링하였고 두 가지 기법의 결과가 동일함을 증명하였다. 또한 SOQPSK-DD 신호의 로랑분해 파형이 SOQPSK-TG 신호의 로랑분해 파형을 근사한 파형임을 확인하였고, SOQPSK-DD의 로랑분해 파형을 검출필터에 적용한 결정궤환 IQ-검출기가 기존보다 단순한 파형으로도 거의 동일한 성능을 발휘함을 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.475-476
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• 2007

Electroglottography (EGG) is a technique used to register laryngeal behavior indirectly by a measuring the change in electrical impedance across the throat during speaking. However, EGG waveform is affected by laryngeal muscles which fluctuate the vocal cords, and which result in baseline wander. It is required to reduce baseline wander in EGG waveform, because EGG waveform is used for input signal of nonlinear speech synthesizer in next chapter. In vocal cords, the abduction-adduction of glottis is mainly controlled by the posterior cricoarytenoid (abductor) and interarytenoid (adductor) muscles respectively. Empirical Mode Decomposition method was adopted in cancellation of EGG waveform baseline wandering, and showd better performance than that of high pass filter with 500 order.

• 대한의용생체공학회:의공학회지
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• 제15권3호
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• pp.281-288
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• 1994

In this paper, a new decomposition method of the interference EMG signal using MAMDF filtering and digital signal processor. The efficient software and hardware signal processing techniques are employed. The MAMDF filter is employed in order to estimate the presence and likely location of the respective templates which may include in the observed mixture, and high-resolution waveform alignment is employed in order to provide the optimal combination set and time delays of the selected templates. The TMS320C25 digital signal processor chip is employed in order to execute the intensive calculation part of the software. The method is verified through a simulation with real templates which are obtain ed from needle EMG. As a result, the proposed method provides an overall speed improvement of 32-40 times.

• 한국소음진동공학회논문집
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• 제25권6호
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• pp.399-405
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• 2015

In this work we use the mode decomposition technique employing chirplet transform, which is able to separate the individual modes from dispersive and multimodal waveform measured with the magnetostrictive sensor. The mode decomposition technique is also used to estimate the time-frequency centers and individual energies of the reflection, which would be used to locate and characterize axial defects. The arrival times of the separated modes are calculated and the axial defect lengths can be evaluated by using the estimated arrival time. Results from an experiment on a carbon steel pipe are presented and it is shown that the accurate and quantitative defect characterization could become enabled using the proposed technique.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2011년도 춘계학술대회
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• pp.187-188
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• 2011

Independent component analysis (ICA) is a method separating the mixture of signals into statistically and mutually independent ones. It has been applied to not only the Cocktail-party problem but also EEG analysis using the EEG waveform, digital signal processing, image processing and cognitive technique field actively. This study aims to propose a procedure to estimate the modal responses and mode shapes of a floating structure by using the ICA method from measured responses of the floating structure.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1807-1813
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• 2018

In this paper, the fault line selection and location problems of single line-to-ground (SLG) fault in distribution network are addressed. Firstly, the adaptive filtering property for empirical mode decomposition is formulated. Then in view of the different characteristics showed by the intrinsic mode functions(IMF) under different fault inception angles obtained by empirical mode decomposition, the sign of peak value about the low-frequency IMF and the capacitance transient energy is chosen as the fault line selection criteria according to the different proportion occupied by the low-frequency components. Finally, the fault location is determined based upon the comparison result with adjacent fault passage indicators' (FPI) waveform on the strength of the interaction between the distribution terminal unit(DTU) and the FPI. Moreover, the logic nodes regarding to fault line selection and location are newly expanded according to IEC61850, which also provides reference to acquaint the DTU or FPI's function and monitoring. The simulation results validate the effectiveness of the proposed fault line selection and location methods.

• 한국소음진동공학회논문집
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• 제24권8호
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• pp.636-642
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• 2014

The sensor configuration of the magnetostrictive guided wave system can be described as a single continuous transducing element which makes it difficult to separate the individual modes from the reflected signal. In this work we develop the mode decomposition technique employing chirplet transform, which is able to separate the individual modes from dispersive and multimodal waveform measured with the magnetostrictive sensor, and to estimate the time-frequency centers and individual energies of the reflection, which would be used to locate and characterize defects. The reflection coefficients are calculated using the modal energies of the separated mode. Results from experimental results on a carbon steel pipe are presented, which show that the accurate and quantitative defect characterization could become enabled using the proposed technique.