• 한국정보통신학회논문지
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• 제10권6호
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• pp.1025-1031
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• 2006

본 논문에서는 FIR 근사를 기반으로한 전역통과 시스템에 대한 deconvolution 필터링 기법을 제안한다. 제안한 기법은 안정한 non-causal deconvolution 필터를 FIR 근사에 의해 안정한 causal deconvolution 필터로 변환시키는 것이다. 본 논문에서 보인바와 같이 전역통과시스템에 대한 deconvolution 필터의 임펄스 응답은 전역통과 시스템 자체의 임펄스 응답의 거울 영상(mirror image) 임을 알 수 있다. 이와 같이 전역통과 시스템에 대한 임펄스 응답과 그 시스템의 deconvolution 필터에 대한 임펄스 응답의 대칭성 때문에, 제안한 기법은 전역 통과 필터의 차수에 상관없이 동일하게 적용할 수 있다. 제안한 기법의 성능을 보이기 위하여 1차, 2차 및 400차의 전역통과 시스템에 대한 컴퓨터 시뮬레이션 결과를 포함한다.

• Communications for Statistical Applications and Methods
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• 제23권1호
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• pp.71-83
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• 2016

In this paper we discuss a deconvolution density estimator obtained using the support vector machines (SVM) and Tikhonov's regularization method solving ill-posed problems in reproducing kernel Hilbert space (RKHS). A remarkable property of SVM is that the SVM leads to sparse solutions, but the support vector deconvolution density estimator does not preserve sparsity as well as we expected. Thus, in section 3, we propose another support vector deconvolution estimator (method II) which leads to a very sparse solution. The performance of the deconvolution density estimators based on the support vector method is compared with the classical kernel deconvolution density estimator for important cases of Gaussian and Laplacian measurement error by means of a simulation study. In the case of Gaussian error, the proposed support vector deconvolution estimator shows the same performance as the classical kernel deconvolution density estimator.

• Communications for Statistical Applications and Methods
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• 제19권4호
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• pp.517-526
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• 2012

In this paper a support vector method is proposed for use when the sample observations are contaminated by a normally distributed measurement error. The performance of deconvolution density estimators based on the support vector method is explored and compared with kernel density estimators by means of a simulation study. An interesting result was that for the estimation of kurtotic density, the support vector deconvolution estimator with a Gaussian kernel showed a better performance than the classical deconvolution kernel estimator.

• Communications for Statistical Applications and Methods
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• 제17권3호
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• pp.451-457
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• 2010

This paper considers the problem of nonparametric deconvolution density estimation when sample observa-tions are contaminated by double exponentially distributed errors. Three different deconvolution density estima-tors are introduced: a weighted kernel density estimator, a kernel density estimator based on the support vector regression method in a RKHS, and a classical kernel density estimator. The performance of these deconvolution density estimators is compared by means of a simulation study.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집A
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• pp.84-89
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• 2001

Ultrasonic pulse echo method comes to be difficult to apply to the multi-layered structure with very thin layer, because the echoes from the top and the bottom of the layer are overlapped. Conventionally method, deconvolution technique has been used for the decomposition of overlapped UT signals, however it has disabilities when the waveform of the transmitted signal is distorted according to the propagation. In this paper, the wavelet transform based deconvolution (WTBD) technique is proposed as a new signal processing method that can decompose the overlapped echo signals in A-Scan signal with superior performances compared to the conventional deconvolution technique. Performances of the proposed method are shown by through computer simulations using model signal with noise and are demonstrated by through experiments for the fabricated acryl rod with a thin steel plate bonded to it.

• Molecules and Cells
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• 제46권2호
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• pp.99-105
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• 2023

Tumors are surrounded by a variety of tumor microenvironmental cells. Profiling individual cells within the tumor tissues is crucial to characterize the tumor microenvironment and its therapeutic implications. Since single-cell technologies are still not cost-effective, scientists have developed many statistical deconvolution methods to delineate cellular characteristics from bulk transcriptome data. Here, we present an overview of 20 deconvolution techniques, including cutting-edge techniques recently established. We categorized deconvolution techniques by three primary criteria: characteristics of methodology, use of prior knowledge of cell types and outcome of the methods. We highlighted the advantage of the recent deconvolution tools that are based on probabilistic models. Moreover, we illustrated two scenarios of the common application of deconvolution methods to study tumor microenvironments. This comprehensive review will serve as a guideline for the researchers to select the appropriate method for their application of deconvolution.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2014년도 추계학술대회
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• pp.53-55
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• 2014

본 논문에서는 deconvolution 알고리즘 중에 하나인 Richardson-Lucy deconvolution 의 개선된 알고리즘을 제시한다. Richardson-Lucy deconvolution 의 단점인 반복횟수가 증가할수록 노이즈도 같이 증폭되는 현상을 소개하고 이를 개선하기 위해 기존 알고리즘에 전, 후처리 필터를 이용하여 노이즈 증폭을 억제한다. 또한 다른 노이즈 증폭을 억제하는 알고리즘과 제안된 알고리즘의 비교를 통해서 제안된 알고리즘의 성능을 보여준다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.673-675
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• 2003

The image restoration algorithm for microwave imaging radiometer is proposed. A blind deconvolution method was proposed. A point spread function was identified and three deconvolution schemes were employed, Wiener filtering, Lucy- Richardson deconvolution, and Maximum Likelihood blind deconvolution. The experimental data is illustrated with restored image.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 춘계학술대회 논문집
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• pp.606-609
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• 2008

Deconvolution is one of the most used techniques for processing seismic reflection data. It is applied to improve temporal resolution by wavelet shaping and removal of short period reverberations. Several deconvolution algorithms such as predicted, spike, minimum entropy deconvolution and so on has been proposed to obtain such above purposes. Among of them, $\iota_1$ norm proposed by Taylor et al., (1979) and used to compared to minimum entropy deconvolution by Sacchi et al., (1994) has given some advantages on time computing and high efficiency. Theoritically, the deconvolution can be considered as inversion technique to invert the single seismic trace to the reflectivity, but it has not been successfully adopted due to noisy signals of the real data set and unknown source wavelet. After stacking, the seismic traces are moved to zero offset, thus each seismic traces now can be a single trace that is created by convolving the seismic source wavelet and reflectivity. In this paper, the fundamental of $\iota_1$ norm deconvolution method will be introduced. The method will be tested by synthetic data and applied to improve the stacked section of gas hydrate.

• 지구물리와물리탐사
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• 제13권4호
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• pp.323-329
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• 2010

동해 울릉분지에서 가스하이드레이트 탐사를 목적으로 획득된 탄성파 중합 자료에 다음 세 가지의 디컨볼루션을 적용하여 지층경계면을 분해하는 특성을 분석하였다: (1) 트레이스별 최소위상 스파이킹 디컨볼루션 (2) 트레이스 평균 최소위상 디컨볼루션 (3) 검층자료를 이용한 디컨볼루션. 트레이스별 최소위상 스파이킹 디컨볼루션의 경우 수직 분해능은 증가하지만 수평 연장성이 감소하는 경향을 보였다. 각 트레이스에서 구한 최소위상 파형요소를 평균하여 구한 대표 파형요소를 이용하는 두 번째 방법은 전체적으로 트레이스별 스파이킹 디컨볼루션의 결과와 비슷하지만 해저면 모방 반사면이 보다 연속적이고 일관된 결과를 보이며 하부 반사면들이 더 뚜렷하게 나타난다. 세 번째 방법의 결과는 쇄설류 퇴적체 내부가 좀 더 상세하게 나타나며 해저면과 해저면 모방 반사면의 파형이 이상적 영위상 형태를 보이며 반사면의 연속성이 향상되었음을 보여준다. 이러한 특성은 가스하이드레이트 안정영역의 하부경계를 지시하는 해저면 모방 반사면의 진폭특성분석과 퇴적상 해석을 향상시키므로 탐사 지역의 가스하이드레이트 분포와 자원량을 정확히 추정하는 데에 도움을 준다.