• 한국통신학회논문지
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• 제40권9호
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• pp.1725-1727
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• 2015

본 논문은 MIMO 시스템을 위한 QR 분해 기반의 순차적 신뢰 전파 검출 기법을 제안한다. 제안 기법은 매 반복 과정마다 가장 작은 차수를 가지는 관측 노드의 메시지부터 순차적인 갱신 과정을 진행하여 수렴 속도 향상을 도모한다. 모의실험을 통해 제안 기법이 기존 기법들 대비 향상된 오류 성능을 달성함과 동시에 수렴 속도를 크게 개선함을 확인하였다.

• 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.

• 전자공학회논문지S
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• 제35S권3호
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• pp.176-184
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• 1998

We present a sequential factorization method using singular value decomposition (SVD) for recovering both the three-dimensional shape of an object and the motion of camera from a sequence of images. We employ paraperpective projection [6] for camera model to handle significant translational motion toward the camera or across the image. The proposed mthod not only quickly gives robust and accurate results, but also provides results at each frame becauseit is a sequential method. These properties make our method practically applicable to real time applications. Considerable research has been devoted to the problem of recovering motion and shape of object from image [2] [3] [4] [5] [6] [7] [8] [9]. Among many different approaches, we adopt a factorization method using SVD because of its robustness and computational efficiency. The factorization method based on batch-type computation, originally proposed by Tomasi and Kanade [1] proposed the feature trajectory information using singular value decomposition (SVD). Morita and Kanade [10] have extenened [1] to asequential type solution. However, Both methods used an orthographic projection and they cannot be applied to image sequences containing significant translational motion toward the camera or across the image. Poleman and Kanade [11] have developed a batch-type factorization method using paraperspective camera model is a sueful technique, the method cannot be employed for real-time applications because it is based on batch-type computation. This work presents a sequential factorization methodusing SVD for paraperspective projection. Initial experimental results show that the performance of our method is almost equivalent to that of [11] although it is sequential.

• 대한수학회보
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• 제53권3호
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• pp.853-874
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• 2016

Based on a particular overlapping domain decomposition technique, a parallel finite element discretization algorithm for the generalized Stokes equations is proposed and investigated. In this algorithm, each processor computes a local approximate solution in its own subdomain by solving a global problem on a mesh that is fine around its own subdomain and coarse elsewhere, and hence avoids communication with other processors in the process of computations. This algorithm has low communication complexity. It only requires the application of an existing sequential solver on the global meshes associated with each subdomain, and hence can reuse existing sequential software. Numerical results are given to demonstrate the effectiveness of the parallel algorithm.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.818-823
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• 2000

In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.

• 제어로봇시스템학회논문지
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• 제5권4호
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• pp.403-410
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• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• 품질경영학회지
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• 제32권3호
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• pp.141-152
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• 2004

This study describes process and method to establish concurrent and/or sequential schedule planning for the system design process of the EIA632 standard. For this purpose, the study suggest Process and method that are context analysis of standard process, interface definition from activity decomposition, integration of related activities, and definition of concurrent and/or sequential work flow. The proposed process and method will contribute to minimize time loss that is emerged from activities iteration.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.980-983
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• 2005

An agent Is an autonomous process that recognizes external environment, exchanges knowledge with external machines and performs an autonomous decision-making function in order to achieve common goals. The techniques fur tackling complexity in software need to be introduced. That is decomposition, abstraction and organization. Agent-oriented model ing has the merits of decomposition. In decomposition, each autonomous unit may have a control thread. Thread is single sequential flow in program. The use of thread in agent modeling has an important meaning in the performance of CPU and the relation of autonomous units.

• 한국멀티미디어학회논문지
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• 제11권11호
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• pp.1480-1490
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• 2008

무손실 오디오 부호화기에 있어서 선형예측기 및 이에 적합한 엔트로피 부호화기의 설계가 가장 중요한 부분이다. 본 논문에서는 공분산 방법에 콜레스키 분해를 이용하여 선형예측기의 계수를 계산하였고, 그 결과를 다항 예측기와 비교하여 예측 에러가 최소화되는 선형예측기를 선택하도록 하였다. 엔트로피 부호화기는 골롬-라이스 부호를 사용하였고, 골롬-라이스 부호화기의 매개변수를 계산하기 위해 블록기반 매개변수 예측 방법과 LOCO-I, RLGR의 순차 적응 방법을 적용하였다. 실험 결과 블록기반 매개변수 예측 방법과 제안 방식의 예측기를 이용하면 자기상관 방법과 레빈슨-더빈을 사용하는 FLAC 무손실 부호화기보다 $2.2879%{\sim}0.3413%$ 압축률이 향상되는 결과를 나타내었고, 제안 방식의 예측기와 LOCO-I 순차 적응 방법을 이용한 경우는 $2.2381%{\sim}0.0214%$ 압축률이 향상되는 결과를 나타내었다. 그러나 제안 방식의 예측기와 RLGR 순차 적응 방법을 이용한 경우는 특정 신호에서만 압축률이 향상되었다.

• 한국통신학회논문지
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• 제24권9A호
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• pp.1419-1424
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• 1999

형태학적 필터를 영상 처리 시스템에 효율적으로 구현하기 위하여서는 영상 처리 시스템의 구조적인 제약으로 인하여 형태소의 크기가 작아야 하며, 따라서 크기가 큰 형태소를 가지는 필터의 구현을 위하여 주어진 형태소를 작은 크기의 형태소로 분해하는 과정이 필요하다. 본 논문에서는 임의의 형태학적 필터를 3$\times$3 Pipeline Machine에 효율적으로 구현하기 위하여 모양과 크기에 아무 제한 없이 행태소를 분해하는 알고리즘을 개발한다. 먼저 주어진 형태소를 순차적 방법으로 합집합 분해하고, 각 분해된 결과를 다시 3$\times$3 크기의 형태소로 최적 분해하여 최종 형태소 분해 결과를 얻는다. 개발된 분해 알고리즘을 형태소에 적용하여 분해 결과를 구하였으며, 최적에 매우 근접한 결과를 얻을 수 있었다.