• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.595-598
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• 1988

In this paper, a new folding algorithm for design of high density PLA's is proposed. This algorithm generates transform matrix so that programmed region of each row becomes narrow. Based on transform matrix, folding pair is selected. In the process of generating transform matrix, interval degree and dense degree are used to improve folding ratio. This paper also proposes an efficient folding pair graph which has short time of selection folding pair. This proposed algorithm is named PLAFOLII and implemented in C language on VAX-11/750 (UNIX) computer. Through various example, efficiency of this algorithm is verified.

• 한국시뮬레이션학회논문지
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• 제12권2호
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• pp.13-24
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• 2003

In this study, we propose a scheduling analysis method of the Flexible management system using the transitive matrix. The Scheduling problem is a combination-optimization problem basically, and a complexity is increased exponentially for a size of the problem. To reduce an increase of a complexity, we define that the basic unit of concurrency (short BUC) is a set of control flows based on behavioral properties in the net. And we propose an algorithm to divide original system into some BUC. To sum up, we divide a petri net model of the Flexible management system Into the basic unit of concurrency through the division algorithm using the transitive matrix. Then we apply it to the division-scheduling algorithm to find an efficient scheduling. Finally, we verify its efficiency with an example.

• 전기학회논문지
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• 제67권2호
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• pp.239-247
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• 2018

Adaptive Beamforming (ABF) algorithm, which is a typical jammer suppression algorithm, guarantees the performance on the assumption that the jamming characteristics of the TDS (Training Data Sample) are stationary, which are obtained immediately before and after transmitting the pulse signal. Therefore, effective jammer suppression can not be expected when the jamming characteristics are non-stationary. In this paper, we propose a new jammer suppression algorithm, of which power spectrum fluctuates fast. In this case, we assume that the location of the jammer station is fixed during the processing time. By applying the MPM (Matrix Pencil Method) to the jamming signal in TDS, we can estimate jammer parameters such as power and incident angle, of which the power will vary fast in time or range bins after TDS. Though we assume that the jammer station is fixed, the estimated jammer's incident angle has an error due to the noise, which degrades the performance of the jammer suppression as the jammer power increases fast. Therefore, the jammer's incident angle should be re-estimated at each range bin after TDS. By using the re-estimated jammer's incident angle, we can construct new covariance matrix under the non-stationary jamming environment. Then, the optimum weight for the jammer suppression is obtained by inversing matrix estimation method based on the matrix projection with the estimated jammer parameters as variables. To verify the performance of the proposed algorithm, the SINR (signal-to-interference plus noise ratio) loss of the proposed algorithm is compared with that of the conventional ABF algorithm.

• 한국전산구조공학회논문집
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• 제21권1호
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• pp.1-11
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• 2008

전단빌딩에 발생한 손상 추정에 있어서 대상 구조물의 물성치를 가정하고 이상화한 모델을 이용한 역해석이 필요하다. 강성행렬을 이용하는 고전적인 손상추정 방법에 비해 유연도 행렬을 이용한 손상추정은 구조물의 저차모드를 이용하기 때문에 비교적 정확한 값을 계산할 수 있기 때문에 더 효과적으로 알려져 있다. 이 논문에서는 손상추정을 위한 알고리즘으로 유전자 알고리즘(Genetic Algorithm, GA)을 도입하였고, 구조 응답에서 취득할 수 있는 유연도 행렬을 이용하여 역해석을 통한 손상추정 기법을 소개하고 있다. 제안된 손상추정 기법은 전단빌딩의 강성에 대한 정확한 정보가 없는 상황에서 전단빌딩의 손상으로 인한 실제 강성변화량을 추정하도록 하였다. 더불어 open source code인 OPENSEES를 이용하여 전단빌딩 수치해석을 통해 제안된 손상추정 기법의 효율성을 검증하였다.

• Journal of applied mathematics & informatics
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• 제30권3_4호
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• pp.365-380
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• 2012

Non-negative matrix factorization (NMF) is a very efficient method to explain the relationship between functions for finding basis information of multivariate nonnegative data. The multiplicative update (MU) algorithm is a popular approach to solve the NMF problem, but it fails to approach a stationary point and has inner iteration and zero divisor. So the elementwisely alternating projected gradient (eAPG) algorithm was proposed to overcome the defects. In this paper, we use the fact that the equilibrium point is stable to prove the convergence of the eAPG algorithm. By using a classic model, the equilibrium point is obtained and the invariant sets are constructed to guarantee the integrity of the stability. Finally, the convergence conditions of the eAPG algorithm are obtained, which can accelerate the convergence. In addition, the conditions, which satisfy that the non-zero equilibrium point exists and is stable, can cause that the algorithm converges to different values. Both of them are confirmed in the experiments. And we give the mathematical proof that the eAPG algorithm can reach the appointed precision at the least iterations compared to the MU algorithm. Thus, we theoretically illustrate the advantages of the eAPG algorithm.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.227-242
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• 2015

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

• Smart Structures and Systems
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• 제17권6호
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• pp.1017-1030
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• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.

• 제어로봇시스템학회논문지
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• 제10권1호
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• pp.87-95
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• 2004

We proposed the division algorithm that was aimed at dividing system models. It used a transitive matrix to express the relation between place and transition. And the division algorithm was applied to the scheduling problem, with the division-scheduling algorithm. The division-scheduling algorithm was able to calculate the divided subnet table. And it is able to reduce the analysis complexity. In this study, we applied the proposed division algorithm and division-scheduling algorithm to flexible manufacturing system models. We compared the efficiency and performance of the division-scheduling algorithm with the Hillion algorithm, Korbaa algorithm, and Unfolding algorithm proposed in previous researches.

• 한국구조물진단유지관리공학회 논문집
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• 제18권2호
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• pp.30-37
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• 2014

본 연구에서는 개인 컴퓨터의 플래시 메모리가 충분하지 않을 경우 대용량의 플래시 메모리를 필요로 하는 구조해석을 컴퓨터 프로그램으로 수행하는 방법론을 연구하였다. 이러한 문제점의 해결방안으로 강성행렬의 블록화기법 -강성행렬이 몇 개의 블록으로 나뉘고 각각의 블록에 대하여 행렬분해가 수행되는 방법- 을 제안하였으며 제안된 방법론을 바탕으로 컴퓨터 프로그래밍이 가능한 알고리즘을 제시하였다. 끝으로, 본 연구를 바탕으로 구조해석 프로그램을 개발하였으며 몇 가지 기초적인 구조해석 예제를 통하여 개발 알고리즘의 정합성 및 효율성을 확인할 수 있었다.

• 설비공학논문집
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• 제22권8호
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• pp.573-578
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• 2010

Topological matrix which reflects characteristics of network connectivity has been widely used in efficient solving for complicated flow network. Using topological matrix, one can easily define continuity at each node of flow network and make algorithm to automatically generate continuity equation of matrix form. In order to analyze flow network completely it is required to satisfy energy conservation in closed loops of flow network. Fundamental cycle retrieving algorithm based on graph theory automatically constructs energy conservation equation in closed loops. However, it is often accompanied by NP-complete problem. In addition, it always needs fundamental cycle retrieving procedure for every structural change of flow network. This paper proposes alternative mathematical method to analyze flow network without fundamental cycle retrieving algorithm. Consequently, the new mathematical method is expected to reduce solving time and prevent error occurrence by means of simplifying flow network analysis procedure.