• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.193-196
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• 2000

본 논문은 희소어레이의 패턴을 원하는 패턴과 실제 희소어레이의 패턴간의 오차의 계수적 자승치를 미세탐색을 이용하여 최소화하여 최적화하는 방법을 제시한다. 센서의 간격이 어레이 중심에 관하여 대칭인 경우와 비대칭인 경우에 대하여 성능을 점검하며, 어레이 공간의 주어진 영역의 오차함수에 성능 향상을 위하여 계수를 적용한다. 미세탐색을 이용함으로써 계수 최소 방법의 성능이 주빔 부근의 측면롭에 관련하여 향상되는 것이 판명되었다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.7
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• pp.261-271
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• 1986

This paper describes a method for the state estimation considering current measurement component and detection of the bad data. The state values are estimated by weighted least square method in which measurement vector included bus injection current and line current. The bad data are detected using standardized variable of normal distribution and identified using sensitivity coefficients. When the bad data were occured by the bad measurement values. The results of the application to the model power system reveal the effectiveness of the presented algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1930-1933
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• 1991

In this paper, the robustness of self turning controller on the continuous time-delay system is investigated. The polynomial identification method using continuous time exponentially weighted least square algorithm is used for estimating the time.-delay system parameters. The pole-zero and pole placement method are adopted for the control algorithm. On considering the control weighting factor and reliability filter the effect of unmodeled dynamics of the plant are examined by the simulation.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.31-38
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• 2002

In the case of multiple survival times which might be censored at each covariate vector, we study the regression quantile estimations in this paper. The estimations are based on the empirical distribution functions of the censored times and the sample quantiles of the observed survival times at each covariate vector and the weighted least square method is applied for the estimation of the regression quantile. The estimators are shown to be asymptotically normally distributed under some regularity conditions.

• Journal of applied mathematics & informatics
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• v.33 no.1_2
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• pp.193-201
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• 2015

In this paper, we present preconditioned generalized accelerated overrelaxation (GAOR) methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we give a numerical example to confirm our theoretical results.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.496-499
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• 1990

In this paper, the robustness of implict self tunning controller on the continuous time system is investigated. Continuous time exponentially weighted least square algorithm is used for estimating the system parameters. The pole-zero placement method is adapted for the control algorithm. On considering the control weighting factor and realizability filter the effects of unmodeled dynamics of the plant are examined by the simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.9
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• pp.364-371
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• 1984

This paper describes a method for the state estimation in electric power system. The state values are estimated through the weighted least square method considering the bad data. Then, the bad data are identified by using sensitivity coefficients of power system after being detected the bad data through the distribution of T. This method was applied to the model power system, and, the results of test for proposed method are given.

• Proceedings of the Optical Society of Korea Conference
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• 2000.08a
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• pp.128-129
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• 2000

3차원 형상측정에서 많이 쓰이고 있는 모아레 간섭계에는 그 setup에 따라 Projection Type과 Shadow Type이 있다. 이러한 모아레 간섭계는 광원과 측정 카메라의 각도에 의해 물체의 형상을 측정하게 된다. 그러나, 이러한 광원과 측정 카메라의 각도에 의해 생겨나는 그림자에 의한 영향 때문에 물체의 형상이 굴곡이 심한 곳은 측정하기 어렵다. 본 논문에서는 아래 그림과 같이 두 개 이상의 광원을 사용하여 그 영향을 줄이기 위한 방법을 제안하였다. 이 방법은 projection type이나 shadow type에서 동일하게 적용 가능할 것으로 예상된다. (중략)

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.1 no.1
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• pp.1-34
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• 1997

In this study, various available meshless methods are briefly reviewed and the connection among them is investigated. The objective of meshless methods is to eliminate some difficulties which are originated from reliance on a mesh by constructing the approximation entirely in terms of nodes. Especially, focusing on Element Free Galerkin Method(EFGM) based on moving least square interpolants(MLSI), a new implementation is developed based on a variational principle with penalty function method were used to enforce the essential boundary condition. In addition, the weighted orthogonal basis functions are constructed to overcome disadvantage of MLSI.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.