• 대한의용생체공학회:의공학회지
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• 제15권4호
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• pp.481-488
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• 1994

시각 및 손가락의 전기자극에 의해 머리표면에서 발생하는 유발전위를 검출하여 Source Tracing Method를 이용하여 뇌의 시각인지영역 및 손가락 감각인지영역을 추정하였다. 본 과정에서 유발전위 검출방식은 average method를 이용하였고, 흥분뉴런군에 대한 물리적 모델로 Single Current Dipole Model을 이용하고, 머리기하에 대한 3중구각모델을 이용하여 Forward Problem을 풀었다. Inverse Problem은 current dipole의 6개의 parameter에 대한 Least Square Error Method를 이용하여 신견흥분의 위치를 추정하였다. 이러한 결과와 생리학적으로 밝혀진 시각 및 체성감각 신경로와의 비교결과 유사성이 확인되었다.

• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.633-642
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• 2008

본 논문에서는 반응변수가 하나 이상이고 설명변수들의 수가 관측치에 비하여 상대적으로 많은 경우에 널리 사용되는 부분최소제곱회귀모형에 벌점함수를 적용하여 모형에 필요한 설명변수들을 선택하는 문제를 고려하였다. 모형에 필요한 설명변수들은 각각의 잠재변수들에 대한 최적해 문제에 벌점함수를 추가한 후 모의담금질을 이용하여 선택하였다. 실제 자료에 대한 적용 결과 모형의 설명력 및 예측력을 크게 떨어뜨리지 않으면서 필요없는 변수들을 효과적으로 제거하는 것으로 나타나 부분최소제곱회귀모형에서 최적인 설명변수들의 부분집합을 선택하는데 적용될 수 있을 것이다.

• Journal of the Korean Statistical Society
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• 제9권1호
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• pp.61-77
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• 1980

In response surface experiments, a polynomial model is often used to fit the response surface by the method of least squares. However, if the vectors of predictor variables are multicollinear, least squares estimates of the regression parameters have a high probability of being unsatisfactory. Hoerland Kennard have demonstrated that these undesirable effects of multicollinearity can be reduced by using "ridge" estimates in place of the least squares estimates. Ridge regrssion theory in literature has been mainly concerned with selection of k for the first order polynomial regression model and the precision of $\hat{\beta}(k)$, the ridge estimator of regression parameters. The problem considered in this paper is that of selecting k of ridge regression for a given polynomial regression model with an arbitrary order. A criterion is proposed for selection of k in the context of integrated mean square error of fitted responses, and illustrated with an example. Also, a type of admissibility condition is established and proved for the propose criterion.criterion.

• 한국전산유체공학회지
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• 제14권4호
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• pp.93-100
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• 2009

The gridless (or meshfree) methods, such as MPS, SPH, FPM an so forth, are feasible and robust for the problems with moving boundary and/or complicated boundary shapes, because these methods do not need to generate a grid system. In this study, a gridless solver, which is based on the combination of moving least square interpolations on a cloud of points with point collocation for evaluating the derivatives of governing equations, is presented for two-dimensional unsteady incompressible Navier-Stokes problem in the low Reynolds number. A MAC-type algorithm was adopted and the Poission equation for the pressure was solved successively in the moving least square sense. Some typical problems were solved by the presented solver for the validation and the results obtained were compared with analytic solutions and the numerical results by conventional CFD methods, such as a FVM.

• 한국정보통신학회논문지
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• 제13권7호
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• pp.1321-1327
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• 2009

본 논문에서는 최근 방송 및 이동 통신 서비스가 광벙위하게 사용되고 서비스 영역의 용이한 확대로 인해 무선중계기에 대한 수요가 급격히 증가하고 있다. 그러나 무선중계기에서 발생되는 궤환 신호로 인한 발진현상이 발생 한다. 그룹화 LMS(Least Mean Square)와 CMA(Constant Modulus Algorithm) 알고리즘을 이용한 적응 필터를 적용시킨 새로운 혼합 간섭 제거기활 제안한다. 제안한 간섭 제거기는 그룹화 LMS 알고리즘 간섭 제거기법을 적용시키기 때문에 기존 구조보다 나은 채널 적응 성능과 낮은 MSE(Mean Square Error)을 가진다. 이 제안된 검출기는 수렴속도를 증가하면서 동시에 평균 자승 에러를 줄이기 위해 최소평균 자승 알고리즘에서 두 개의 적응화 상수를 이용한다. 이 구조는 기존 비선형 간섭제거기에 비해 같은 MSE(Mean Square Error)에 대한 반복수와 하드웨어 복잡도를 줄여준다.

• Journal of applied mathematics & informatics
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• 제41권3호
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• pp.647-656
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• 2023

In this work, we are concerned by the problem of identification of noisy terms which arise in singular problem as for remote sensing problems, and which are modeled by a linear singular parabolic equation. For the reason of missing some data that could be arisen when using the traditional sentinel method, the later will be changed by a new sentinel method for attaining the same purpose. Such new method is a particular least square-like method which permits one to distinguish between the missing terms and the pollution terms. In particular, a sentinel method will be given here in its more realistic setting for singular parabolic problems, where in this case, the observation and the control have their support in different open sets. The problem of finding a new sentinel is equivalent to finding singular optimality system of the least square control for the parabolic equation that we solve.

• 한국멀티미디어학회논문지
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• 제16권12호
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• pp.1465-1474
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• 2013

In this paper, air pollutant tracing models using perceptron neural network(PNN) and non-negative least square(NNLS) are proposed. When the measured values of the air pollution and the contribution concentration of each source by chemical transport modeling are given, they estimate and trace the amount of the air pollutants emission from each source. Two kinds of emissions data are used in the experiments : CH4 and N2O of Geumgo-dong landfill greenhouse gas, and PM10 of 17 areas in Northeast Asia and eight regions of the Korean Peninsula. Emission values were calculated using pseudo inverse method, PNN and NNLS. Pseudo inverse method could be used for the model, but it may have negative emission values. In order to deal with the problem, we used the PNN and NNLS methods. As a result, the estimation using the NNLS is closer to the measured values than that using PNN. The proposed tracing models have better utilization and generalization than those of conventional pseudo inverse model. It could be used more efficiently for air quality management and air pollution reduction.

• 한국정보처리학회논문지
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• 제4권12호
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• pp.3200-3210
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• 1997

훼손된 타원 및 복잡한 형태의 영상에서 타원 검출에 최소자승법(LSM : Least Square Method)을 적용할 수 있는데 이는 데이터가 비정규 오류 분포를 따르거나 특이한점들이 있는 상태에서는 신뢰할 수 있는 결과를 얻을 수 없다. 특히 최소자승법은 훼손된 부분을 데이터가 없는 것으로 가정 하고 모든 데이터를 동일한 비중으로 연산하므로 훼손된 부분은 더욱 훼손된 모양으로 검출되는 문제점 있다. 본 논문에서 변형된 최소자승 법(MLSM: Modified Least Square Method)이란 훼손부분의 가까운점에 큰 비중을 둠으로 원래의 모양에 접근하는 형상(feature)의 타원을 검출하려는 것으로 훼손점 부근의 2점과 그외 중요한 l점을 강제로 만족하는 방법이다. 3점을 만족시키는 제한 조건을 주고 2개의 파라미터는 최소자승법으로 구하고, 나머지 3개는 제한 조건으로 구하여 타원 검출에 적용한 결과 실제 영상에서 타원의 검출 및 판별에 좋은 효과가 있었으며, 특히 인간의 치열의 곡선 모양을 결정하는테 좋은 효과가 있음을 보였다.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.467-473
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• 2007

In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming the coordinate systems. In order to identify the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. From the simulation results, it is shown that the considered parameter identification problem is characterized by a highly multimodal landscape; thus, a global optimization technique such as a particle swarm optimization could be a promising tool to identify the model parameters of a robot hand tracking system, whereas the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum.

• Journal of the Korean Statistical Society
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• 제33권3호
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• pp.313-321
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• 2004

We consider the problem of testing cell probabilities in sparse multinomial data. Aerts et al. (2000) presented T=${{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2$ as a test statistic with the local least square polynomial estimator ${{p}_{i}}^{*}$, and derived its asymptotic distribution. The local least square estimator may produce negative estimates for cell probabilities. The local maximum likelihood polynomial estimator ${{\hat{p}}_{i}}$, however, guarantees positive estimates for cell probabilities and has the same asymptotic performance as the local least square estimator (Baek and Park, 2003). When there are cell probabilities with relatively much different sizes, the same contribution of the difference between the estimator and the hypothetical probability at each cell in their test statistic would not be proper to measure the total goodness-of-fit. We consider a Pearson type of goodness-of-fit test statistic, $T_1={{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2/p_{i}$ instead, and show it follows an asymptotic normal distribution. Also we investigate the asymptotic normality of $T_2={{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2/p_{i}$ where the minimum expected cell frequency is very small.