• The Journal of the Acoustical Society of Korea
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• 제25권2E호
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• pp.43-48
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• 2006

Abstract-Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. Simulations demonstrate that DLS outperforms ordinary least square for certain types of deconvolution problems.

• 전기전자학회논문지
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• 제15권4호
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• pp.293-298
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• 2011

본 논문에서 광대역 코드분할 다중접속 무선 중계기에서 간섭제거를 위한 새로운 CMF(Constant Modulus Fourth) 알고리즘을 제안한다. CMF 알고리즘은 고정 계수 알고리즘인 CMA(Constant Modulus Algorithm)를 수정한 것으로서, 스텝 사이즈를 적절하게 조절함에 따라 개선된 성능을 보이게 된다. 제안된 CMF 알고리즘에서 스텝사이즈가 0.35인 경우 수렴상태에서 평균 자승 에러는 기존 CMA 알고리즘보다 약 4 dB정도 더 낮다. 그리고, 평균 자승 에러 -25dB를 기준으로하면 LMS(Least Mean Square)와 NLMS(Normalized Least Mean Square)보다 반복회수가 400~1100번 정도 줄어든다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권7_8호
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• pp.744-751
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• 2003

본 논문에서는 최근 뛰어난 예측력으로 각광받는 최소제곱 Support Vector Machine(Least Square Support Vector Machine: LS-SVM)과 First Principle(FP)을 결합한 하이브리드 최소제곱ㆍSupport Vector Machine 모델, HLS-SVM(Hybrid Least Square-Super Vector Machine)을 제안한다. 제안한 모델인 하이브리드 최소제곱 Support Vector Machine을 기존의 방법인 하이브리드 신경망(Hybrid Neural Network:HNN), 비선형 칼만필터와 하이브리드 신경망을 결합한 HNN-EKF (Hybrid Neural Network with Extended Kalman Filter) 모델과 비교해 보았다. HLS-SVM 모델은 학습 및 validation 과정에서는 HNN-EKF와 근사한 성능을 보였고, HNN 보다는 우수한 결과를 보였고, 일반화 성능에서는 HNN-EKF에 비해 3배, HNN보다 100배정도 우수한 결과를 보였다.

• 소음진동
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• 제6권5호
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• pp.679-684
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• 1996

The Instrumental Variable Method(IVM), modified from least square algorithm, is applied to parameter identification of a noise contaminated bearing test rig. The signal to noise ratio included in Frequency Response Function(FRF) can cause significant errors in parameter identification. Therefore, among several candidates of parameter identification method, results of the applied IVM were compared with noise-contaminated least square method. This study shows that the noise-contaminated least square method can have indonsistent accuracy depending on the degree of noise level, while the IVM has robuster performance to signal to noise ratio than least square method.

• Journal of Power Electronics
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• 제17권1호
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• pp.149-160
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• 2017

To improve the performance of sensorless induction motor (IM) drives, an adaptive speed estimation method based on a strong tracking extended Kalman filter with a least-square algorithm (LS-STEKF) for induction motors is proposed in this paper. With this method, a fading factor is introduced into the covariance matrix of the predicted state, which forces the innovation sequence orthogonal to each other and tunes the gain matrix online. In addition, the estimation error is adjusted adaptively and the mutational state is tracked fast. Simultaneously, the fading factor can be continuously self-tuned with the least-square algorithm according to the innovation sequence. The application of the least-square algorithm guarantees that the information in the innovation sequence is extracted as much as possible and as quickly as possible. Therefore, the proposed method improves the model adaptability in terms of actual systems and environmental variations, and reduces the speed estimation error. The correctness and the effectiveness of the proposed method are verified by experimental results.

• International Journal of Automotive Technology
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• 제8권1호
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• pp.93-102
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• 2007

The frontal crash optimization of an engine room member using the response surface method was studied. The engine room member is composed of the front side member and the sub-frame. The thicknesses of the panels on the front side member and the sub-frame were selected as the design variables. The purpose of the optimization was to reduce the weight of the structure, under the constraint that the objective quantity of crash energy is absorbed. The response surface method was used to approximate the crash behavior in mathematical form for optimization procedure. To research the effect of the regression method, two different methodologies were used in constructing the response surface model, the least square method and the moving least square method. The optimum with the two methods was verified by the simulation result. The precision of the surrogate model affected the optimal design. The moving least square method showed better approximation than the least square method. In addition to the deterministic optimization, the reliability-based design optimization using the response surface method was executed to examine the effect of uncertainties in design variables. The requirement for reliability made the optimal structure be heavier than the result of the deterministic optimization. Compared with the deterministic optimum, the optimal design using the reliability-based design optimization showed higher crash energy absorption and little probability of failure in achieving the objective.

• 수산해양기술연구
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• 제46권3호
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• pp.223-231
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• 2010

This paper showed the difference between the selectivity of gill net by least square method with polynomials in Kitahara's and that by maximum likelihood analysis for Japanese sandfish and Korean flounder. Catch experiments for Japanese sandfish using commercial vessels off the eastern coast of Korea were conducted with six different mesh sizes between October and December 2007 and those for Korean flounder with five different mesh sizes between 2008 and 2009. The mesh size of 50% probability of catch corresponding to biological maturity length of fish was not different between that by least square method and that by maximum likelihood analysis for Japanese sandfish, however, a little different for Korean flounder, that is, those mesh sizes of 50% probability of catch for biological maturity length of Korean flounder were 10.6cm and 10.1cm by least square method and maximum likelihood analysis, respectively.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.410-413
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• 2009

웨이퍼 Pre-Alignment는 반도체 공정에서 장비에 웨이퍼를 놓기 전에 웨이퍼의 중심 및 방향을 정확하게 정렬할 필요가 있는데, 이를 위해서 일정한 수준 이하로 중심과 방향을 찾아 Alignment 하는 방법을 말한다. 본 논문에서는 웨이퍼를 Alignment 하기 위해 기존의 Mechanical한 방법이 아닌 Area 카메라를 통한 비접촉식 방법을 이용하였다. 이 방법은 웨이퍼를 45도씩 8번씩, 한 바퀴를 회전하여 이미지를 획득한 뒤, 이미지의 웨이퍼의 에지값 들을 이용하여 Least Square Circle Fitting을 이용하여 웨이퍼의 중심과 방향을 정확하게 측정하여 Alignment를 한다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1999년도 학술발표대회 논문집 제18권 2호
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• pp.165-168
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• 1999

This paper concerns a least square approach to optimizing a thinned antenna array with respect to antenna spacing to improve the sidelobe performance. A least square method based on a modified version of the modified perturbation method is proposed to efficiently synthesize an optimum pattern in a thinned array. It is demonstrated that the array performance improves with the proposed method, compared with the conventional method.

• Journal of the Korean Data and Information Science Society
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• 제18권1호
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• pp.97-105
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• 2007

We consider a nonparametric additive risk model that is based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huller and Mckeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.