• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1829-1830
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• 2008

The paper deals with leader-follower formations of nonholonomic mobile robots using least square method in order to maintain the formation constantly. The nonholonomic property of the mobile robot cause us to use the least square method. Then, the performance of the developed formation controller is verified by simulation results.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.643-654
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• 2000

In this paper, we review some class of t-norms on which fuzzy arithmetic operations preserve the shapes of fuzzy numbers and the Hausdorff-distance between fuzzy numbers as the measure of distance between fuzzy numbers. And we suggest the least Hausdorff-distance square method for fuzzy linear regression model using shape preserving fuzzy arithmetic operations.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.49-50
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• 2006

We consider a nonparametric additive risk model that are 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 Huffer 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.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.208-210
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• 1998

A high speed digital distance relaying algorithm based on a modified least square error method is proposed. To obtain stable phasor values very Quickly, first, a lowpass filter which has very short transient period and no overshoot is used. Secondly, the conventional least square error method is modified to the one having the data window of 3 samples by applying a FIR filter which removes the DC-offset component in current relaying signals.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.633-641
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• 2001

The least squares method is usually applied when estimating the parameters in the regression models. However the least square estimator is not very efficient when the distribution of the error is skewed. In this paper, we propose the asymmetric least square estimator for a particular nonlinear time series regression model, and give the simple and practical sufficient conditions for the strong consistency of the estimators.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2E
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• pp.63-68
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• 2007

Using the neural network model for oriented principal component analysis (OPCA), we propose a solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. In this paper, we applied this neural network model to channel equalization. Simulations show that the neural network based DLS outperforms ordinary least squares in channel equalization problems.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.459-465
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• 2011

A phasor estimation algorithm based on the least square curve fitting technique for the distorted secondary current due to current transformer (CT) saturation is proposed. The mathematical form of the secondary current during CT saturation is represented as the scaled primary current with magnetizing current. The information on the scaled primary current is estimated using the least square technique, with the measured secondary current in the saturated section. The proposed method can estimate the phasor of a fundamental frequency component during the saturated period. The performance of the algorithm is validated under various fault and CT conditions using a C400 CT model. A series of performance evaluations shows that the proposed phasor estimation algorithm can estimate the phasor of the fundamental frequency component with high accuracy, regardless of fault conditions and CT characteristics.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.279-281
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• 2006

A Voltage Instability Predictor(VIP) estimates the proximity of a power system to voltage collapse in real time. Voltage Instability Index(Z-index) from VIP algorithm is estimated using LS(Least Square) method. But this method has oscillations and noise of result due to the system's changing conditions. To suppress oscillations, a larger data window needs to be used. In this paper. I propose the new other method which improves that weakness. It uses RLS(Recursive Least Square) to estimate voltage instability index without a large moving data window so this method is suitable for on-line monitor and control in real time. In order to verify effectiveness of the algorithm using RLS method, the method is tested on HydroQuebec system in real time digital simulator(HYPERSIM).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.235-238
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• 2001

Deformation phase can be obtained by using Least-Square Fitting. In extraction of phase values, Least-Square Fitting is superior to usual method like as 2, 3, 4-Bucket Algorithm. That can extract almost noise-free phase and retain 2$\pi$discontinuities. But more fringe in phase map, 2$\pi$ discontinuities is destroyed when that is filtered and reconstruction of deformation is not reliable. So, we adapted Least-Square Fitting using an isotropic window in dense fringe. using Sine-Cosine filter give us perfect 2$\pi$discontinuities information. We showed the process and result of extraction of phase map and filtering in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.20-26
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• 2002

Deformation phase can be obtained by using Least-Square fitting. In extraction of phase values, Least-Square Fitting is superior to usual method such as 2, 3, 4-Bucket Algorithm. That can extract almost noise-free phase and retain 2 $\pi$ discontinuities. But more fringes in phase map, 2 $\pi$ discontinuities are destroyed when that are filtered and reconstruction of deformation is not reliable. So, we adapted Least-Square fitting using an isotropic window in dense fringe. Using Sine/cosine filter give us perfect 2 $\pi$ discontinuities information. We showed the process and result of extraction of phase map and filtering in this paper.