• 한국정밀공학회지
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• 제11권5호
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• pp.88-97
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• 1994

We persent a method for kinematic calibration of open chain mechanisms based on the product of exponentials (POE) formula. The POE formula represents the forward kinematics of an open chain as a product of matrix exponentials, and is based on a modern geometric interpretation of classical screw theory. Unlike the kinematic parameters in the POE formula vary smoothly with changes in the joint axes;ad hoc methods designed to address the inherent singularities in the D-H parameters are therefore are therefore unnecessary. After introducing the POE formula, we derive a least-squares kinematic calibration algorithm for general open chain mechanisms. Simulation results with a 6-axis open chain are presented.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 Proceedings ICPE 98 1998 International Conference on Power Electronics
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• pp.149-152
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• 1998

From the viewpoint of model-based current control, it is indispensable to use the accurate system parameters for the high control performance. This paper adopts the Least-Squares algorithm as a parameter estimation scheme because it has the fast convergence rate and the low sensitivity to noises. In case of the intelligent current controller with delay compensator, the simulation results show that the adopted estimation scheme can be successfully applied to PWM converters and also show the improved control performance in the estimated parameters.

• 대한의용생체공학회:의공학회지
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• 제13권2호
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• pp.107-114
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• 1992

An adaptive filter for noise cancellation of ECG Is proposed. An adaptive noise canceller using the least mean squares algorithm Is used to reduce unwanted noise. An adaptive filter for nolse cancella lion minimizes the mean-square error between a primary input and a reference input. A primary input is the noisy ECG, and a reference input is a noise that Is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1985년도 하계학술회의논문집
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• pp.55-60
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• 1985

A state-space model of a burn through point control system of an industrial sintering process is derived. The model is then used in designing a self-tuning controller which consists of the receding horizon control law and a least-squares prediction algorithm. By applying this adaptive controller to POSCO sintering process IV, satisfactory expermental results have been obtained. Some of these practical results are presented in this paper.

• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.629-636
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• 2007

A kernel type semi-supervised estimate is proposed. The proposed estimate is based on the penalized least squares loss and the principle of Gaussian Random Fields Model. As a result, we can estimate the label of new unlabeled data without re-computation of the algorithm that is different from the existing transductive semi-supervised learning. Also our estimate is viewed as a general form of Gaussian Random Fields Model. We give experimental evidence suggesting that our estimate is able to use unlabeled data effectively and yields good classification.

• Journal of Information Processing Systems
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• 제1권1호
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• pp.32-35
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• 2005

Image denoising is basic work for image processing, analysis and computer vision. This paper proposes a novel algorithm based on wavelet threshold for image denoising, which is combined with the linear CLS (Constrained Least Squares) filtering and thresholding methods in the transform domain. We demonstrated through simulations with images contaminated by white Gaussian noise that our scheme exhibits better performance in both PSNR (Peak Signal-to-Noise Ratio) and visual effect.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2004년도 춘계학술발표대회논문집
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• pp.786-789
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• 2004

With the development of RAIM techniques for single failure. there has been increasing interest in the multiple failure problem. There have been many approaches to tackle the problem from various points of view. This paper approaches to two failure problem with total least squares (TLS) technique, which has rarely been addressed because TLS requires a great number of computations.

• Journal of Positioning, Navigation, and Timing
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• 제10권2호
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• pp.121-130
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• 2021

In this paper, we propose a method to improve the positioning accuracy of TOA based indoor positioning system in NLOS environments. TOA based indoor positioning systems have been studied mostly considering LOS environments. However, it is almost impossible to maintain the LOS environments due to obstacles such as people, furniture, walls, and so on. The proposed method in this study compensates the range error caused by the NLOS environments. We confirmed that positioning accuracy of a proposed method is improved than conventional algorithms through simulation and field test.

• 대한전자공학회논문지
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• 제23권4호
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• pp.445-449
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• 1986

This paper presents a direct adaptive control scheme for nonminimum phase systems of which controller parameters are estimated from the least-squares algorithm, and some additional auxiliadry parameters are obtianed from the proposed polynomial identity equation. Integral action is incorporated into the adaptive controller to eliminate the steady-state error, and to satisfy a condition of the unique solution for the polynomial identity as well.

• 전자공학회논문지B
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• 제30B권4호
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• pp.76-84
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• 1993

In this thesis, general method using autoregressive model in the functional separation of the myoelectric signal of human arm movements are suggested. Covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squares error. With the error signals of autoregressive(AR) model, the result showed that the highest success, rate was abtained in the case of 4th order, and success rate was decreased with increase of order. This technique might be applied to biomedical-and rehabilitation-engi-neering.