• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.193-200
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• 2011

This paper proposes a low-cost visual analyzer algorithm of human body motion for real-time applications such as human-computer interfacing, virtual reality applications in medicine and telemonitoring of patients. To reduce cost of its use, we design the algorithm to use a single camera. To make the proposed system to be used more conveniently, we avoid from using optical markers. To make the proposed algorithm be convenient for real-time applications, we design it to have a closed-form with high accuracy. To design a closed-form algorithm, we propose an idea that formulates motion of a human body joint as a 2D universal joint model instead of a common 3D spherical joint model, without any kins of approximation. To make the closed-form algorithm has high accuracy, we formulates the estimation process to be an optimization problem. Thus-desined algorithm is applied to each joint of the human body one after another. Through experiments we show that human body motion capturing can be performed in an efficient and robust manner by using our algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1123-1126
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• 1990

A new controller design algorithm based on the Hessenberg form for linear control systems has een proposed. The controller is composed of the dynamic compensator and the state feedback (dynamic state feedback). The algorithm gives a simple way to assign the eigenstructure (eigenvalues and eigenvectors) of the closed loop system and it also provides a method to assign the frequency shapes near the corner frequencies of the closed loop transfer function matrix. Because of this property, the algorithm is called the independent frequency shape control (IFSC) method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.886-893
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• 2017

Recently, for detection of low-RCS targets, bistatic radar and multistatic radar have been widely employed. In this paper, we present the process of deriving the received signal modeling of the bistatic MIMO radar system and deals with the performance analysis of applying the bistatic signal to the ML arrival angle estimation algorithm. In case of the ML algorithm, as the number of the targets increases, azimuth search dimension for DOA estimation also increases, which implies that the ML algorithm for multiple targets is computationally very intensive. To solve this problem a closed-form expression of estimation error is presented for performance analysis of the algorithm.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.35-41
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• 2016

Based on correlation and least square method, a closed-form algorithm for estimating the location of mixed far-field and near-field source is presented using the Uniform Circular Array (UCA). Recently, for a homogeneous circular arrangement case, a correlation based closed-form algorithm is proposed to estimate 2-D angle (azimuth, elevation) and the extended algorithm is proposed to 3-D location (azimuth, elevation, range). These algorithms assume the far-field source or near-field source only. Therefore, for mixed source localization, the proposed algorithm estimates source location with the assumption of far-field source, and then estimates the range to distinguish the far-field from the near-field source. For both cases, numerical experiments have been performed, which confirmed the validity of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1269-1274
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• 2004

This paper presents a new quantisation algorithm which has the closed-loop form and guarantees the boundness of accumulative error. This algorithm is particularly useful for mobile robot navigation that is usually implemented on embedded systems. If wheel commands of the mobile robot are given by velocity or positional increment at every control instant and quantised due to finite word length of controller's CPU, the quantisation error gets accumulated to causes large position error. Such an error accumulative characteristic is fatal for non wheeled mobile robots or autonomous vehicles with non-holonomic constraint. To solve this problem, we propose a non-error accumulative quantisation algorithm with closed-loop form. We also show it can be extend to a generalized form corresponding to the n-th order accumulation. The boundness of the accumulative quantisation error is investigated by a series of computer simulation. The proposed method is particularly effective to precise navigation control the autonomous mobile robots.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.673-683
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• 2012

Cabral et al. (2012) defined a mixture model of multivariate skew t-distributions(STMM), and proposed the use of an ECME algorithm (a variation of a standard EM algorithm) to fit the model. Their estimation by the ECME algorithm is closely related to the estimation of the degree of freedoms in the STMM. With the ECME, their purpose is to escape from the calculation of a conditional expectation that is not provided by a closed form; however, their estimates are quite unstable during the procedure of the ECME algorithm. In this paper, we provide a conditional expectation as a closed form so that it can be easily calculated; in addition, we propose to use the ECM algorithm in order to stably fit the STMM.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.683-687
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• 2007

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and Closed-Form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-Form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a Self-Tuning Weighted Least Square AOA algorithm that is a modified version of the conventional Closed-Form solution. In order to estimate the error covariance matrix as a weight, a two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.485-489
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• 2006

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and closed-form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a self-tuning weighted least square AOA algorithm that is a modified version of the conventional closed-form solution. In order to estimate the error covariance matrix as a weight, two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1093-1098
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• 2000

This paper presents an efficient algorithm for including the kinematic calibration data into the motion controller to improve the positioning accuracy of the manipulators. Rather than spending several iterations for finding the inverse solution of the calibrated kinematics, our approach requires only the nominal inverse solution and the calibrated forward kinematics for providing a better position command promptly. Thus, real-time application is guaranteed whenever the manipulators nominal inverse solution can be expressed in a closed form. Experimental results show that the line tracking performances can be remarkably improved by employing our algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.173-176
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• 1994

In this paper a closed-form predictive control which takes the intervalwise receding horizon strategy is presented and its stability properties are investigated. A slate-space form output predictor is derived which is composed of the one-step ahead optimal output prediction, input and output data of the system. A set of feedback gains are obtained using the dynamic programming algorithm so that they minimize a multi-stage quadratic cost function and they are used periodically.