• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.129-132
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• 2001

This paper presents an efficient method to estimate the maximum SSN (simultaneous switching noise) for ground interconnection networks in CMOS systems using Taylor's series and analyzes the truncation error that has occurred in Taylor's series approximation. We assume that the curve form of noise voltage on ground interconnection networks is linear and derive a polynomial expression to estimate the maximum value of SSN using $\alpha$-power MOS model. The maximum relative error due to the truncation is shown to be under 1.87% through simulations when we approximate the noise expression in the 3rd-order polynomial.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2000-2003
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm for robust face recognition. Given a 3D input image, we automatically extract several important 3D facial feature points based on the facial geometry. To estimate 3D head pose accurately, we propose an Error Compensated-SVD (EC-SVD) algorithm. We estimate the initial 3D head pose of an input image using Singular Value Decomposition (SVD) method, and then perform a Pose refinement procedure in the normalized face space to compensate for the error for each axis. Experimental results show that the proposed method is capable of estimating pose accurately, therefore suitable for 3D face recognition.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1509-1510
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• 2008

In this paper, we propose a robust adaptive controller for induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the high order neural networks(HONN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• IE interfaces
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• v.22 no.3
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• pp.214-222
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• 2009

In the early design stage, system reliability must be estimated from life testing data at the component level. Previously, a point estimate of system reliability was obtained from the unbiased estimate of the component reliability after assuming that the number of failed components for a given time followed a binomial distribution. For deriving the confidence interval of system reliability, either the lognormal distribution or the normal approximation of the binomial distribution was assumed for the estimator of system reliability. In this paper, a new estimator is used for the component level reliability, which is biased but has a smaller mean square error than the previous one. We propose to use the beta distribution rather than the lognormal or approximated normal distribution for developing the confidence interval of the system reliability. A numerical example based on Monte Carlo simulation illustrates advantages of the proposed approach over the previous approach.

• East Asian mathematical journal
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• v.14 no.1
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• pp.63-76
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• 1998

we consider the hp-version to solve non-constant coefficients elliptic equations $-div(a{\nabla}u)=f$ with Dirichlet boundary conditions on a bounded polygonal domain $\Omega$ in $R^2$. In [6], M. Suri obtained an optimal error-estimate for the hp-version: ${\parallel}u-u^h_p{\parallel}_{1,\Omega}{\leq}Cp^{(\sigma-1)}h^{min(p,\sigma-1)}{\parallel}u{\parallel}_{\sigma,\Omega}$. This optimal result follows under the assumption that all integrations are performed exactly. In practice, the integrals are seldom computed exactly. The numerical quadrature rule scheme is needed to compute the integrals in the variational formulation of the discrete problem. In this paper we consider a family $G_p=\{I_m\}$ of numerical quadrature rules satisfying certain properties, which can be used for calculating the integrals. Under the numerical quadrature rules we will give the variational form of our non-constant coefficients elliptic problem and derive an error estimate of ${\parallel}u-\tilde{u}^h_p{\parallel}_{1,\Omega}$.

• Journal of Biomedical Engineering Research
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• v.5 no.2
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• pp.133-142
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• 1984

The EMG signal can be considered as a signal source that expresses the intention of man because it is a electrical signal generated when the man contracts muscles. For proportional control of prostheses, the control signal proportional to the mousle contraction level must be estimated. Typically a foul-wave rectifier and low-pass filter are used to estimate the proportional control signal from the EMG signal. In this paper, it is proposed to use a logarithmic transformation and a linear minimum mean square error estimator. A logarithmic transformation maps the myoelectric signal into an additive control signal-plus-noise domain and the Kalman filter is used to estimate the control signal as a linear minimum mean square error estimator. The performance of this estimator is verified by the computer simulation and the estimator is applied to the EMG obtained from the biceps brachii muscle of normal subjects.

• Proceedings of the Korean Printing Society Conference
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• 1998.10a
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• pp.1-6
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• 1998

The object color does not look same under the different light source. It depends on the surface spectral reflectance and the spectral distribution of light source. Therefore we should find the surface spectral reflectance of object color and the spectral distribution of light source for color reproduction. Using Winer estimation, we can reconstruct the spectral reflectance from low dimensional images obtained with a few filters. The kind and the number of filters have the effect on the estimation of the spectral reflectance. Therefore it is important that optimal filters are selected to minimize the error of the result. In this paper, we describe methods to select optimal filters with minimum error between measured and estimated surface spectral reflectance and to estimate surface spectral reflectance of Munsell color from six band images by using Wiener estimation.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.140-143
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• 2000

In this paper, forward error control coding in multicarrier direct sequence code division multiple access (DS/CDMA) systems is considered. In order to accommodate a number of coding rates easily and make the encoder and do-coder structure simple, we use the rate compatible punctured convolutional (RCPC) code. We obtain data throughputs at several coding rates and choose the coding rate which has the highest data throughput in the SINR sense. To achieve maximum data throughput, a rate adaptive system using channel state information (the SINR estimate) is proposed. The SINR estimate is obtain by the soft decision Viterbi decoding metric. We show that the proposed rate adaptive convolutionally coded multicarrier DS/CDMA system can enhance spectral efficiency and provide frequency diversity.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.127-134
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• 2008

In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.264-270
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• 2003

Application of the Filtered-X LMS adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive canceler. In this paper, we derive an adaptive control algorithm and analyze its convergence behavior when the acoustic noise is assumed to consist of multiple sinusoids. The results of the convergence analysis of the Filtered-X LMS algorithm indicate that the effects of parameter estimation inaccuracy on the convergence behavior of the algorithm are characterize by two distinct components : Phase estimation error and estimated magnitude. In particular, the convergence of the Filtered-X LMS algorithm is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results of the algorithm are presented which support the theoretical convergence analysis.