• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.295-298
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• 1996

In distillation column control, secondary measurements such as temperatures and flows are widely used in order to infer product composition. This paper addresses the design of static estimators using the secondary measurements for estimating the product compositions of the multicomponent distillation columns. Based on the unified framework for the estimator problems, the relationships among several typical static estimators are discussed including the effect of the measured inputs. Design guidelines for the composition estimator using PLS regression are also presented. The estimator based on the guidelines is robust to sensor noise and has a good predictive power.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.579-582
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• 2001

The performance of a coherent rake receiver of DS-CDMA systems is significantly affected by the accuracy of channel estimation. The performance of the channel estimator can be improved by employing a channel estimation filter (CEF) whose impulse response is adjusted according to the channel condition. In this paper, we consider the design of an adaptive channel estimator for DS-CDMA systems with a pilot channel. The proposed channel estimator estimates the channel condition, which can be performed without haying exact a priori information on the operating condition. The estimated channel condition adjusts the impulse response of the CEF. Numerical results show that the use of the proposed channel estimator can provide BER performance quite robust to a wide range of channel condition.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.782-787
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• 2004

In the conventional sliding mode control technique, a priori knowledge of the bound of external disturbances or/and parameter uncertainties is required to assure control robustness. This, however, may not be easy to obtain in practical situation. This work presents a novel methodology, a sliding mode controller with perturbation estimator, which offers a robust control performance without a priori knowledge about the perturbations (disturbances and parameter uncertainties). The proposed technique is featured by an integrated average value of the imposed perturbation over a certain sampling period. This work also proposes two effective actuating methods of the perturbation estimator: on-off condition and filtering condition. In order to demonstrate the effectiveness of the proposed methodology, a two-link robotic system is adopted and its position control performance is evaluated. In addition, a comparative work between the conventional technique and the proposed one is undertaken.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1E
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• pp.3-6
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• 1999

In digital mobile communication system, the transmission errors affect the quality of output speech seriously. There are many error concealment techniques using a posteriori probability which provides information about any transmitted parameter. They need knowledge about channel transition probability as well as the 1st order Markov transition probability of codec parameters for estimation of transmitted parameters. However, in applications of mobile communication systems, the channel transition probability varies depending on nonstationary channel characteristics. The mismatch of designed channel transition probability of the estimator to actual channel transition probability degrades the performance of the estimator. In this paper, we proposed a new parameter estimator which adapts to the channel characteristics using short time average of maximum a posteriori probabilities(MAPs). The proposed scheme, when applied to the LSP parameter estimation, performed better than the conventional estimator which do not adapt to the channel characteristics.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.277-287
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• 1995

It is well kmown that the $L_1$-estimator is robust with respect to vertical outliers in regression data, even if it is susceptible to bad leverage points. This article is concerned with the robustness of the $L_1$-estimator. To investigate its robustness against vertical outliers we may find intervals for the value of the response variable within which the $L_1$-estimates do not shange. A procedure for constructing those intervals in multiple limear regression is illustrated in the sensitivity analysis context. And then vertical breakdown point of the $L_1$-estimator is defined on the basis of properties related to those intervals.

• Journal of Korean Academy of Nursing
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• v.29 no.5
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• pp.1030-1041
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• 1999

This study examined those problems noticed under the Asymptotically Generalized Least Squares estimator in evaluating a structural model of physical health. The problems were highly correlated parameter estimates and high standard errors of some parameter estimates. Separate analyses of the endogenous part of the model and of the metric of a latent factor revealed a highly skewed and kurtotic measurement indicator as the focal point of the manifested problems. Since the sample sizes are far below that needed to produce adequate AGLS estimates in the given modeling conditions, the adequacy of the Maximum Likelihood estimator is further examined with the robust statistics and the bootstrap method. These methods demonstrated that the ML methods were unbiased and statistical decisions based upon the ML standard errors remained almost the same. Suggestions are made for future studies adopting structural equation modeling technique in terms of selecting of a reference indicator and adopting those statistics corrected for nonormality.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.11-16
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• 1996

This paper proposes a deadzone estimator for robust system identification. In order to cope with the drift phenomena occurred in where system inputs are not sufficiently excited in adaptive control, we introduce a novel and flexible bound condition against a fixed constant. It is derived from a forgetting factor and a rational value of the traces of the covariance matrices between step k and k-1. The key feature of this is that it does not require a priori for the bound. Also, the calculation of it is more simple than the one of literatures. The simulation results are examined for showing the practical performance of this algorithm.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.475-488
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• 2004

Several robust regression estimators are compared under contamination. Symmetric and asymmetric contamination schemes are used to measure the variance and MSE of regression estimators. Under asymmetric contamination depth-based regression estimator, especially projection based regression estimator(rcent) outperforms the rest and under symmetric contamination HBR performs relatively well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3055-3070
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• 2013

This paper proposes an improved carrier frequency offset (CFO) and sampling frequency offset (SFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) based broadcasting system with cyclic delay diversity (CDD) antenna. By exploiting a periodic nature of channel transfer function, cyclic delay and pilot pattern with a maximum channel power are carefully chosen, which helps to enable a robust estimation of CFO and SFO against the frequency selectivity of the channel. As a performance measure, a closed-form expression for the achievable mean square error of the proposed scheme is derived and is verified through simulations using the parameters of the digital radio mondiale standard. The comparison results show that the proposed frequency estimator is shown to benefit from properly selected delay parameter and pilot pattern, with a performance better than the existing estimator.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.181-183
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• 2001

This paper presents a robust power system state estimator using linear programming(LP). LP state estimators minimize the weighted sum of the absolute values of the measurement residuals. In this paper, WLS(weighted least square) and WLAV(weighted least absolute value) state estimators are run with same measurement sets including bad data in order to compare the robustness to bad data and convergence characteristics of the two methods. Simulations with three test cases are performed and the results are presented, using IEEE 14 bus system.