• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1084-1087
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• 2002

This paper presents an improved fuzzy logic-based adaptive PWM technique. A fuzzy logic- based adaptive PWM technique determines the optimal output voltage vector which takes into account both direction of back-emf and direction of current error vector. This technique has a simple structure and a good level of stability, but it has disadvantages. The longer sampling period, the larger current error. Because there is no considerations of the current error magnitude of each phases. The proposed method improves the control performance by selecting the optimum switching pattern in which the magnitudes of current errors are considered introducing space vector concept. Simulation results using Matlab/Simulink show that the proposed control method reduces current error keeping the merit of previous one.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.139.4-139
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• 2001

The thesis propose the sensorless vector control method that estimates the rotor speed using stator current. The estimated speed is used as feedback in a vector control system. The conventional MRAS structure has a problem the error output is decreasing as estimated speed error is increasing and the estimation performance is not robust when mutual inductance has been changed. In the proposed method, error output is proportional to estimated speed error. The described technique is less complex, robust to variations of mutual inductance. This new method can achieve much wider bandwidth speed control than that of the conventional MRAS structure.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.192-195
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• 2002

The thesis proposes the sensorless vector control method that estimates the rotor speed and rotor time constant at the same time using stator current. In the proposed method, stator current error in the stationary reference frame is proportional to estimated speed error, and stator current error in the synchronous reference frame is proportional to estimated rotor time constant error. The proposed method can simultaneously produce a fast speed estimation and rotor time constant estimation. Therefore, this new method offers an improvement in the performance of a sensorless vector controller. And, the superiority of the proposed method is verified by simulation.

• ETRI Journal
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• v.28 no.5
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• pp.574-582
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• 2006

In this paper, a new error concealment algorithm is proposed for the H.264 standard. The algorithm consists of two processes. The first process uses a fuzzy logic method to select the size type of lost blocks. The motion vector of a lost block is calculated from the current frame, if the motion vectors of the neighboring blocks surrounding the lost block are discontinuous. Otherwise, the size type of the lost block can be determined from the preceding frame. The second process is an error concealment algorithm via a proposed adapted multiple-reference-frames selection for finding the lost motion vector. The adapted multiple-reference-frames selection is based on the motion estimation analysis of H.264 coding so that the number of searched frames can be reduced. Therefore the most accurate mode of the lost block can be determined with much less computation time in the selection of the lost motion vector. Experimental results show that the proposed algorithm achieves from 0.5 to 4.52 dB improvement when compared to the method in VM 9.0.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.71-83
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• 2016

In this paper we discuss a deconvolution density estimator obtained using the support vector machines (SVM) and Tikhonov's regularization method solving ill-posed problems in reproducing kernel Hilbert space (RKHS). A remarkable property of SVM is that the SVM leads to sparse solutions, but the support vector deconvolution density estimator does not preserve sparsity as well as we expected. Thus, in section 3, we propose another support vector deconvolution estimator (method II) which leads to a very sparse solution. The performance of the deconvolution density estimators based on the support vector method is compared with the classical kernel deconvolution density estimator for important cases of Gaussian and Laplacian measurement error by means of a simulation study. In the case of Gaussian error, the proposed support vector deconvolution estimator shows the same performance as the classical kernel deconvolution density estimator.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.42-49
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• 1996

In this paper, we propose a satellite multispectral image data compression method using classified vector quantization. This method classifies each pixel vector considering band characteristics of multispectral images. For each class, we perform both intraband and interband vector quantization to romove spatial and spectral redundancy, respectively. And residual vector quantization for error images is performed to reduce error of interband vector quantization. Thus, this method improves compression efficiency because of removing both intraband(spatial) and interband (spectral) redundancy in multispectral images, effectively. Experiments on landsat TM multispectral image show that compression efficiency of proposed method is better than that of conventional method.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.1-12
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• 1995

An estimator of coefficients of polynomial measurement error model with vector predictor and first-order interaction terms is derived using Hermite polynomial. Asymptotic normality of estimator is provided and some simulation study is performed to compare the small sample properties of derived estimator with those of OLS estimator.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.98-107
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• 1996

The use of composite hyperpatch model is proposed to predict a machine tool positional error over the entire work space. This is an appropriate representation of the distorted work space. This model is valid for any configuration of 3-axis machine tool. Tool position, which is given NC data or CL data, contains error vector in actual work space. In this study, off-line compensation scheme was investigated for tool position error due to inaccuracy in machine tool structure. The error vector in actual work space is corrected by the error model using Newton-Raphson method. The proposed error compensation method shows the possibility of improving machine accuracy at a low cost.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1573-1583
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• 2016

It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.29-34
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• 1996

In data transmission system, some data are more sensitive to channel errors. Unequal error protection method increases transmission reliability by protecting channel error sensitive data more than other data. However, this method cannot be directly applied to vector quantized signals which are designed by LBG algorithm that assumes no channel distortion in the design, process. Therefore, in this paper, to apply unequal error protection to vector quantized signals, we propose a method which systematically assigns binary indexes to code vectors. We applied the proposed method to the transmission of vector quantized first-order Gauss-Marcov signals assuming that the percentage of the important data is 50%