• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.3
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• pp.274-284
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• 2003

Multi-level converter that is high-capacity electric power conversion system is used widely to electric motor drive system and FATCs(Flexible AC Transmission Systems). H-Bridge converter has been prevalently applied to shunt-type system because it can be easily expanded to the multi-level. In steady states, converter is normally operated in the range of 0.7∼0.8 of modulation Index. Even though zero vectors are not imposed to high modulation index, DC-Link voltage Is constant. It means that converter has another boost vector except for zero vectors among several vectors in 3-level converter. This paper has examined the principle of boost vector and investigated the difference between another boost vector and zero vectors in 3-level converter. In addition, this paper has analysed and compared the charging currents and the capacitor voltages of two topologies. The currents and voltages are related to reference voltage. Therefore, it proposed the calculation method for the voltage ripple and the charging current of each capacitor and compared various DC-Link voltage control methods through the simulation.

• East Asian mathematical journal
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• v.15 no.1
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• pp.81-90
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• 1999

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.5
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• pp.1-14
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• 1997

We consider transmission beamforming techniques for frequency-division-duplex (FDD) wireless communication systems using adaptive arrays to improve the signal quality of the array transmission link. We develop a simple effective transmission beamforming technique based on an approximated frequency tranlsation (AFT) to derive the tranmsiion beamforming weights from the uplink channel vector. This technique exploits the invariance of the short-time averaged fast fading statistics to small frequency translations. A simple approximate relationship that relates the transmission channel vector to the reception channel vector is derived. We have developed its practical alternative in which the frequency translation of the channel vector is performed at the principal angle of arrival (AOA) of the u;link synthestic angular spectrum instead of the mean AOA. To analyze the performance of the proposed methods, we consider the power loss incurred by applying the estimated channel vector instead of the true downlink channel vector. The performance is analyzed as a function of the mean AOA, the angular spread, the number of elements, frequncy difference between the uplink and the downlink, and the angle distribution. Their performance is also compared with that of the direct weight reuse method and the AOA based methods.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.65-68
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• 2001

In the vector control methods of induction motor, the stator current is divided into the flux and torque component current. By controlling these components respectively, the methods control independently flux and torque as in the DC motor and improve the control effects. To apply the vector control methods, the position of the rotor current is identified. The indirect vector control use the parameters of the machine to identify the position of rotor flux. But due to the temperature rise during machine operation, the variation of rotor resistance degrades the vector control. To solve the problem, the q-axis is aligned to reference frame without phase difference by comparing the real flux component with the reference flux component. Then to compensate the slip, PI controller is used. The proposed method keeps a constant slip by compensating the gain of direct slip frequency when the rotor resistance of induction motor varies. To prove the validations of the proposed algorithm in the paper, computer simulations is executed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.107-115
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• 2020

Support vector regression (SVR) is devised to solve the regression problem by utilizing the excellent predictive power of Support Vector Machine. In particular, the ⲉ-insensitive loss function, which is a loss function often used in SVR, is a function thatdoes not generate penalties if the difference between the actual value and the estimated regression curve is within ⲉ. In most studies, the ⲉ-insensitive loss function is used symmetrically, and it is of interest to determine the value of ⲉ. In SVQR (Support Vector Quantile Regression), the asymmetry of the width of ⲉ and the slope of the penalty was controlled using the parameter p. However, the slope of the penalty is fixed according to the p value that determines the asymmetry of ⲉ. In this study, a new ε-insensitive loss function with p1 and p2 parameters was proposed. A new asymmetric SVR called GSVQR (Generalized Support Vector Quantile Regression) based on the new ε-insensitive loss function can control the asymmetry of the width of ⲉ and the slope of the penalty using the parameters p1 and p2, respectively. Moreover, the figures show that the asymmetry of the width of ⲉ and the slope of the penalty is controlled. Finally, through an experiment on a function, the accuracy of the existing symmetric Soft Margin, asymmetric SVQR, and asymmetric GSVQR was examined, and the characteristics of each were shown through figures.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.17-28
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• 2009

This study attempts to perform the statistical test for the causality between the Korean and the U.S. business conditions in association with the lead-lag relationship between the domestic stock price and the business condition. Their causal relationships are clearly identified after the outbreak of the IMF financial crisis. The vector autoregression for the corresponding period appears to reflect the strong interrelationships between the market variables and the dependency of the domestic business conditions on the U.S. market. The estimation results validate the leading effect of the stock price and the U.S. business behavior.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.103-105
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• 1993

This paper proposed a new direct vector control scheme using high frequency current injection. This scheme has some attractive features such as using no flux sensor or speed sensor, robustness of parameter variation, capability of accurate vector control at very low speed. Compared to other direct vector control scheme, this scheme doesn't depends on phase delay and difference of magnitude of estimated flux, rotor resistance and all inductances except stator resistance. These features are proved by computer simulation and experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1001-1008
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• 2003

A time-delay compensation method for vector control system is proposed that can compensate for voltage and current distortions resulting from a time delay in the overall system due to the low pass filter, hysteresis control inverter, microprocessor program computation time, and so on. The proposed scheme estimates the time delay using the difference between the Q-axis stator current command and the time-delayed actual Q-axis stator current in a synchronous reference frame, then compensates the time delay in the voltage and current using the angular displacement of a DQ transformation. Accordingly, the proposed scheme can accurately compensate for the time delay related to the overall system, thereby significantly improving the performance of the vector control system, as verified by simulation and experiment.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.77-83
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• 1997

We present a fast adaptive block matching algorithm using variable search area and subsampling to estimate motion vector more exactly. In the presented method, the block is classified into one of three motion categories: zero motion vector block, medium-motion bolck or high-motion block according to mean absolute difference of the block. By the simulation, the computation amount of the presented methoe comparable to three step search algorithm and new three step search algorithm. In the fast image sequence, the PSNR of our algorithm increased more than TSS and NTSS, because our algorithm estimated motion vector more accurately.

• East Asian mathematical journal
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• v.37 no.3
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• pp.333-354
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• 2021

A support vector machine (SVM) is a state-of-the-art machine learning model rooted in structural risk minimization. SVM is underestimated with regards to its application to real world problems because of the difficulties associated with its use. We aim at showing that the performance of SVM highly depends on which kernel function to use. To achieve these, after providing a summary of support vector machines and kernel function, we constructed experiments with various benchmark datasets to compare the performance of various kernel functions. For evaluating the performance of SVM, the F1-score and its Standard Deviation with 10-cross validation was used. Furthermore, we used taylor diagrams to reveal the difference between kernels. Finally, we provided Python codes for all our experiments to enable re-implementation of the experiments.