• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.4
• /
• pp.395-403
• /
• 2002

The advanced space vector PWM is Implemented for the control system using high arithmetic performance microprocessor such as DSP. It is difficult to realize the complicate SLIM which is applied to SVPWM system, but widely used in vector control system or servo control system for AC motor because of its high performance in current control. In this paper, we use the dynamic characteristic analyzing method that can calculate efficiently the end effect by using equivalent circuit methode in the operating SLIM system modeling and examine the dynamic characteristics of SVPWM with PI controller.

• Korean Journal of Optics and Photonics
• /
• v.5 no.4
• /
• pp.439-444
• /
• 1994

When diffraction by arbitrary two-dimensional surface-relief dielectric gratings is analyzed using the rigorous three-dimensional vector coupled-wave analysis, it is found that the matrix eigenvalue problem pertaining to the analysis can always be simplified to that for a matrix which has the dimension of a quarter of the original, so that computing time and memory requirements for computer may be greatly reduced. However this kind of simplification can not be obtained in the case of volume diffraction gratings. tings.

• 한국전산유체공학회:학술대회논문집
• /
• 1999.05a
• /
• pp.113-123
• /
• 1999

In this study a pure vector potential method (PVPM) for a three dimensional, unsteady, incompressible flow is proposed. A simplified version for a two dimensional problem is described in detail, and a method to prescribe appropriate boundary conditions is also presented. The resulting numerical algorithm is applied to the cavity flow driven by an impulsively started wall and also to the Stokes' first problem. Some important unsteady/steady features are captured for these two flows, and quantitative agreements of flow variables with available reference database are good.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.1
• /
• pp.193-200
• /
• 2021

In this study, an analysis technique using static condensation is proposed for an efficient local nonlinear static analysis. The static condensation method is a model reduction method based on the degrees of freedom, and the analysis model is divided into a target part and a condensed part to be omitted. In this study, the nonlinear and linear parts were designated to the target and the omitted parts, respectively, and both the stiffness matrix and load vector corresponding to the linear part were condensed into the nonlinear part. After model condensation, the reduced model comprising the stiffness matrix and the load vector for the nonlinear part is constructed, and only this reduced model was updated through the Newton-Raphson iteration for an efficient nonlinear analysis. Finally, the efficiency and reliability of the proposed analysis technique were presented by applying it to various numerical examples.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.24 no.5
• /
• pp.541-548
• /
• 2013

This paper presents a vector network analysis system for 2-port scattering parameters of microwave devices using some basic microwave instruments/devices such as signal generators, vector voltmeter, directional couplers and frequency mixers. The analytical model and implementation method for scattering parameter measurements - which can replace the vector network analyzers - are presented. The performance of the implemented system is evaluated through 1- and 2-port scattering parameter measurements, respectively. The vector volt signals which determine the scattering parameters are detected in two distinct methods depending on the frequency band of interests; a direct-detection method with a single signal generator and vector voltmeter for relatively low band and a heterodyne method to frequency down-mix associated with an additional signal source as well as frequency mixers for high band are used, respectively. Using these two methods, scattering parameters of UHF and X bands are evaluated and their performances are verified through a comercial vector network analyzer.

• The Korean Journal of Applied Statistics
• /
• v.28 no.5
• /
• pp.871-883
• /
• 2015

Vector autoregressive (VAR) models in high dimension suffer from noisy estimates, unstable predictions and hard interpretation. Consequently, the sparse vector autoregressive (sVAR) model, which forces many small coefficients in VAR to exactly zero, has been suggested and proven effective for the modeling of high dimensional time series data. This paper studies coupling measures to select non-zero coefficients in sVAR. The basic idea based on the simulation study reveals that removing the effect of other variables greatly improves the performance of coupling measures. sVAR model coefficients are asymmetric; therefore, asymmetric coupling measures such as Granger causality improve computational costs. We propose two asymmetric coupling measures, filtered-cross-correlation and filtered-Granger-causality, based on the filtered residuals series. Our proposed coupling measures are proven adequate for heavy-tailed and high order sVAR models in the simulation study.

• Proceedings of the Korean Magnestics Society Conference
• /
• 1993.11a
• /
• pp.24-25
• /
• 1993

• Proceedings of the KIEE Conference
• /
• 1984.07a
• /
• pp.13-15
• /
• 1984

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.8
• /
• pp.868-876
• /
• 2016

MUSIC (multiple signal classification) algorithm is a representative algorithm estimating the angle of arrival using the eigenvalues and eigenvectors. Generally, the eigenvalues and eigenvectors are obtained through the eigen-analysis, but this analysis requires high computational complexity and late convergence time. For this reason, it is almost impossible to construct the real-time system with low-cost using this approach. Even though QR iteration is considered as the eigen-analysis approach to improve these problems, this is inappropriate to apply to the MUSIC algorithm. In this paper, we analyze the problems of conventional method based on the eigenvalues for convergence decision and propose the improved decision algorithm using the eigenvectors.

• Communications for Statistical Applications and Methods
• /
• v.15 no.1
• /
• pp.125-136
• /
• 2008

In many practical engineering design problems, the form of objective functions is not given explicitly in terms of design variables. Given the value of design variables, under this circumstance, the value of objective functions is obtained by real/computational experiments such as structural analysis, fluid mechanic analysis, thermodynamic analysis, and so on. These experiments are, in general, considerably expensive. In order to make the number of these experiments as few as possible, optimization is performed in parallel with predicting the form of objective functions. Response Surface Methods (RSM) are well known along this approach. This paper suggests to apply Support Vector Machines (SVM) for predicting the objective functions. One of most important tasks in this approach is to allocate sample data moderately in order to make the number of experiments as small as possible. It will be shown that the information of support vector can be used effectively to this aim. The effectiveness of our suggested method will be shown through numerical example which is well known in design of engineering.