• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1413-1415
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• 2004

This paper proposes a SVM(Support Vector Machine) training algorithm to control a service robot with voice command. The service robot with a stereo vision system and dual manipulators of four degrees of freedom implements a User-Dependent Voice Control System. The training of SVM algorithm that is one of the statistical learning theories leads to a QP(quadratic programming) problem. In this paper, we present an efficient SVM speech recognition scheme especially based on less learning data comparing with conventional approaches. SVM discriminator decides rejection or acceptance of user's extracted voice features by the MFCC(Mel Frequency Cepstrum Coefficient). Among several SVM kernels, the exponential RBF function gives the best classification and the accurate user recognition. The numerical simulation and the experiment verified the usefulness of the proposed algorithm.

• Journal of applied mathematics & informatics
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• v.33 no.3_4
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• pp.235-246
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• 2015

In this paper, a vector optimization problem over cones is considered, where the functions involved are $\eta$-semidifferentiable. Necessary and sufficient optimality conditions are obtained. A dual is formulated and duality results are proved using the concepts of cone $\rho$-semilocally preinvex, cone $\rho$-semilocally quasi-preinvex and cone $\rho$-semilocally pseudo-preinvex functions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.4
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• pp.575-581
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• 2000

In this paper, a new active phase shifter is proposed using a vector sum method, and a unique digital phase control method of the circuit is suggested. The proposed scheme was designed and implemented using a Wilkinson power combiner/divider, a branch line 3 dB quadrature hybrid coupler and variable gain amplifiers (VGAs) using gate FETs(DGFETs). Furthermore, it was also shown that the proposed scheme is more efficient and works properly with the digital phase control method.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.69-85
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• 2006

Transductive Support Vector Machine(TSVM) is one of semi-supervised learning algorithms which exploit the domain structure of the whole data by considering labeled and unlabeled data together. Although it was proposed several years ago, there has been no efficient algorithm which can handle problems with more than hundreds of training examples. In this paper, we propose an efficient branch-and-bound algorithm which can solve large-scale TSVM problems with thousands of training examples. The proposed algorithm uses two bounding techniques: min-cut bound and reduced SVM bound. The min-cut bound is derived from a capacitated graph whose cuts represent a lower bound to the optimal objective function value of the dual problem. The reduced SVM bound is obtained by constructing the SVM problem with only labeled data. Experimental results show that the accuracy rate of TSVM can be significantly improved by learning from the optimal solution of TSVM, rather than an approximated solution.

• Kyungpook Mathematical Journal
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• v.56 no.3
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• pp.793-806
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• 2016

G-vector-valued sequence space frames and g-Banach frames for Banach spaces are introduced and studied in this paper. Also, the concepts of duality mapping and ${\beta}$-dual of a BK-space are used to define frame mapping and synthesis operator of these frames, respectively. Finally, some results regarding the existence of g-vector-valued sequence space frames and g-Banach frames are obtained. In particular, it is proved that if X is a separable Banach space and Y is a Banach space with a Schauder basis, then there exist a Y-valued sequence space $Y_v$ and a g-Banach frame for X with respect to Y and $Y_v$.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.367-378
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• 2016

Thrust Vectoring is a dynamic feature that offers many benefits in terms of maneuverability and control effectiveness. Thrust vectoring capabilities make the satisfaction of take-off and landing requirements easier. Moreover, it can be a valuable control effector at low dynamic pressures, where traditional aerodynamic controls are less effective. A numerical investigation of Fluidic Thrust Vectoring (FTV) is completed to evaluate the use of fluidic injection to manipulate flow separation and cause thrust vectoring of the primary jet thrust. The methodology presented is general and can be used to study different techniques of fluidic thrust vectoring like shock-vector control, sonic-plane skewing and counterflow methods. For validation purposes the method will focus on the dual-throat nozzle concept. Internal nozzle performances and thrust vector angles were computed for several range of nozzle pressure ratios and fluidic injection flow rate. The numerical results obtained are compared with the analogues experimental data reported in the scientific literature. The model is integrated using a finite volume discretization of the compressible URANS equations coupled with a Spalart-Allmaras turbulence model. Second order accuracy in space and time is achieved using an ENO scheme.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.262-264
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• 1996

This paper presents a new dual loop control using novel vector phase locked loop(VP-PLL) for a high power static var compensator(SVC) with three-level GTO voltage source inverter(VSI). Through circuit DQ-transformation, a simple dq-axis equivalent circuit is obtained. From this, DC analysis is carried out to obtain maximum controllable phase angle ${\alpha}_{max}$ per unit current between the three phase source and the switching function of inverter, and AC open-loop transfer function is given. Because ${\alpha}_{max}$ becomes small in high power SVC, this paper proposes VP-PLL for more accurate $\alpha$-control. As a result, the overall control loop has dual loop structure, which consists of inner VP-PLL for synchronizing the phase angle with source and outer Q-loop for compensating reactive power of load. Finally, the validity of the proposed control method is verified through the experimental results.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.268-270
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• 1995

In crane drives, DC motor has been most widely used due to simple control characteristic and favorable transient behavior. Nowadays, however, the squirrel cage induction motor is known as an attractive candidate due to elimination of all sliding electrical contacts, resulting in an exceedingly simple and rugged construction. Especially, in hoist application, the smooth torque control and four quadrant operation are essential. In this paper, an operation of dual inverters with common DC bus fed by vector controlled induction motor is described. Single DSP is employed as a main processor to control dual inverters and communicates each input/output signal with PLC. As well as giving a detailed expression, full simulation and experimental results are presented.

• Journal of Power Electronics
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• v.17 no.1
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• pp.161-171
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• 2017

To enhance the reliability of two-motor drive systems, this paper proposes an improved direct torque control (DTC) scheme (P-DTC) for five-leg dual-PMSM drive systems. First, the topology of a five-leg dual-PMSM drive system is illustrated. To clarify the analysis of the P-DTC, the standard DTC scheme for three-phase drive systems is presented. The operation of a five-leg dual-PMSM drive system is classified into three situations according to the definitions of the switching-vector unions. Compared with the existing DTC scheme (R-DTC), the P-DTC can minimize the replacement of active switching-vectors to zero switching-vectors. When this replacement cannot be avoided, the P-DTC uses a proposed master-slave selection principle to minimize the system error. Comparing with the R-DTC, the P-DTC has lower torque ripples, a wider speed range and a faster torque increasing response. Experiments have been carried out in the coupling and independent modes, and the effectiveness of the P-DTC is verified by the obtained results.