• Journal of Power Electronics
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• v.16 no.3
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• pp.946-959
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• 2016

A novel Virtual Space Vector (VSV) modulation strategy for complete control of potential neutral point (NP) issues is proposed in this paper. The neutral point potential balancing problems of multi-level converters, which include elimination of low frequency oscillations and self-balancing for NP dc unbalance, are investigated first. Then a set of improved virtual space vectors with dynamic adjustment factors are introduced and a multi-objective optimization algorithm which aims to optimize these adjustment factors is presented in this paper. The improved virtual space vectors and the multi-objective optimization algorithm constitute the novel Virtual Space Vector modulation. The proposed novel Virtual Space Vector modulation can simultaneously recover NP dc unbalance and eliminate low frequency oscillations of the neutral point. Experiment results show that the proposed strategy has excellent performance, and that both of the neutral point potential issues can be solved.

• Proceedings of the KIPE Conference
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• 2014.11a
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• pp.115-116
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• 2014

기존의 2-레벨 인버터에 비해 더 나은 출력특성을 갖는 멀티레벨 인버터가 등장함에 따라 이를 좀 더 효율적으로 사용하고자 많은 연구가 진행되어 왔다. 멀티레벨 인버터 종류의 하나로 Neutral-Point-Clamped 인버터를 들 수 있는데, 이를 구동하기 위한 방식으로 여러 가지 PWM 기법들이 사용되고 있다. 기존의 방식들에서는 dc-link단의 커패시터에서 저주파수리플이 발생하는 문제가 있다. 이에 관하여, virtual space vector PWM 기법이 제안된 바 있다. 본 논문에서는 이 기법을 계통연계 방식에 적용하여 그 결과를 시뮬레이션을 통해 확인하였다.

• Journal of Power Electronics
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• v.13 no.5
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• pp.787-797
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• 2013

Despite the advantages offered by multilevel inverters, one of the main drawbacks that prevents their widespread use is their circuit complexity as the number of power switches employed is usually high. This paper presents a new multilevel inverter topology with a considerable reduction in the number of power switches used through the switch-sharing approach. The fact that the proposed inverter applies two bidirectional power switches for sharing among the three phases does not prevent it from producing seven levels in the line-to-line output voltage waveforms. A modified scheme of space vector modulation via the application of virtual voltage vectors is developed to generate the PWM signals of the power switches. The performance of the proposed inverter is investigated through MATLAB/SIMULINK simulations and is practically tested using a laboratory prototype with a DSP-based modulator. The results demonstrate the satisfactory performance of the inverter and verify the effectiveness of the modulation method.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.405-407
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• 2009

SVM(Support Vector Machine) is a classification method which is recently watched in mechanical learning system. Vapnik, Osuna, Platt etc. had suggested methodology in order to solve needed QP(Quadratic Programming) to realize SVM so that have extended application field. SVM find hyperplane which classify into 2 class by converting from input space converter vector to characteristic space vector using Kernel Function. This is very systematic and theoretical more than neural network which is experiential study method. Although SVM has superior generalization characteristic, it depends on Kernel Function. There are three category in the Kernel Function as Polynomial Kernel, RBF(Radial Basis Function) Kernel, Sigmoid Kernel. This paper has analyzed performance of SVM against kernel using virtual data.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.11
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• pp.675-690
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• 2003

In this paper, we present the virtual dancing studio for distributed virtual environment. In this system, geographically distributed user shares the virtual dancing hall and interacts with each other. The participating object can be a graphical avatar or a live video stream. It allows the coexistence of graphic objects and real images in the shared virtual space. One of the main technical challenges in developing the distributed virtual environment is to handle excessive network traffic. In an effort to effectively reduce the network traffic, we propose a scheme to adjust the QoS of each object with respect to the distance from the observer in the virtual space. The server maintains the QoS vector for each client's shared space and controls the packet traffic to individual clients based on its QoS vectors. We develop a proto-type virtual dancing environment. Java based development enables the client to be platform independent. The result of experiment shows that the adoption of hierarchical QoS management significantly reduces the overall network traffic.

• Journal of Power Electronics
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• v.19 no.1
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• pp.168-178
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• 2019

Discrete space vector modulation (DSVM) is an effective method to improve the steady-state performance of the finite control set predictive control for permanent magnet synchronous motor drive systems. However, it requires complex computations due to the presence of numerous virtual voltage vectors. This paper proposes an improved finite control set model-free predictive control using DSVM to reduce the computational burden. First, model-free deadbeat current control is used to generate the reference voltage vector. Then, based on the principle that the voltage vector closest to the reference voltage vector minimizes the cost function, the optimal voltage vector is obtained in an effective way which avoids evaluation of the cost function. Additionally, in order to implement double-objective control, a two-level decisional cost function is designed to sequentially reduce the stator currents tracking error and the inverter switching frequency. The effectiveness of the proposed control is validated based on experimental tests.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.501-508
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• 2004

This paper proposes a virtual relevant document technique in the teaming phase for text categorization. The method uses a simple transformation of relevant documents, i.e. making virtual documents by combining document pairs in the training set. The virtual document produced by this method has the enriched term vector space, with greater weights for the terms that co-occur in two relevant documents. The experimental results showed a significant improvement over the baseline, which proves the usefulness of the proposed method: 71% improvement on TREC-11 filtering test collection and 11% improvement on Routers-21578 test set for the topics with less than 100 relevant documents in the micro average F1. The result analysis indicates that the addition of virtual relevant documents contributes to the steady improvement of the performance.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1648-1649
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• 2007

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM(Support Vector Machines) makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller be with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.626-637
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• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.