• Title/Summary/Keyword: Vector method

Search Result 5,546, Processing Time 0.033 seconds

A Novel Modulation Method for Three-Level Inverter Neutral Point Potential Oscillation Elimination

  • Yao, Yuan;Kang, Longyun;Zhang, Zhi
    • Journal of Power Electronics
    • /
    • v.18 no.2
    • /
    • pp.445-455
    • /
    • 2018
  • A novel algorithm is proposed to regulate the neutral point potential in neutral point clamped three-level inverters. Oscillations of the neutral point potential and an unbalanced dc-link voltage cause distortions of the output voltage. Large capacitors, which make the application costly and bulky, are needed to eliminate oscillations. Thus, the algorithm proposed in this paper utilizes the finite-control-set model predictive control and the multistage medium vector to solve these issues. The proposed strategy consists of a two-step prediction and a cost function to evaluate the selected multistage medium vector. Unlike the virtual vector method, the multistage medium vector is a mixture of the virtual vector and the original vector. In addition, its amplitude is variable. The neutral point current generated by it can be used to adjust the neutral point potential. When compared with the virtual vector method, the multistage medium vector contributes to decreasing the regulation time when the modulation index is high. The vectors are rearranged to cope with the variable switching frequency of the model predictive control. Simulation and experimental results verify the validity of the proposed strategy.

A Note on Deconvolution Estimators when Measurement Errors are Normal

  • Lee, Sung-Ho
    • Communications for Statistical Applications and Methods
    • /
    • v.19 no.4
    • /
    • pp.517-526
    • /
    • 2012
  • In this paper a support vector method is proposed for use when the sample observations are contaminated by a normally distributed measurement error. The performance of deconvolution density estimators based on the support vector method is explored and compared with kernel density estimators by means of a simulation study. An interesting result was that for the estimation of kurtotic density, the support vector deconvolution estimator with a Gaussian kernel showed a better performance than the classical deconvolution kernel estimator.

Vector Control of Induction Motors using 80C196MC (80C196MC를 이용한 유도전동기 벡터제어)

  • 이동명;김창현;이주환;김학원;홍석종;김종철;신휘범
    • Proceedings of the KIPE Conference
    • /
    • 1997.07a
    • /
    • pp.156-160
    • /
    • 1997
  • This paper proposed the vector controller of induction motors using one chip microprocessor. For developing a small and cheep speed control system, we use the one chip microprocessor 80C196MC. By using the one chip microprocessor we can make an inexpensive and small-sized vector controller for induction motors. We apply indirect vector control method and space vector modulation method to this system. The experimental results show that the proposed inverter has high performance features.

  • PDF

Method of Shape Error Measurement for the Optimal Blank Design of Shapes with 3D Contour Lines (목표윤곽선이 3 차원 곡선인 형상의 최적블랭크 설계를 위한 형상오차 측정법)

  • Shim, H.B.
    • Transactions of Materials Processing
    • /
    • v.24 no.1
    • /
    • pp.28-36
    • /
    • 2015
  • After a short review of the iterative optimal blank method, a new method of measuring the shape error for stamped parts with 3D contour lines, which is an essential component of the optimal blank design, is proposed. When the contour line of the target shape does not exist in a plane, but exists in 3D space, especially when the shape of the target contour line is very complicated as in the real automotive parts, then the measurement of the shape error is critical. In the current study, a method of shape error measurement based on the minimum distance is suggested as an evolution of the radius vector method. With the proposed method, the optimal blank shapes of real automotive parts were found and compared to the results of the radius vector method. From the current investigation the new method is found to resolve the issues with the radius vector method.

Vector Map Data Watermarking Method using Binary Notation

  • Kim, Jung-Yeop;Park, Soo-Hong
    • Spatial Information Research
    • /
    • v.15 no.4
    • /
    • pp.385-395
    • /
    • 2007
  • As the growth of performance of the computer and the development of the Internet are exponential, sharing and using the information illegally have also increased to the same proportion. In this paper, we proposed a novel method on the vector map data among digital contents. Vector map data are used for GIS, navigation and web-based services etc. We embedded watermark into the coordinate of the vector map data using bit operation and extracted the watermark. This method helps to protect the copyright of the vector map data. This watermarking method is a spatial domain method and it embeds the watermark within an allowable error. Our experiment shows that the watermark produced by this method is resistant to simplification and translation.

  • PDF

Morphological Feature Extraction of Microorganisms Using Image Processing

  • Kim Hak-Kyeong;Jeong Nam-Su;Kim Sang-Bong;Lee Myung-Suk
    • Fisheries and Aquatic Sciences
    • /
    • v.4 no.1
    • /
    • pp.1-9
    • /
    • 2001
  • This paper describes a procedure extracting feature vector of a target cell more precisely in the case of identifying specified cell. The classification of object type is based on feature vector such as area, complexity, centroid, rotation angle, effective diameter, perimeter, width and height of the object So, the feature vector plays very important role in classifying objects. Because the feature vectors is affected by noises and holes, it is necessary to remove noises contaminated in original image to get feature vector extraction exactly. In this paper, we propose the following method to do to get feature vector extraction exactly. First, by Otsu's optimal threshold selection method and morphological filters such as cleaning, filling and opening filters, we separate objects from background an get rid of isolated particles. After the labeling step by 4-adjacent neighborhood, the labeled image is filtered by the area filter. From this area-filtered image, feature vector such as area, complexity, centroid, rotation angle, effective diameter, the perimeter based on chain code and the width and height based on rotation matrix are extracted. To prove the effectiveness, the proposed method is applied for yeast Zygosaccharomyces rouxn. It is also shown that the experimental results from the proposed method is more efficient in measuring feature vectors than from only Otsu's optimal threshold detection method.

  • PDF

A NUMERICAL METHOD FOR THE MODIFIED VECTOR-VALUED ALLEN-CAHN PHASE-FIELD MODEL AND ITS APPLICATION TO MULTIPHASE IMAGE SEGMENTATION

  • Lee, Hyun Geun;Lee, June-Yub
    • Journal of the Korean Society for Industrial and Applied Mathematics
    • /
    • v.18 no.1
    • /
    • pp.27-41
    • /
    • 2014
  • In this paper, we present an efficient numerical method for multiphase image segmentation using a multiphase-field model. The method combines the vector-valued Allen-Cahn phase-field equation with initial data fitting terms containing prescribed interface width and fidelity constants. An efficient numerical solution is achieved using the recently developed hybrid operator splitting method for the vector-valued Allen-Cahn phase-field equation. We split the modified vector-valued Allen-Cahn equation into a nonlinear equation and a linear diffusion equation with a source term. The linear diffusion equation is discretized using an implicit scheme and the resulting implicit discrete system of equations is solved by a multigrid method. The nonlinear equation is solved semi-analytically using a closed-form solution. And by treating the source term of the linear diffusion equation explicitly, we solve the modified vector-valued Allen-Cahn equation in a decoupled way. By decoupling the governing equation, we can speed up the segmentation process with multiple phases. We perform some characteristic numerical experiments for multiphase image segmentation.

Object-based Stereo Sequence Coding using Disparity and Motion Vector Relationship (변이-움직임 벡터의 상관관계를 이용한 객체기반 스테레오 동영상 부호화)

  • 박찬희;손광훈
    • Journal of Broadcast Engineering
    • /
    • v.7 no.3
    • /
    • pp.238-247
    • /
    • 2002
  • In this paper, we propose an object-based stereo sequence compression technique using disparity-motion vector relationship. The proposed method uses the coherence of motion vectors and disparity vectors in the left and right Image sequences. After two motion vectors and one disparity vector ate computed using FBMA(Fixed Block Matching Algorithm), the disparity vector of the current stereoscopic pall is computed by disparity-motion vector relationship with vectors which are previously estimated. Moreover, a vector regularization technique is applied in order to obtain reliable vectors. For an object-based coding. the object is defined and coded in terms of layers of VOP such as in MPEG-4. we present a method using disparity and motion vector relationship for extending two-frame compensation into three-frame compensation method for prediction coding of B-VOP. The proposed algorithm shows a high performance when comparing with a conventional method.

A vector control method for parallel connected induction motor (병렬구동 유도전동기 벡터제어 기법)

  • Byun Yeun-Sub;Kim Yong-Kyu;Shin Ducko;Kim Jong-Gi
    • Proceedings of the KSR Conference
    • /
    • 2003.05a
    • /
    • pp.444-449
    • /
    • 2003
  • This paper presents a vector control method for the parallel-connected motor drive system. In this paper new estimation scheme of rotor flux position is presented to reduce sensitivity due to load difference between the motors. To confirm the validity of the proposed control method, we compare a simulation result of the proposed control method with that of the conventional indirect vector control method. The simulation results show that the proposed control method is effective the step change in load torque.

  • PDF

An Improvement of LVQ3 Learning Using SVM (SVM을 이용한 LVQ3 학습의 성능개선)

  • 김상운
    • Proceedings of the IEEK Conference
    • /
    • 2001.06c
    • /
    • pp.9-12
    • /
    • 2001
  • Learning vector quantization (LVQ) is a supervised learning technique that uses class information to move the vector quantizer slightly, so as to improve the quality of the classifier decision regions. In this paper we propose a selection method of initial codebook vectors for a teaming vector quantization (LVQ3) using support vector machines (SVM). The method is experimented with artificial and real design data sets and compared with conventional methods of the condensed nearest neighbor (CNN) and its modifications (mCNN). From the experiments, it is discovered that the proposed method produces higher performance than the conventional ones and then it could be used efficiently for designing nonparametric classifiers.

  • PDF