• Title/Summary/Keyword: Vector Reduce

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SCALED VISUAL CURVATURE AND VISUAL FRENET FRAME FOR SPACE CURVES

  • Jeon, Myungjin
    • Journal of the Chungcheong Mathematical Society
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    • v.34 no.1
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    • pp.37-53
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    • 2021
  • In this paper we define scaled visual curvature and visual Frenet frame that can be visually accepted for discrete space curves. Scaled visual curvature is relatively simple compared to multi-scale visual curvature and easy to control the influence of noise. We adopt scaled minimizing directions of height functions on each neighborhood. Minimizing direction at a point of a curve is a direction that makes the point a local minimum. Minimizing direction can be given by a small noise around the point. To reduce this kind of influence of noise we exmine the direction whether it makes the point minimum in a neighborhood of some size. If this happens we call the direction scaled minimizing direction of C at p ∈ C in a neighborhood Br(p). Normal vector of a space curve is a second derivative of the curve but we characterize the normal vector of a curve by an integration of minimizing directions. Since integration is more robust to noise, we can find more robust definition of discrete normal vector, visual normal vector. On the other hand, the set of minimizing directions span the normal plane in the case of smooth curve. So we can find the tangent vector from minimizing directions. This lead to the definition of visual tangent vector which is orthogonal to the visual normal vector. By the cross product of visual tangent vector and visual normal vector, we can define visual binormal vector and form a Frenet frame. We examine these concepts to some discrete curve with noise and can see that the scaled visual curvature and visual Frenet frame approximate the original geometric invariants.

Vector control of AC servo motor using high Performance DSP (고성능 DSP를 이용한 AC 서보 모터의 벡터제어)

  • Choi, Chi-Young;Hong, Sun-Gi
    • Proceedings of the KIEE Conference
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    • 2003.04a
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    • pp.258-261
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    • 2003
  • This paper is a studying of the vector control of AC servo motor using a high performance DSP(TMX320F2812). This DSP has many special peripheral circuits to drive a AC Servo motor as AD converter, QEP and so on. It makes us reduce the time of developing a control system and also can be simple size controller. We use vector control algorithm for instantaneous torque control and SVPWM algorithm by offset voltage methods.

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EQUIVARIANT VECTOR BUNDLES OVER GRAPHS

  • Kim, Min Kyu
    • Journal of the Korean Mathematical Society
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    • v.54 no.1
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    • pp.227-248
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    • 2017
  • In this paper, we reduce the classification problem of equivariant (topological complex) vector bundles over a simple graph to the classification problem of their isotropy representations at vertices and midpoints of edges. Then, we solve the reduced problem in the case when the simple graph is homeomorphic to a circle. So, the paper could be considered as a generalization of [3].

COMMON-MODE VOLTAGE PULSE CANCELLATION METHOD BASED ON SPACE-VECTOR PWM IN CONVERTER-INVERTER SYSTEM

  • Lee, Hyeoun-Dong;Sul, Seung-Ki
    • Proceedings of the KIPE Conference
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    • 1998.10a
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    • pp.171-175
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    • 1998
  • This paper proposes the advanced PWM method that can reduce common-mode voltage in three-phase PWM converter-inverter system. By the proper distribution of the zero-voltage vector of inverter, it is possible to cancel out a common-mode voltage pulse in a sampling period. Since the proposed PWM method maintains the effective-voltage vector, it does not affect the control performance of converter-inverter system. Without any extra hardware, overall common-mode voltage can be decreased by one-third compared with conventional PWM scheme.

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Estimating Basin of Attraction for Multi-Basin Processes Using Support Vector Machine

  • Lee, Dae-Won;Lee, Jae-Wook
    • Management Science and Financial Engineering
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    • v.18 no.1
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    • pp.49-53
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    • 2012
  • A novel method of transient stability analysis is presented in this paper. The proposed method extracts data points near the basin-of-attraction boundary and then builds a support vector machine (SVM) model learned from the generated data. The constructed SVM classifier has been shown to reduce dramatically the conservativeness of the estimated basin of attraction.

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
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    • 2003.05a
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    • pp.444-449
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    • 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.

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Frame Rate Up-Conversion Using the Motion Vector Correction based on Motion Vector Frequency of Neighboring blocks (주변 블록의 움직임 벡터 빈도수에 기반한 움직임 벡터 교정을 적용한 프레임 율 변환 기법)

  • Lee, Jeong-Hun;Han, Dong-Il
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.259-260
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    • 2007
  • In this paper, a frame rate up-conversion algorithm using the motion vector frequency of neighboring blocks to reduce the block artifacts caused by failure of conventional motion estimation based on block matching algorithm is proposed. Experimental results show good performance of the proposed scheme with significant reduction of the erroneous motion vectors and block artifacts.

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Frame Rate Up-Conversion Considering The Direction and Magnitude of Identical Motion Vectors (동일한 움직임 벡터들의 방향과 크기를 고려한 프레임율 증가기법)

  • Park, Jonggeun;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.20 no.6
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    • pp.880-887
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    • 2015
  • In this paper, frame rate up conversion (FRUC) algorithm considering the direction and magnitude of identical motion vectors is proposed. extended bilateral motion estimation (EBME) has higher complexity than bilateral motion estimation (BME). By using average magnitude of motion vector with x and y direction respectively, dynamic frame and static frame are decided. We reduce complexity to decide EBME. also, After we compare the direction and magnitude of identical motion vectors, We reduce complexity to decide motion vector smoothing(MVS). Experimental results show that this proposed algorithm has fast computation and better peak singnal to noise ratio(PSNR) results compared with EBME.

Contents-based Image Retrieval Using Regression of Shape Features (모양 정보의 회귀추정에 의한 내용 기반 이미지 검색 기법)

  • Song Jun-Kyu;Choi Hwang-Kyu
    • Journal of Digital Contents Society
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    • v.2 no.2
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    • pp.157-166
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    • 2001
  • In this paper we propose a feature vector extraction technique using regression of shape features for the content-based image retrieval system. The proposed technique can reduce the number of dimensions of a feature vector by converting the extracted high-dimensional feature vector into a specific n-dimensional feature vector. This paper shows how to resolve the 'dimensionality curse' problem by reducing the number of dimensions of a feature vector, and shows that the technique is more efficient than the conventional techniques for the practical image retrievals.

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Support Vector Machine based Cluster Merging (Support Vector Machines 기반의 클러스터 결합 기법)

  • Choi, Byung-In;Rhee, Frank Chung-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.3
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    • pp.369-374
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    • 2004
  • A cluster merging algorithm that merges convex clusters resulted by the Fuzzy Convex Clustering(FCC) method into non-convex clusters was proposed. This was achieved by proposing a fast and reliable distance measure between two convex clusters using Support Vector Machines(SVM) to improve accuracy and speed over other existing conventional methods. In doing so, it was possible to reduce cluster number without losing its representation of the data. In this paper, results for several data sets are given to show the validity of our distance measure and algorithm.