• Title/Summary/Keyword: Hyperplane

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Variable length Chromosomes in Genetic Algorithms for Modeling the Class Boundaries

  • Bandyopadhyay, Sanghamitra;Pal, Sankar K.;Murthy, C.A.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.634-639
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    • 1998
  • A methodology based on the concept of variable string length GA(VGA) is developed for determining automatically the number of hyperplanes and their appropriate arrangement for modeling the class boundaries of a given training data set in RN. The genetic operators and fitness functionare newly defined to take care of the variability in chromosome length. Experimental results on different artificial and real life data sets are provided.

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TRANSNORMAL SYSTEMS ON $R_{1}^{n+1}$

  • Kwang Sung Park;Koon Chan Kim;Young Soo Jo
    • Communications of the Korean Mathematical Society
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    • v.12 no.1
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    • pp.109-112
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    • 1997
  • In this paper, we study on a classification of hypersurfaces given by tansnormal functions on $R^{n+1}_1$. If M is a level set of a transnormal function on $R^{n+1}_1$, then it is one of a hyperplane, a cylinder around k-plane, a pseudo-sphere and a pseudo-hyperbolic space.

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Closed convex set들의 교집합에 대한 연구

  • 최우용;장수영
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1993.10a
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    • pp.127-127
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    • 1993
  • Separating Hyperplane의 기하학적인 성질을 이용하여, 일반적인 Closed Convex Set들의 교집합에 속하는 점을 찾아가는 방법을 제안하고, 교집합에 속하는 점을 찾아가는 과정에서 그 교집합의 공집합 여부를 판정할 수 있는 방법을 제안하였다. 이 기법은 기존의 방법들이 가정하는 수렴조건보다 더 일반적인 조건 하에서도 수렴성을 갖는 것을 증명할 수 있었으며, 그 교집합의 공집합 여부를 선형부동식 해의 존재 유무로 판정할 수 있는 방법을 제시하였다. 몇가지 특수한 경우의 Convex Set들의 경우에 대한 기법의 적용 결과도 알아 보기로 한다.

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Design of the controller with sliding mode for flexible robot arm (유연한 로봇 팔의 슬라이딩모드를 갖는 제어기 설계)

  • 김성태;임규만;함운철
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.547-551
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    • 1996
  • In this paper, robust vibration control of a one-link flexible robot arm based on variable structure system is discussed. We derive dynamic equations of it using a Lagrangian assumed modes method based on Bernoulli-Euler Beam theory. The optimal sliding surface is designed and the problem of chattering is also solved by the adoption of a continuous control law within a small neighborhood of the switching hyperplane.

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A Speed Sensorless Vector Control for Permanent Magnet Synchronous Motors using the Integral Binary Observer (적분스위칭평면을 갖는 바이너리 관측기를 이용한 영구자석 동기전동기의 속도 및 위치센서리스 제어)

  • 한윤석;김영석;김현중
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.18-21
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    • 1999
  • This paper presents a speed and position sensorless control of permanent magnet synchronous motors using an integral binary observer. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral dynamics to the switching hyperplane equation. The observer structure and its deign method are described. The experimetntal results of the proposed algorithm are presented to demonstrate the effectiveness of the approach.

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Design of the robost hydraulic servomechanisms by continuously variable structure control (연속적 가변구조 제어에 의한 강인한 유압서보계의 설계)

  • 권기수;곽동훈;허준영;이진걸
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.945-950
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    • 1991
  • A method to design a robust servomechanism by continuously variable structure control is proposed. The state and control signal of this servomechanism do notchatter since a continuous control scheme is used. The input-output relation of this servomechanism is determined by prescribing a hyperplane in a state space of which the neighborhood is asymptotically attractive everywhere. This control mechanism was applied to a single rod cylinder servomechanism which has the nonlinerities due to their nonsymmetrical structure and its excellency was verified.

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On the Support Vector Machine with the kernel of the q-normal distribution

  • Joguchi, Hirofumi;Tanaka, Masaru
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.983-986
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    • 2002
  • Support Vector Machine (SVM) is one of the methods of pattern recognition that separate input data using hyperplane. This method has high capability of pattern recognition by using the technique, which says kernel trick, and the Radial basis function (RBF) kernel is usually used as a kernel function in kernel trick. In this paper we propose using the q-normal distribution to the kernel function, instead of conventional RBF, and compare two types of the kernel function.

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Sliding Mode Control with Finite Time Error Convergence

  • Park, Kang-Bak;Teruo Tsuji;Tsuyoshi Hanamoto
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.96-99
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    • 1999
  • In this paper, a sliding node controller guaranteeing finite time error convergence is proposed jot uncertain systems. By using a novel sliding hyperplane, it is guaranteed that the output tracking error converges to zero in finite time.

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Design of the Controller with Sliding Mode for Robot Arm (슬라이딩모드를 갖는 로봇 팔의 제어기 설계)

  • 서원창;임규만;정영창
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.703-706
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    • 1999
  • In this paper, robust vibration control of a one-link flexible robot arm based on variable structure system is discussed. We derive dynamic equations of it using a Lagragian assumed modes method based on Bernoulli-Euler beam theory. The optimal sliding surface is designed and the problem of chattering is also solved by the adoptation of a continuous control law within a small neighborhood of the switching hyperplane.

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Visualizing SVM Classification in Reduced Dimensions

  • Huh, Myung-Hoe;Park, Hee-Man
    • Communications for Statistical Applications and Methods
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    • v.16 no.5
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    • pp.881-889
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    • 2009
  • Support vector machines(SVMs) are known as flexible and efficient classifier of multivariate observations, producing a hyperplane or hyperdimensional curved surface in multidimensional feature space that best separates training samples by known groups. As various methodological extensions are made for SVM classifiers in recent years, it becomes more difficult to understand the constructed model intuitively. The aim of this paper is to visualize various SVM classifications tuned by several parameters in reduced dimensions, so that data analysts secure the tangible image of the products that the machine made.