Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Hyper-ellipsoidal clustering algorithm using Linear Matrix Inequality

선형행렬 부등식을 이용한 타원형 클러스터링 알고리즘

  • 이한성 (고려대학교 컴퓨터정보학과) ;
  • 박주영 (고려대학교 제어계측공학과) ;
  • 박대희 (고려대학교 컴퓨터정보학과)
  • Published : 2002.08.01
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Abstract

In this paper, we use the modified gaussian kernel function as clustering distance measure and recast the given hyper-ellipsoidal clustering problem as the optimization problem that minimizes the volume of hyper-ellipsoidal clusters, respectively and solve this using EVP (eigen value problem) that is one of the LMI (linear matrix inequality) techniques.

본 논문에서는 타원형 클러스터링을 위한 거리측정 함수로써 변형된 가우시안 커널 함수를 사용하며, 주어진 클러스터링 문제를 각 타원형 클러스터의 체적을 최소화하는 문 로 해석하고 이를 선형행렬 부등식 기법 중 하나인 고유값 문제로 변환하여 최적화하는 새로운 알고리즘을 제안한다.

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References

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