Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
권호 표지

A Study on the Fuzzy Similarity Measure

퍼지 유사 척도에 관한 연구

  • Published : 1997.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper a fuzzy similarity measure is proposed. The proposed fuzzy similarity measure considers the relative distance between data and cluster centers in addition to the Euclidean distance to decide the degree of similarity. The boundary of a cluster center is constracted on the competitive region and expanded on the less competitive region. This result shows the possibility of using relative distance as a similarity measure.

본 논문에서는 퍼지 유사 척도가 제시된다. 제시된 퍼지 유사 척도는 유사도를 결정하기 위해서 유크라디안 거리와 함께 데이터와 클러스터 대표값들 사이의 상대적 거리를 고려한다. 클러스터의 경계선은 경쟁이 심한 곳에서는 축소되며 경쟁이 심하지 않은 곳에서는 확장된다. 본 논문의 결과는 상대적 거리를 유사 척도로 사용하는 가능성을 보인다.

Keywords

References

  1. Pattern Recognition with Fuzzy Objective Function Algotithms J.C.Bezdek
  2. Pattern Recognition Principles J.T.Tou;R.C.Gonzalez
  3. IEEE ASSP Mag. An Introduction to Computing with Neural Net R.P.Lippmann
  4. Fuzzy Models for Pattern Recognition-Methods That Search for Structures in Data J.C.Bezdek;S.K.Pal
  5. Computer Vision, Graphics, and Image Processing v.37 A Massively Parallel Architecture for A Self-Organizing Neural Pattern Reconition Machine G.A.Carpenter;S.Grossberg
  6. Neural Networks v.4 no.6 Fuzzy ART:Fast Stable Learning and Gategorization of Analog Patterns by an Adaptive Resonance Systems G.A.Carpenter;S.Grossberg;D.Rosen
  7. IEEE Trans. on Fuzzy System v.1 no.1 Fuzzy min-mix neural newworks Part2:Clustering P.K.Simpson
  8. Fuzzy Sets and System v.65 An Adaptive Integrated Fuzzy Clustering Model for Pattern Recognition Y.S.Kim;S.Mitra