Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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An Interval Type-2 Fuzzy PCM Algorithm for Pattern Recognition

패턴인식을 위한 Interval Type-2 퍼지 PCM 알고리즘

  • 민지희 (한양대학교 전자 컴퓨터 제어 계측 공학과) ;
  • 이정훈 (한양대학교 전자 컴퓨터 제어 계측 공학과)
  • Published : 2009.02.25
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Abstract

The Possibilistic C-means(PCM) was proposed to overcome some of the drawbacks associated with the Fuzzy C-means(FCM) such as improved performance for noise data. However, PCM possesses some drawbacks such as sensitivity in initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome these drawbacks, we propose an interval type 2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm.

Fuzzy C-Means(FCM)의 단점을 극복하기 위해 제안되었던 PCM은 잡음에는 강하지만 초기 파라미터 값에 민감하고, 상대적으로 가까이에 위치한 prototype들을 형성하는 패턴들의 경우에는 최종 prototype의 위치가 겹치는(동일한) 결과가 나올 수 있다는 단점이 있다. 이러한 PCM의 단점을 극복하기 위해 여러 방법이 제안되었지만, 본 논문에서는 PCM 알고리즘에 Interval Type 2 Fuzzy 접근 방법을 적용하여 PCM 알고리즘의 파라미터에 존재하는 uncertainty를 제어함으로써 성능을 향상시키는 방법을 제안한다.

Keywords

References

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