An initial independent and highly noise-resistant fuzzy possibilistic clustering algorithm

Xinhua Zhuang Xinhua Zhuang,Tong Huang Tong Huang,Yunxin Zhao Yunxin Zhao,Yan Huang Yan Huang

doi:10.1109/sipnn.1994.344923

An initial independent and highly noise-resistant fuzzy possibilistic clustering algorithm

Xinhua Zhuang Xinhua Zhuang, Tong Huang Tong Huang + Show 2 more

https://doi.org/10.1109/sipnn.1994.344923

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Publication Date: Apr 13, 1994

Citations: 4

Affiliation: University of Missouri

#Possibilistic C-means Clustering #Possibilistic Clustering Algorithm + Show 8 more

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Abstract

The possibilistic C-means (PCM) clustering algorithm is shown to be superior to the conventional fuzzy C-means (FCM) clustering algorithms. We attack several unsolved issues in applying the possibilistic approach to fuzzy clustering. An initial independent and highly noise resistant possibilistic clustering algorithm, named the novel possibilistic C-means (NPCM) clustering algorithm, is developed. >

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