DocumentCode :
456524
Title :
Noise Clustering using a New Distance
Author :
Wu, Xiao-Hong ; Zhou, Jian-Jiang
Author_Institution :
Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut.
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
1938
Lastpage :
1943
Abstract :
Based on a new distance, a novel noise-resistant fuzzy clustering algorithm called alternative noise clustering (ANC) algorithm is proposed. ANC is an extension of the noise clustering (NC) algorithm proposed by Dave (1993). By replacing the Euclidean distance used in the objective function of NC algorithm, a new distance (non-Euclidean distance) is introduced in NC algorithm. Based on robust statistical point of view and influence function, the non-Euclidean distance is more robust than the Euclidean distance. So the ANC algorithm is more robust than the NC algorithm. Moreover, with the new distance ANC can deal with noises or outliers better than NC and fuzzy c-means (FCM). The better performance of the proposed algorithm is shown by performing experiments on data sets
Keywords :
fuzzy set theory; noise; pattern clustering; alternative noise clustering; noise-resistant fuzzy clustering; nonEuclidean distance; Clustering algorithms; Computer vision; Digital images; Educational institutions; Equations; Euclidean distance; Noise robustness; Partitioning algorithms; Pattern recognition; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location :
Damascus
Print_ISBN :
0-7803-9521-2
Type :
conf
DOI :
10.1109/ICTTA.2006.1684686
Filename :
1684686
Link To Document :
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