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An interval type-2 fuzzy PCM algorithm for pattern recognition

Authors
Min, Ji-HeeShim, Eun-ARhee, Frank Chung-Hoon
Issue Date
Aug-2009
Publisher
IEEE
Keywords
Fuzzy C-means; Possibilistic c-means; Fuzzy approach; Fuzzy parameter; Pattern recognition; Initial parameter; Short distances; Pulse code modulation; Noise data; Fuzzy systems
Citation
IEEE International Conference on Fuzzy Systems, pp.480 - 483
Indexed
SCIE
Journal Title
IEEE International Conference on Fuzzy Systems
Start Page
480
End Page
483
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/40984
DOI
10.1109/FUZZY.2009.5277167
ISSN
1098-7584
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 the initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome theses drawbacks, we propose an interval type-2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm. ©2009 IEEE.
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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