An enhanced progressive fuzzy clustering approach to pattern recognition
Im, Paul Poh Teng (1997) An enhanced progressive fuzzy clustering approach to pattern recognition. PhD thesis, Victoria University of Technology.
This thesis applies an enhanced progressive clustering approach, involving fuzzy clustering algorithms and fuzzy neural networks, to solve some practical problems of pattern recognition. A new fuzzy clustering framework, referred to as Cluster Prototype Centring by Membership (CPCM), has been developed. A Possibilistic Fuzzy c-Means algorithm(PFCM), which is also new, has been formulated to investigate properties of fuzzy clustering. PFCM extends the useability of the Fuzzy c-Means (FCM) algorithm by generalisation of the membership function.
|Item Type:||Thesis (PhD thesis)|
|Uncontrolled Keywords:||Pattern recognition, cluster set theory, fuzzy algorithms|
|Subjects:||FOR Classification > 0802 Computation Theory and Mathematics
Faculty/School/Research Centre/Department > School of Engineering and Science
|Depositing User:||VU Library|
|Date Deposited:||19 May 2010 04:58|
|Last Modified:||23 May 2013 16:42|
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