DocumentCode
1123961
Title
On the Local Optimality of the Fuzzy Isodata Clustering Algorithm
Author
Selim, Shokri Z. ; Ismail, M.A.
Author_Institution
Department of Systems Engineering, University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Issue
2
fYear
1986
fDate
3/1/1986 12:00:00 AM
Firstpage
284
Lastpage
288
Abstract
The convergence of the fuzzy ISODATA clustering algorithm was proved by Bezdek [3]. Two sets of conditions were derived and it was conjectured that they are necessary and sufficient for a local minimum point. In this paper, we address this conjecture and explore the properties of the underlying optimization problem. The notions of reduced objective function and improving and feasible directions are used to examine this conjecture. Finally, based on the derived properties of the problem, a new stopping criterion for the fuzzy ISODATA algorithm is proposed.
Keywords
Clustering algorithms; Filtering; Hilbert space; Kalman filters; Minerals; Multidimensional signal processing; Petroleum; Signal processing algorithms; Speech processing; Systems engineering and theory; Fuzzy clustering algorithms; fuzzy ISODATA algorithm; fuzzy c-means algorithm; fuzzy unsupervised classification; local optimality;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.1986.4767783
Filename
4767783
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