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231224s1980 xx ||||| 00| ||eng c |
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|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Bezdek, J C
|e verfasserin
|4 aut
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| 245 |
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|a A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
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| 264 |
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|c 1980
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 02.10.2012
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|a Date Revised 12.11.2019
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a In this paper the convergence of a class of clustering procedures, popularly known as the fuzzy ISODATA algorithms, is established. The theory of Zangwill is used to prove that arbitrary sequences generated by these (Picard iteration) procedures always terminates at a local minimum, or at worst, always contains a subsequence which converges to a local minimum of the generalized least squares objective functional which defines the problem
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| 650 |
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|a Journal Article
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 2(1980), 1 vom: 01. Jan., Seite 1-8
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
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| 951 |
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|a AR
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| 952 |
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|d 2
|j 1980
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