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Volumn , Issue , 2008, Pages 361-368

A fuzzy clustering algorithm based on fuzzy distance norms for asynchronously sampled data

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING PROBLEMS; COMPUTATIONAL SCIENCE AND ENGINEERING; CONVENTIONAL CLUSTERING; FCM ALGORITHMS; FEATURE VECTORS; FUZZY C-MEANS ALGORITHMS; FUZZY C-MEANS CLUSTERING ALGORITHM; FUZZY CLUSTERING ALGORITHMS; FUZZY DISTANCE; INTERNATIONAL CONFERENCES; K-MEANS ALGORITHMS; NEW ALGORITHM; SAMPLED DATA; SYNCHRONOUS OBSERVATIONS;

EID: 51849095872     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSE.2008.7     Document Type: Conference Paper
Times cited : (6)

References (15)
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  • 5
    • 0021202650 scopus 로고
    • k-means type algorithm: A generalized convergence theorem and characterization of local optimality
    • Selim, S. Z. and Ismail, M. A., "'k-means type algorithm: a generalized convergence theorem and characterization of local optimality", IEEE Trans. Pattern Analysis Machine Intelligence, 6, 81-87, 1984
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    • Selim, S.Z.1    Ismail, M.A.2
  • 6
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  • 7
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    • Fuzzy Mathematics in Pattern Classification
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  • 8
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.