Survey of fuzzy min–max neural network for pattern classification variants and applications

Al Sayaydeh, Osama Nayel, Mohammed, Mohammed Falah and Lim, Chee Peng 2019, Survey of fuzzy min–max neural network for pattern classification variants and applications, IEEE transactions on fuzzy systems, vol. 27, no. 4, pp. 635-645, doi: 10.1109/TFUZZ.2018.2865950.

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Title Survey of fuzzy min–max neural network for pattern classification variants and applications
Author(s) Al Sayaydeh, Osama Nayel
Mohammed, Mohammed Falah
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Journal name IEEE transactions on fuzzy systems
Volume number 27
Issue number 4
Start page 635
End page 645
Total pages 11
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Publication date 2019-04
ISSN 1063-6706
Keyword(s) Fuzzy min–max model
Pattern classification
Hyperbox structure
Neural network learning
Science & Technology
Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Computer Science
Engineering
Fuzzy min-max (FMM) model
Language eng
DOI 10.1109/TFUZZ.2018.2865950
Field of Research 0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
0102 Applied Mathematics
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30113268

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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