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|Title:||Ordered fuzzy ARTMAP||Authors:||Dagher, Issam
|Affiliations:||Department of Computer Engineering||Keywords:||Pattern classification
Fuzzy neural nets
ART neural nets
|Subjects:||Computational complexity||Issue Date:||2002||Publisher:||IEEE||Part of:||IEEE World Congress on Computational Intelligence. IEEE International Joint Conference on Neural Networks Proceedings||Start page:||1717||End page:||1722||Conference:||IEEE International Joint Conference on Neural Networks (4-9 May 1998 : Anchorage, AK, USA)||Abstract:||
In this paper we introduce a procedure that identifies a fixed order of training pattern presentation for fuzzy ARTMAP. The resulting algorithm is named ordered fuzzy ARTMAP. Experimental results have demonstrated that ordered fuzzy ARTMAP achieves a network performance that is better than the average fuzzy ARTMAP network performance (averaged over a fixed number of random orders of pattern presentations), and occasionally better than the maximum fuzzy ARTMAP network performance (maximum over a fixed number of random orders of pattern presentations). What is also worth noting is that the computational complexity of the aforementioned procedure is only a small fraction of the computational complexity required to complete the training phase of fuzzy ARTMAP for a single order of pattern presentation.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/732||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Computer Engineering|
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