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|Title:||A comparative study of the category choice of the fuzzy ART with the L -1 norm||Authors:||Dagher, Issam||Affiliations:||Department of Computer Engineering||Keywords:||Fuzzy neural nets
ART neural nets
Learning (artificial intelligence)
|Issue Date:||2003||Publisher:||IEEE||Part of:||Proceedings of the International Joint Conference on Neural Networks, 2003||Start page:||1969||End page:||1974||Conference:||International Joint Conference on Neural Networks (20-24 July 2003 : Portland, OR, USA)||Abstract:||
In this paper, a comparative study of the category choice of the Fuzzy ART with the L-1 norm is presented. It is shown that the category choice can be replaced by a distance measure related to the L-1 norm. This distance measure will have the following advantages over the category choice of the Fuzzy ART network: 1) no need for augmenting the dimensions of the input patterns. The distance measure will operate directly on the input patterns without the need for doing complement coding; and 2) no need for normalizing the input patterns. The input patterns need not to be in the interval.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/450||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Computer Engineering|
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