Title
Properties of learning in fuzzy ART
Abstract
This paper presents some important properties of the Fuzzy ART neural network algorithm. The properties described in the paper are distinguished into a number of categories. These include template, access, and reset properties, as well as properties related to the number of list presentations needed for weight stabilization. These properties provide numerous insights as to how Fuzzy ART operates. Furthermore, the effect of the Fuzzy ART parameters α and ρ on the functionality of the algorithm is clearly illustrated.
Publication Date
12-1-1994
Publication Title
IEEE International Conference on Neural Networks - Conference Proceedings
Volume
2
Number of Pages
756-761
Document Type
Article; Proceedings Paper
Identifier
scopus
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0028752258 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0028752258
STARS Citation
Huang, Juxin; Georgiopoulos, Michael; and Heileman, Gregory L., "Properties of learning in fuzzy ART" (1994). Scopus Export 1990s. 24.
https://stars.library.ucf.edu/scopus1990/24