DocumentCode
288417
Title
Properties of learning in fuzzy ART
Author
Huang, Juxin ; Georgiopoulos, Michael ; Heileman, Gregory L.
Author_Institution
Dept. of Electr. & Comput. Eng., Central Florida Univ., Orlando, FL, USA
Volume
2
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
756
Abstract
This paper presents some important properties of the fuzzy ART neural network algorithm. The properties described in the paper are divided 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
Keywords
ART neural nets; fuzzy neural nets; learning (artificial intelligence); access; functionality; fuzzy ART neural network algorithm; learning; list presentations; reset; template; weight stabilization; Equations; Fuzzy logic; Subspace constraints;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374272
Filename
374272
Link To Document