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
fDate :
27 Jun-2 Jul 1994
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;
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
DOI :
10.1109/ICNN.1994.374272
