Title :
Hybrid fuzzy neural nets are universal approximators
Author :
Buckley, James J. ; Hayashi, Yoichi
Author_Institution :
Dept. of Math., Alabama Univ., Birmingham, AL, USA
Abstract :
It is known that regular fuzzy neural nets, based on standard fuzzy arithmetic and the extension principle, can not be universal approximators. This negative result is surprising since (regular) neural nets are universal approximators. We argue that hybrid fuzzy neural nets, not necessarily based only on standard fuzzy arithmetic, can be universal approximators
Keywords :
approximation theory; fuzzy neural nets; fuzzy set theory; transfer functions; fuzzy arithmetic; hybrid fuzzy neural nets; transfer function; universal approximators; Control systems; Digital arithmetic; Extraterrestrial measurements; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Hybrid intelligent systems; Mathematics; Neural networks; Neurons;
Conference_Titel :
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1896-X
DOI :
10.1109/FUZZY.1994.343759
