DocumentCode
2623598
Title
Learning rules for multilayer neural networks using a difference approximation
Author
Maeda, Yutaka ; Yamashita, Hisanobu ; Kanata, Yakichi
Author_Institution
Dept. of Electr. Eng., Kansai Univ., Suita, Japan
fYear
1991
fDate
18-21 Nov 1991
Firstpage
628
Abstract
The authors describe learning rules of multilayer feedforward neural networks using a difference approximation of an error function. Simulation results by digital computer are shown. These learning rules are easy to realize as an electronic circuit. An analog neural network circuit that learns the exclusive-OR problem by using the proposed learning rule has been fabricated. The details of the circuit and the operation results are presented
Keywords
application specific integrated circuits; learning systems; neural nets; analog neural network circuit; difference approximation; digital computer; error function; exclusive-OR problem; learning rules; multilayer feedforward neural networks; multilayer neural networks; Circuit simulation; Computer networks; Electronic circuits; Emulation; Feedforward neural networks; Hardware; Microelectronics; Multi-layer neural network; Neural networks; Optical devices;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170470
Filename
170470
Link To Document