DocumentCode
2782612
Title
A localized learning rule for analog VLSI implementation of neural networks
Author
Wasaki, Hiroyuki ; Horio, Yoshihiko ; Nakamura, Shogo
Author_Institution
Dept. of Electron. Eng., Tokyo Denki Univ., Japan
fYear
1990
fDate
12-14 Aug 1990
Firstpage
17
Abstract
A modified Hebbian type learning rule for self-organization which uses only the local information is proposed. As the result of computer simulations of self-organizing networks, the validity of the rule was confirmed and learning speed was improved. Furthermore, circuit examples for implementing the learning rule are proposed
Keywords
VLSI; analogue circuits; learning systems; neural nets; analog VLSI implementation; computer simulations; learning speed; local information; localized learning rule; modified Hebbian type learning rule; neural networks; self-organization; self-organizing networks; Circuit simulation; Computational modeling; Computer simulation; Distributed processing; Hardware; Integrated circuit interconnections; Neural networks; Neurons; Very large scale integration; Wires;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1990., Proceedings of the 33rd Midwest Symposium on
Conference_Location
Calgary, Alta.
Print_ISBN
0-7803-0081-5
Type
conf
DOI
10.1109/MWSCAS.1990.140641
Filename
140641
Link To Document