DocumentCode
296151
Title
A quick learning rule to expand stable attraction basins in autoassociative neural networks
Author
Qingshan, Zhou ; Guoxiang, Zhou ; JianDong, Hu
Author_Institution
Dept. of Telecommun. Eng., Beijing Univ. of Posts & Telecommun., China
Volume
4
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1977
Abstract
In this paper, a quick repeated learning rule, which is based on the Hebb rule and the Hamming distance distribution of the pattern set to be learned, is studied. With the help of the proposed learning rule, not only can the learned patterns be addressable, but an attraction basin with a predetermined radius is established for each attractor
Keywords
Hebbian learning; content-addressable storage; neural nets; Hamming distance distribution; Hebb rule; autoassociative neural networks; quick learning rule; radius of attraction; stable attraction basins; Electronic mail; Equations; Hamming distance; Hidden Markov models; Intelligent networks; Magnesium compounds; Neural networks; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488974
Filename
488974
Link To Document