DocumentCode
1099858
Title
Neural networks with higher-order nonlinearity
Author
Tai, Heng-Ming ; Jong, Tai-Lang
Author_Institution
Dept. of Electr. Eng., Tulsa Univ., OK
Volume
24
Issue
19
fYear
1988
fDate
9/15/1988 12:00:00 AM
Firstpage
1225
Lastpage
1226
Abstract
Neural networks for associative memory based on the Hopfield relaxation model and matched filtering techniques with higher-order nonlinearity are proposed. These high-order models show dramatic improvement in memory storage capacity and error-correction capability in comparison to conventional binary autoassociative models
Keywords
content-addressable storage; error correction; filtering and prediction theory; neural nets; Hopfield relaxation model; associative memory; error-correction capability; higher-order nonlinearity; matched filtering techniques; memory storage capacity; neural networks;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
Filename
29174
Link To Document