DocumentCode
1150208
Title
Integer-weight neural nets
Author
Khan, Affan Hasan ; Hines, E.L.
Author_Institution
Dept. of Eng., Warwick Univ., Coventry
Volume
30
Issue
15
fYear
1994
fDate
7/21/1994 12:00:00 AM
Firstpage
1237
Lastpage
1238
Abstract
Integer-weight neural nets (IWNN) are better suited for hardware implementation than their real-weight analogues. The authors present a learning procedure for generating multilayer IWNNs having all weights in the set {-3, -2, -1, 0, 1, 2, 3}. The performance of this procedure was evaluated on XOR, encoder/decoder and the MONK benchmark. The IWNNS were found to be as capable as their real-weight counterparts with regard to generalisation performance
Keywords
learning (artificial intelligence); neural nets; MONK benchmark; integer-weight neural nets; learning procedure; multilayer type;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19940817
Filename
311914
Link To Document