DocumentCode
1507530
Title
Improved exponential bidirectional associative memory
Author
Chen, Songcan ; Gao, Hang ; Yan, WeI
Author_Institution
Dept. of Comput. Sci., Nanjing Univ. of Aeronaut. & Astronaut., China
Volume
33
Issue
3
fYear
1997
fDate
1/30/1997 12:00:00 AM
Firstpage
223
Lastpage
224
Abstract
Based on Jeng´s exponential bidirectional associative memory (eBAM) another improved updating rule for eBAMs is presented. In the recalling process of the improved eBAM (IeBAM), the continuity assumption of the eBAM is avoided, and the stability of the system in synchronous and asynchronous modes are proven by defining an energy function which decreases on the change of neuron states. The proposed model greatly improves the performances of the eBAM. Computer simulations demonstrate that the IeBAM has a much higher storage capacity and a better error correcting capability than those of the eBAM
Keywords
content-addressable storage; error correction; exponential distribution; neural nets; IeBAM; asynchronous modes; continuity assumption; eBAMs; energy function; error correcting capability; exponential bidirectional associative memory; neuron states; recalling process; storage capacity; synchronous modes; updating rule;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19970155
Filename
575939
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