DocumentCode
2971494
Title
Robust learning rule for bidirectional associative memory
Author
Leung, C.S.
Author_Institution
Dept. of Comput. Sci., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Volume
3
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
2686
Abstract
A robust learning rule, called adaptive Ho-Kashyap bidirectional learning (AHKBL), is proposed to enhance the capacity and error correction capability of a bidirectional associative memory (BAM). Also, the sufficient conditions for convergence of AHKBL are discussed. Simulation shows that AHKBL greatly improves the capacity and the error correction capability of the BAM.
Keywords
content-addressable storage; error correction; learning (artificial intelligence); neural nets; adaptive Ho-Kashyap bidirectional learning; bidirectional associative memory; convergence; error correction capability; robust learning rule; sufficient conditions; Associative memory; Computer science; Convergence; Encoding; Error correction; Libraries; Magnesium compounds; Neurons; Robustness; Sufficient conditions;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714277
Filename
714277
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