DocumentCode
1264268
Title
Two coding strategies for bidirectional associative memory
Author
Wang, Yeou-Fang ; Cruz, Jose B., Jr. ; Mulligan, James H., Jr.
Author_Institution
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
Volume
1
Issue
1
fYear
1990
fDate
3/1/1990 12:00:00 AM
Firstpage
81
Lastpage
92
Abstract
Enhancements of the encoding strategy of a discrete bidirectional associative memory (BAM) reported by B. Kosko (1987) are presented. There are two major concepts in this work: multiple training, which can be guaranteed to achieve recall of a single trained pair under suitable initial conditions of data, and dummy augmentation, which can be guaranteed to achieve recall of all trained pairs if attaching dummy data to the training pairs is allowable. In representative computer simulations, multiple training has been shown to lead to an improvement over the original Kosko strategy for recall of multiple pairs as well. A sufficient condition for a correlation matrix to make the energies of the training pairs be local minima is discussed. The use of multiple training and dummy augmentation concepts are illustrated, and theorems underlying the results are presented
Keywords
content-addressable storage; encoding; neural nets; Kosko strategy; bidirectional associative memory; correlation matrix; dummy augmentation; encoding strategy; multiple training; neural nets; sufficient condition; Associative memory; Computer simulation; Encoding; Iterative decoding; Joining processes; Magnesium compounds; Manufacturing; Neural networks; Subcontracting; Sufficient conditions;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.80207
Filename
80207
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