Document Detail


A feedforward bidirectional associative memory.
MedLine Citation:
PMID:  18249814     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
In contrast to conventional feedback bidirectional associative memory (BAM) network models, a feedforward BAM network is developed based on a one-shot design algorithm of O(p(2)(n+m)) computational complexity, where p is the number of prototype pairs and n, m are the dimensions of the input/output bipolar vectors. The feedforward BAM is an n-p-m three-layer network of McCulloch-Pitts neurons with storage capacity 2(min{m,n}) and guaranteed perfect bidirectional recall. The overall network design procedure is fully scalable in the sense that any number p=/<2(min{m,n}) of bidirectional associations can be implemented. The prototype patterns may be arbitrarily correlated. With respect to inference performance, it is shown that the Hamming attractive radius of each prototype reaches the maximum possible value. Simulation studies and comparisons illustrate and support these theoretical developments.
Authors:
Y Wu; D A Pados
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council     Volume:  11     ISSN:  1045-9227     ISO Abbreviation:  -     Publication Date:  2000  
Date Detail:
Created Date:  2008-02-05     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101211035     Medline TA:  IEEE Trans Neural Netw     Country:  United States    
Other Details:
Languages:  eng     Pagination:  859-66     Citation Subset:  -    
Affiliation:
Dept. of Electr. Eng., State Univ. of New York, Buffalo, NY.
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