| A feedforward bidirectional associative memory. | |
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MedLine Citation:
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PMID: 18249814 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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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. |
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Authors:
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Y Wu; D A Pados |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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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:
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Created Date: 2008-02-05 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101211035 Medline TA: IEEE Trans Neural Netw Country: United States |
Other Details:
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Languages: eng Pagination: 859-66 Citation Subset: - |
Affiliation:
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Dept. of Electr. Eng., State Univ. of New York, Buffalo, NY. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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