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Proceedings Paper

Attentive multidirectional associative memory with application to pattern association
Author(s): Heng-Ming Tai
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Paper Abstract

An attentive multidirectional hetero-associative memory network (AMAM) is proposed. The convergence and encoding strategies of AMAM are described. This network enables multiple associations, but with certain associations embedding more attention. This model is inspired by speculation about how associative learning and storage might occur in the nervous system. AMAM has much better error correcting capability and memory capacity than the multidirectional associative memory. Examples are illustrated to show the advantages of this model. In addition, we demonstrate and compare its recall ability for pattern recognition.

Paper Details

Date Published: 1 July 1992
PDF: 10 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140109
Show Author Affiliations
Heng-Ming Tai, Univ. of Tulsa (United States)

Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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