Enregistré dans:
Détails bibliographiques
Auteur principal: María Elena Acevedo Mosqueda
Format: Artículo científico
Langue:en
Publié: Instituto Politécnico Nacional 2006
Sujets:
Accès en ligne:https://www.redalyc.org/articulo.oa?id=61501107
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866814352654336000
author María Elena Acevedo Mosqueda
author_facet María Elena Acevedo Mosqueda
contents Alpha-beta bidirectional associative memories María Elena Acevedo Mosqueda Cornelio Yáñez Márquez Computación Alpha correct recall Beta Associative Memories Bidirectional Associative Memories Most models of Bidirectional associative memories intend to achieve that all trained pattern correspond to stable states; however, this has not been possible. Also, none of the former models has been able to recall all the trained patterns. In this work we introduce a new model of bidirectional associative memory which is not iterative and has no stability problems. It is based on the Alpha-Beta associative memories. This model allows perfect recall of all trained patterns, with no ambiguity and no conditions. Applications of Alpha-Beta Bidirectional Associative Memories as fingerprint recognition and translator are presented. 2006 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61501107 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.10
format Artículo científico
id redalyc_61501107
language en
publishDate 2006
publisher Instituto Politécnico Nacional
spellingShingle Alpha-beta bidirectional associative memories
María Elena Acevedo Mosqueda
Computación
Alpha
correct recall
Beta Associative Memories
Bidirectional Associative Memories
Alpha-beta bidirectional associative memories María Elena Acevedo Mosqueda Cornelio Yáñez Márquez Computación Alpha correct recall Beta Associative Memories Bidirectional Associative Memories Most models of Bidirectional associative memories intend to achieve that all trained pattern correspond to stable states; however, this has not been possible. Also, none of the former models has been able to recall all the trained patterns. In this work we introduce a new model of bidirectional associative memory which is not iterative and has no stability problems. It is based on the Alpha-Beta associative memories. This model allows perfect recall of all trained patterns, with no ambiguity and no conditions. Applications of Alpha-Beta Bidirectional Associative Memories as fingerprint recognition and translator are presented. 2006 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61501107 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.10
title Alpha-beta bidirectional associative memories
topic Computación
Alpha
correct recall
Beta Associative Memories
Bidirectional Associative Memories
url https://www.redalyc.org/articulo.oa?id=61501107