A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY

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A software to appreciate the performance of the Hopfield’s Neural Network (Associative Content-Addressable Memory) has been developed and applied to computer synthesized images. A rather small network has been created and applied to four sets of training-remembrances. The software allows the user to...

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Detalles Bibliográficos
Autor: Montenegro Joo, Javier
Formato: artículo
Fecha de Publicación:2006
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
OAI Identifier:oai:ojs.csi.unmsm:article/8614
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/8614
Nivel de acceso:acceso abierto
Materia:Cybernetics
Artificial Intelligence
Artificial Neural Networks
Hopfield
Pattern Recognition
Image Reconstruction
Ising
Magnetism.
Cibernética
Inteligencia Artificial
Redes de Neuronas artificiales
Reconocimiento de patrones
Reconstrucción de imágenes
Magnetismo.
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spelling A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORYA VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORYMontenegro Joo, JavierCyberneticsArtificial IntelligenceArtificial Neural NetworksHopfieldPattern RecognitionImage ReconstructionIsingMagnetism.CibernéticaInteligencia ArtificialRedes de Neuronas artificialesHopfieldReconocimiento de patronesReconstrucción de imágenesIsingMagnetismo.A software to appreciate the performance of the Hopfield’s Neural Network (Associative Content-Addressable Memory) has been developed and applied to computer synthesized images. A rather small network has been created and applied to four sets of training-remembrances. The software allows the user to become familiar with associative memory computer simulations, it also provides knowledge on the work of a neural net, hence this computer program may be used as a training tool (teach - learn) on neural networks. This software makes evident that a straightforward application of neural networks is in the field of pattern recognition and image reconstruction; it also serves as an introduction to more advanced and complex neural nets. This report is aimed at understanding the performance and potentials of a neural network, it may also foster the interest of students in cybernetics. The Hopfield neural network is important to physicists because it is closely related to the Ising Spin Glass model of magnetism, the learned memories in the net stand for the low energy states in the Ising model. A set of images (shown in this report) is included in the software, however it also accepts those made by the user.Con la finalidad de apreciar la ejecución de la red de neuronas de Hopfiled (memoria asociativa), se ha desarrollado un software y se ha aplicado a imágenes sintéticas. Una pequeña red de neuronas ha sido creada y aplicada a cuatro conjuntos de entrenamiento-remembranzas. El software permite al usuario familiarizarse con la simulación en computadoras de la memoria asociativa, también proporciona conocimientos sobre la operación de una red de neuronas, de modo que el software puede ser usado como una herramienta para enseñar-aprender redes de neuronas. El software hace evidente que una aplicación directa de las redes de neuronas, es el reconocimiento de patrones y la reconstrucción de imágenes, también sirve como una introducción a redes mas avanzadas y complejas. Este reporte apunta a entender la ejecución y potencialidades de una red de neuronas, puede también estimular el interés de los estudiantes en la Cibernética. La red de Hopfield es importante para los físicos, pues está muy relacionada al modelo de Vidrios de Spin de Ising del magnetismo, las memorias que aprende la red, equivalen a los estados de mínima energía en el modelo de Ising. El programa incluye un conjunto de imágenes (mostrado en este reporte), sin embargo, también acepta aquellas suministradas por el usuario.Universidad Nacional Mayor de San Marcos2006-07-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/861410.15381/rif.v9i01.8614Revista de Investigación de Física; Vol. 9 No. 01 (2006); 36-45Revista de Investigación de Física; Vol. 9 Núm. 01 (2006); 36-451728-29771605-7724reponame:Revistas - Universidad Nacional Mayor de San Marcosinstname:Universidad Nacional Mayor de San Marcosinstacron:UNMSMspahttps://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/8614/7458Derechos de autor 2006 Javier Montenegro Joohttps://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessoai:ojs.csi.unmsm:article/86142020-09-02T20:09:28Z
dc.title.none.fl_str_mv A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
title A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
spellingShingle A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
Montenegro Joo, Javier
Cybernetics
Artificial Intelligence
Artificial Neural Networks
Hopfield
Pattern Recognition
Image Reconstruction
Ising
Magnetism.
Cibernética
Inteligencia Artificial
Redes de Neuronas artificiales
Hopfield
Reconocimiento de patrones
Reconstrucción de imágenes
Ising
Magnetismo.
title_short A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
title_full A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
title_fullStr A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
title_full_unstemmed A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
title_sort A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
dc.creator.none.fl_str_mv Montenegro Joo, Javier
author Montenegro Joo, Javier
author_facet Montenegro Joo, Javier
author_role author
dc.subject.none.fl_str_mv Cybernetics
Artificial Intelligence
Artificial Neural Networks
Hopfield
Pattern Recognition
Image Reconstruction
Ising
Magnetism.
Cibernética
Inteligencia Artificial
Redes de Neuronas artificiales
Hopfield
Reconocimiento de patrones
Reconstrucción de imágenes
Ising
Magnetismo.
topic Cybernetics
Artificial Intelligence
Artificial Neural Networks
Hopfield
Pattern Recognition
Image Reconstruction
Ising
Magnetism.
Cibernética
Inteligencia Artificial
Redes de Neuronas artificiales
Hopfield
Reconocimiento de patrones
Reconstrucción de imágenes
Ising
Magnetismo.
description A software to appreciate the performance of the Hopfield’s Neural Network (Associative Content-Addressable Memory) has been developed and applied to computer synthesized images. A rather small network has been created and applied to four sets of training-remembrances. The software allows the user to become familiar with associative memory computer simulations, it also provides knowledge on the work of a neural net, hence this computer program may be used as a training tool (teach - learn) on neural networks. This software makes evident that a straightforward application of neural networks is in the field of pattern recognition and image reconstruction; it also serves as an introduction to more advanced and complex neural nets. This report is aimed at understanding the performance and potentials of a neural network, it may also foster the interest of students in cybernetics. The Hopfield neural network is important to physicists because it is closely related to the Ising Spin Glass model of magnetism, the learned memories in the net stand for the low energy states in the Ising model. A set of images (shown in this report) is included in the software, however it also accepts those made by the user.
publishDate 2006
dc.date.none.fl_str_mv 2006-07-17
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/8614
10.15381/rif.v9i01.8614
url https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/8614
identifier_str_mv 10.15381/rif.v9i01.8614
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/8614/7458
dc.rights.none.fl_str_mv Derechos de autor 2006 Javier Montenegro Joo
https://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2006 Javier Montenegro Joo
https://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional Mayor de San Marcos
publisher.none.fl_str_mv Universidad Nacional Mayor de San Marcos
dc.source.none.fl_str_mv Revista de Investigación de Física; Vol. 9 No. 01 (2006); 36-45
Revista de Investigación de Física; Vol. 9 Núm. 01 (2006); 36-45
1728-2977
1605-7724
reponame:Revistas - Universidad Nacional Mayor de San Marcos
instname:Universidad Nacional Mayor de San Marcos
instacron:UNMSM
instname_str Universidad Nacional Mayor de San Marcos
instacron_str UNMSM
institution UNMSM
reponame_str Revistas - Universidad Nacional Mayor de San Marcos
collection Revistas - Universidad Nacional Mayor de San Marcos
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 13.987332
A VIRTUAL LAB TO VISUALIZE THE PERFORMANCE OF THE HOPFIELD’S NEURAL NETWORK FOR ASSOCIATIVE CONTENT-ADDRESSABLE MEMORY
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).

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