Neural networks applied to wireless communications
- Autores
- Stegmayer Machado, Georgina S.; Chiotti, Omar Juan Alfredo
- Año de publicación
- 2006
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- This paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a wireless transmitter.
IFIP International Conference on Artificial Intelligence in Theory and Practice - Neural Nets
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Neural nets
Wireless communication
time-delayed neural network (TDNN)
nonlinear elements - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23876
Ver los metadatos del registro completo
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Neural networks applied to wireless communicationsStegmayer Machado, Georgina S.Chiotti, Omar Juan AlfredoCiencias InformáticasNeural netsWireless communicationtime-delayed neural network (TDNN)nonlinear elementsThis paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a wireless transmitter.IFIP International Conference on Artificial Intelligence in Theory and Practice - Neural NetsRed de Universidades con Carreras en Informática (RedUNCI)2006-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23876enginfo:eu-repo/semantics/altIdentifier/isbn/0-387-34654-6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T09:39:00Zoai:sedici.unlp.edu.ar:10915/23876Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 09:39:00.494SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Neural networks applied to wireless communications |
title |
Neural networks applied to wireless communications |
spellingShingle |
Neural networks applied to wireless communications Stegmayer Machado, Georgina S. Ciencias Informáticas Neural nets Wireless communication time-delayed neural network (TDNN) nonlinear elements |
title_short |
Neural networks applied to wireless communications |
title_full |
Neural networks applied to wireless communications |
title_fullStr |
Neural networks applied to wireless communications |
title_full_unstemmed |
Neural networks applied to wireless communications |
title_sort |
Neural networks applied to wireless communications |
dc.creator.none.fl_str_mv |
Stegmayer Machado, Georgina S. Chiotti, Omar Juan Alfredo |
author |
Stegmayer Machado, Georgina S. |
author_facet |
Stegmayer Machado, Georgina S. Chiotti, Omar Juan Alfredo |
author_role |
author |
author2 |
Chiotti, Omar Juan Alfredo |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Neural nets Wireless communication time-delayed neural network (TDNN) nonlinear elements |
topic |
Ciencias Informáticas Neural nets Wireless communication time-delayed neural network (TDNN) nonlinear elements |
dc.description.none.fl_txt_mv |
This paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a wireless transmitter. IFIP International Conference on Artificial Intelligence in Theory and Practice - Neural Nets Red de Universidades con Carreras en Informática (RedUNCI) |
description |
This paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a wireless transmitter. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-08 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/23876 |
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http://sedici.unlp.edu.ar/handle/10915/23876 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/0-387-34654-6 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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application/pdf |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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score |
13.001348 |