Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/102442
Type: Artigo de evento
Title: Dynamic Transmission Rate Allocation In Packet Networks Using Recorrent Neural Networks Trained With Real Time Algorithm [alocação Dinâmica De Taxa De Transmissão Em Redes De Pacotes Utilizando Redes Neurais Recorrentes Treinadas Com Algoritmos Em Tempo Real]
Author: Teles Vieira F.H.
Lemos R.P.
Lee L.L.
Abstract: In this paper recurrent neural networks are considered to realize traffic prediction in computer network. The transmission rate that must be allocated in order to prevent byte losses and to get an efficient network use is estimated in real time. For such, recurrent neural networks were trained with real time learning algorithms: RTRL (Real Time Recurrent Learning) and extended Kalman filter. The algorithms are applied in the dynamic transmission rate allocation in a network link, verifying its efficiencies in the traffic prediction and control.
Editor: 
Rights: fechado
Identifier DOI: 10.1109/TLA.2003.1468622
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-77957792699&partnerID=40&md5=2b77b4b980b5422b657b68ae0d8d0564
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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