A generalized seasonal persistent model for video traffic

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RECERCAT Home > Universitat Politècnica de Catalunya > Documents de recerca > View document

To access the full text documents, please follow this link: http://hdl.handle.net/2117/6379

dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica
dc.contributor	Universitat Politècnica de Catalunya. BAMPLA - Disseny i Avaluació de Xarxes i Serveis de Banda Ampla
dc.contributor.author	Zuraniewski, Piotr
dc.contributor.author	Rincón Rivera, David
dc.date	2009-09
dc.identifier.citation	978-3-642-03699-6
dc.identifier.uri	http://hdl.handle.net/2117/6379
dc.language.iso	eng
dc.publisher	Springer Berlin / Heidelberg
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subject	Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Modelització estadística
dc.subject	Stochastic modeling
dc.subject	Imatges -- Processament
dc.subject	Vídeo
dc.subject	Càlcul estocàstic
dc.title	A generalized seasonal persistent model for video traffic
dc.type	info:eu-repo/semantics/draft
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	Video tra±c generated with modern codecs is known to possess a complex statistical structure that includes short memory, long memory, and seasonal components. We propose a k-factor Generalized Autoregressive Moving Average (k-GARMA) process as a versatile model for video tra±c. We provide a wavelet-based approximate Maximum Likelihood Estimator for such a process, together with some results obtained with H.263 and MPEG-2 video traces.

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