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dc.contributor.authorChang, CJen_US
dc.contributor.authorLin, LFen_US
dc.contributor.authorLin, SYen_US
dc.contributor.authorCheng, RGen_US
dc.date.accessioned2014-12-08T15:42:35Z-
dc.date.available2014-12-08T15:42:35Z-
dc.date.issued2002-04-01en_US
dc.identifier.issn1350-2425en_US
dc.identifier.urihttp://dx.doi.org/10.1049/ip-com:20020031en_US
dc.identifier.urihttp://hdl.handle.net/11536/28904-
dc.description.abstractMultimedia networks need sophisticated and real-time connection admission control (CAC) not only to guarantee the required quality of service (QoS) for existing calls but also to enhance utilisation of systems. The power spectral density (PSD) of the input process contains correlation and burstiness characteristics of input traffic and possesses the additive property. Neural networks have been widely employed to deal with the traffic control problems in high-speed networks because of their self-learning capability. The authors propose a power-spectrum-based neural-net connection admission control (PNCAC) for multimedia networks. A decision hyperplane is constructed for the CAC using power spectrum parameters of traffic sources of connections, tinder the constraint of the QoS requirement. Simulation results show that the PNCAC method provides system utilisation and robustness superior to the conventional equivalent capacity CAC scheme and Hiramatsu's neural network CAC scheme, while meeting the QoS requirement.en_US
dc.language.isoen_USen_US
dc.titlePower-spectrum-based neural-net connection admission control for multimedia networksen_US
dc.typeArticleen_US
dc.identifier.doi10.1049/ip-com:20020031en_US
dc.identifier.journalIEE PROCEEDINGS-COMMUNICATIONSen_US
dc.citation.volume149en_US
dc.citation.issue2en_US
dc.citation.spage70en_US
dc.citation.epage76en_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.identifier.wosnumberWOS:000176540900002-
dc.citation.woscount2-
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