Extraction of topological features from communication network topological patterns using self-organizing feature maps

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dc.creatorAli, W.
dc.creatorMondragon, R. J.
dc.creatorAlavi, F.
dc.date2004-04-21
dc.date2004-04-22
dc.date.accessioned2026-07-07T03:21:08Z
dc.date.available2026-07-07T03:21:08Z
dc.descriptionDifferent classes of communication network topologies and their representation in the form of adjacency matrix and its eigenvalues are presented. A self-organizing feature map neural network is used to map different classes of communication network topological patterns. The neural network simulation results are reported.
dc.description8 Pages, 5 figures, To be appeared in IEE Electronics Letter Journal
dc.identifierhttps://arxiv.org/abs/cs/0404042
dc.identifierhttp://arxiv.org/abs/cs/0404042
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32083
dc.subjectNeural and Evolutionary Computing
dc.subjectComputer Vision and Pattern Recognition
dc.subjectC.2; I.5
dc.titleExtraction of topological features from communication network topological patterns using self-organizing feature maps
dc.typetext

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