Neural Network Clustering Based on Distances Between Objects

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dc.creatorLitinskii, Leonid B.
dc.creatorRomanov, Dmitry E.
dc.date2006-08-29
dc.date.accessioned2026-07-07T07:20:07Z
dc.date.available2026-07-07T07:20:07Z
dc.descriptionWe present an algorithm of clustering of many-dimensional objects, where only the distances between objects are used. Centers of classes are found with the aid of neuron-like procedure with lateral inhibition. The result of clustering does not depend on starting conditions. Our algorithm makes it possible to give an idea about classes that really exist in the empirical data. The results of computer simulations are presented.
dc.description7 pages,4 figures, presentation on ICANN (Athens, Greece, 2006)
dc.identifierhttps://arxiv.org/abs/cs/0608115
dc.identifierhttp://arxiv.org/abs/cs/0608115
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/114862
dc.subjectComputer Vision and Pattern Recognition
dc.subjectNeural and Evolutionary Computing
dc.titleNeural Network Clustering Based on Distances Between Objects
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