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dc.contributor.authorGancev, Stojanchoen_US
dc.contributor.authorKulakov, Andreaen_US
dc.date.accessioned2022-11-01T12:44:55Z-
dc.date.available2022-11-01T12:44:55Z-
dc.date.issued2009-10-29-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/24051-
dc.description.abstractThe paper deals with the problem of faster optimal coverage of a Growing Neural Gas algorithm for random signals appearing with non-stationary distributions. A modification of the algorithm that successfully solves this problem will be presented with simulations in a 2-D environment and statistical results that will show its efficiency. A comparison with a previous solution for the same problem using so called Utility measure will be also given.en_US
dc.publisherIEEEen_US
dc.subjectgrowing neural gas; faster convergence; fuzzy algorithm; non-stationary distribution;en_US
dc.titleModified growing neural gas algorithm for faster convergence on signal distribution sudden changeen_US
dc.typeProceedingsen_US
dc.relation.conference2009 XXII International Symposium on Information, Communication and Automation Technologiesen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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