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dc.contributor.authorDocheva, L.
dc.contributor.authorBekiarski, A.
dc.contributor.authorDochev, I.
dc.date.accessioned2016-03-24T06:43:45Z
dc.date.available2016-03-24T06:43:45Z
dc.date.issued2007-09cs
dc.identifier.citationRadioengineering. 2007, vol. 16, č. 3, s. 103-107. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/57309
dc.description.abstractThe analog neural networks have some very useful advantages in comparison with digital neural network, but recent implementation of discrete elements gives not the possibility for realizing completely these advantages. The reason of this is the great variations of discrete semiconductors characteristics. The VLSI implementation of neural network algorithm is a new direction of analog neural network developments and applications. Analog design can be very difficult because of need to compensate the variations in manufacturing, in temperature, etc. It is necessary to study the characteristics and effectiveness of this implementation. In this article the parameter variation influence over analog neural network behavior has been investigated.en
dc.formattextcs
dc.format.extent103-107cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2007/07_03_103_107.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectAnalog neural networksen
dc.subjectVLSIen
dc.subjectroboticen
dc.titleAnalysis of Analog Neural Network Model with CMOS Multipliersen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue3cs
dc.coverage.volume16cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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