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dc.creatorMitrović, Zoran
dc.date.accessioned2022-09-19T15:19:17Z
dc.date.available2022-09-19T15:19:17Z
dc.date.issued1995
dc.identifier.issn1210-0552
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/130
dc.description.abstractThe impossibility of the precise modeling of physical processes has demanded for the control of processes with unknown both by their structure and their parameters. High-quality control can be achieved only by a controlling system which will be able, during its work, to adjust its response according to the act of input and disturbing quantities. Neural networks appear to be one of these controlling systems. The possibility of their training can be considered using Lyapunov's stability theory. In this paper the preparation of the model of object (mechanical system) for neural networks control is pointed out.en
dc.publisherVSP Int Sci Publ, Zeist, Netherlands
dc.rightsrestrictedAccess
dc.sourceNeural Network World
dc.titleNeural networks applications in mechanical systemsen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage189
dc.citation.issue2
dc.citation.other5(2): 183-189
dc.citation.spage183
dc.citation.volume5
dc.identifier.rcubhttps://hdl.handle.net/21.15107/rcub_machinery_130
dc.identifier.scopus2-s2.0-0029201794
dc.type.versionpublishedVersion


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