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dc.contributor.authorPuşcaşu, Gheorghe
dc.contributor.authorCodreş, Bogdan
dc.contributor.authorStancu, Alexandru
dc.date.accessioned2016-01-13T12:54:46Z
dc.date.available2016-01-13T12:54:46Z
dc.date.issued2006
dc.identifier.urihttp://10.11.10.50/xmlui/handle/123456789/3873
dc.descriptionThe Annals of "Dunarea de Jos" University of Galatien_US
dc.description.abstractIn the past years utilization of neural networks took a distinct ampleness because of the following properties: distributed representation of information, capacity of generalization in case of uncontained situation in training data set, tolerance to noise, resistance to partial destruction, parallel processing. Another major advantage of neural networks is that they allow us to obtain the model of the investigated system, systems that is not necessarily to be linear. In fact, the true value of neural networks is seen in the case of identification and control of nonlinear systems. In this paper there are presented some identification techniques using neural networks.en_US
dc.language.isoenen_US
dc.publisher"Dunarea de Jos" University of Galatien_US
dc.subjectidentificationen_US
dc.subjectrecurrent neural networksen_US
dc.subjecttrainingen_US
dc.titleIdentification of the Non-Linear Systems Using Internal Recurrent Neural Networksen_US
dc.typeArticleen_US


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