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dc.contributor.authorMorcego, Bernardo-
dc.contributor.authorFuertes Armengol, Jose Mª-
dc.contributor.authorCembrano, Gabriela-
dc.date.accessioned2010-12-17T13:23:27Z-
dc.date.available2010-12-17T13:23:27Z-
dc.date.issued2004-
dc.identifier.citationApplied Intelligence, 20(1): 37-45 (2004)-
dc.identifier.issn0924-669X-
dc.identifier.urihttp://hdl.handle.net/10261/30558-
dc.description.abstractThis paper presents a software tool suitable for dynamic system modelling. The models generated by this tool are modular neural networks. Each module behaves like a functional block and is connected to the other modules like in classical block diagrams. This tool allows the inclusion of a priori knowledge and, furthermore, to extract physical information from the models, once the system has learned. The modelling tool is capable of automatic model generation, parameter estimation and model validation.-
dc.language.isoeng-
dc.publisherKluwer Academic Publishers-
dc.relation.ispartofApplied Intelligence-
dc.rightsopenAccess-
dc.subjectDynamic system modelling-
dc.subjectModular neural networks-
dc.subjectSoftware tools-
dc.subjectKnowledge acquisition-
dc.subjectControl theory-
dc.titleMIGA, a software tool for nonlinear system modelling with modular neural networks-
dc.typeartículo-
dc.identifier.doi10.1023/B:APIN.0000011140.39317.ab-
dc.description.peerreviewedPeer Reviewed-
dc.relation.publisherversionhttp://dx.doi.org/10.1023/B:APIN.0000011140.39317.ab-
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