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dc.contributor.authorPedreño Molina, Juan Luis 
dc.contributor.authorPinzolas Prado, Miguel 
dc.contributor.authorMonzó Cabrera, Juan 
dc.date.accessioned2010-12-14T13:23:45Z
dc.date.available2010-12-14T13:23:45Z
dc.date.issued2006
dc.identifier.citationPEDREÑO MOLINA, J.L., PINZOLAS PRADO, M., MONZÓ CABRERA, J. A new methodology for in-situ calibration of a neural network-based software sensor for S-parameter prediction in six-port reflectometers. Neurocomputing, Vol. 69 : 2451-2455, 2006. ISSN 0925-2312en_US
dc.description.abstractIn this work, a neural network-based software sensor is proposed for determining the reflection coefficient from measurements obtained by a six-port reflectometer. The proposed software sensor is able to cope with the nonlinearities and noise inherent to the measurement electronics, without needing additional calibration. To extract data for the calibration, a new method that allows in situ calibration is applied. Experimental evidence of the feasibility of the proposed method is given using a simulation testbench.en_US
dc.formatapplication/pdf
dc.language.isoengen_US
dc.publisherElsevier Scienceen_US
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.titleA new methodology for in-situ calibration of a neural network-based software sensor for S-parameter prediction in six-port reflectometersen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.subjectSix-port reflectometeren_US
dc.subjectS-parameter predictionen_US
dc.subjectSix_port calibrationen_US
dc.subjectNeural Networksen_US
dc.subjectMicrowave cavity measurementen_US
dc.subject.otherTeoría de la Señal y las Comunicacionesen_US
dc.identifier.urihttp://hdl.handle.net/10317/1473
dc.peerreviewen_US
dc.contributor.investgroupElectromagnetismo y Materiaen_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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