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dc.contributor.authorHardalac, Firat
dc.date.accessioned2020-06-25T17:44:47Z
dc.date.available2020-06-25T17:44:47Z
dc.date.issued2008
dc.identifier.citationclosedAccessen_US
dc.identifier.issn0148-5598
dc.identifier.urihttps://doi.org10.1007/s10916-007-9116-6
dc.identifier.urihttps://hdl.handle.net/20.500.12587/4196
dc.descriptionWOS: 000253896600007en_US
dc.descriptionPubMed: 18461817en_US
dc.description.abstractTranscranial Doppler signals recorded from cerebral vessels of 110 patients were transferred to a personal computer by using a 16 bit sound card. Spectral analyses of Transcranial Doppler signals were performed for determining the Multi Layer Perceptron (MLP) neural network and neuro Ankara-fuzzy system inputs. In order to do a good interpretation and rapid diagnosis, FFT parameters of Transcranial Doppler signals classified using MLP neural network and neuro-fuzzy system. Our findings demonstrated that 92% correct classification rate was obtained from MLP neural network, and 86% correct classification rate was obtained from neuro-fuzzy system.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.isversionof10.1007/s10916-007-9116-6en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMulti Layer Perceptron (MLP)en_US
dc.subjectneuro-fuzzy classification (NEFCLASS)en_US
dc.subjecttranscranial Doppleren_US
dc.subjectfast Fourier transform (FFT) methoden_US
dc.titleComparison of MLP neural network and neuro-fuzzy system in transcranial doppler signals recorded from the cerebral vesselsen_US
dc.typearticleen_US
dc.identifier.volume32en_US
dc.identifier.issue2en_US
dc.identifier.startpage137en_US
dc.identifier.endpage145en_US
dc.relation.journalJournal Of Medical Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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