Compensatory fuzzy neural networks based intelligent detection of abnormal neonatal cerebral Doppler ultrasound waveforms

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dc.contributor.author Seker, H. en
dc.contributor.author Aydin, N. en
dc.contributor.author Evans, D. H. en
dc.contributor.author Yazgan, E. en
dc.date.accessioned 2008-11-24T13:24:18Z
dc.date.available 2008-11-24T13:24:18Z
dc.date.issued 2001-09-01 en
dc.identifier.citation Seker, H., et al. (2001) Compensatory fuzzy neural networks based intelligent detection of abnormal neonatal cerebral Doppler ultrasound waveforms. IEEE Transactions on Information Technology in Biomedicine, 5(3), pp. 187-194.
dc.identifier.issn 1089-7771 en
dc.identifier.uri http://hdl.handle.net/2086/200
dc.description This paper presents further development of a compensatory fuzzy model whereby a new set of compensatory factors were defined and a non-normalised version of the model was introduced. The new model was shown to be comparable in many ways with other classical methods such as artificial neural networks and to yield better results. It was also the first to discuss application of the old and enhanced versions of the models in biomedicine. The paper has been widely accepted by the research community whose focus is on the compensatory fuzzy system with/without biomedical application. en
dc.language.iso en en
dc.publisher IEEE Transactions on Information Technology in Biomedicine en
dc.subject RAE 2008
dc.subject UoA 23 Computer Science and Informatics
dc.subject backpropagation learning
dc.subject blood-flow velocity
dc.subject Doppler ultrasound
dc.subject fuzzy neural networks
dc.subject neonatal cerebral arteries
dc.subject pattern recognition
dc.subject principal component analysis
dc.title Compensatory fuzzy neural networks based intelligent detection of abnormal neonatal cerebral Doppler ultrasound waveforms en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.1109/4233.945289 en
dc.researchgroup Centre for Computational Intelligence
dc.researchgroup Pharmaceutical Technologies


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