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

Compensatory fuzzy neural networks (CFNN) without normalization, which can be trained with a backpropagation learning algorithm, are proposed as a pattern recognition technique for the intelligent detection of Doppler ultrasound waveforms of abnormal neonatal cerebral hemodynamics. Doppler ultrasoun...

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Detalles Bibliográficos
Publicado en:	IEEE Transactions on information technology in biomedicine 5, 3 (2001).
Autor principal:	Seker, H.
Formato:	Artículo
Lenguaje:	English
Materias:	Doppler ultrasound waveforms. Abnormal neonatal cerebral hemodynamics. Anterior cerebral arteries. Backpropagation learning algorithm. Blood-flow velocity. Compensatory fuzzy neural networks. Feature extraction. Full-term babies. Intelligent waveform detection. Intracranial pathology. Mature babies. Maximum-velocity waveforms. Normalization. Pattern recognition technique. Principal component analysis. Signal analysis.