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

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...

Täydet tiedot

Bibliografiset tiedot
Julkaisussa:IEEE Transactions on information technology in biomedicine 5, 3 (2001).
Päätekijä: Seker, H.
Aineistotyyppi: Artikkeli
Kieli:English
Aiheet:
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.