A comparison of neural network models for pattern recognition
1990 Proceedings 10th International Conference on Pattern Recognition (1990)
- ISBN: 0818620625
- DOI: 10.1109/ICPR.1990.119327
Available from ieeexplore.ieee.org
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Abstract
A brief survey of the existing neural network models for signal/image processing and pattern recognition is presented. A comparison of the back-propagation algorithm for multilayer perception and an adaptive sample set construction procedure offered by Nestor's restricted Coulomb energy network is presented. A performance comparison with real data for ultrasonic nondestructive evaluation of materials is presented
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