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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CITATION STYLE
Chen, C. H. (1990). A comparison of neural network models for pattern recognition. In Proceedings - International Conference on Pattern Recognition (Vol. 2, pp. 45–46). Publ by IEEE. https://doi.org/10.1109/icpr.1990.119327
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