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A comparison of neural network models for pattern recognition

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1 Author(s)
C. H. Chen ; Dept. of Electr. & Comput. Eng., Southeastern Massachusetts Univ., North, MA, USA

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

Published in:

Pattern Recognition, 1990. Proceedings., 10th International Conference on  (Volume:ii )

Date of Conference:

16-21 Jun 1990