IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 Adaptive Bam for Pattern Classification Como, Italy July 24-July 27 ISBN: 0-7695-0619-4
A new method for the synthesis of a neural network with BAM features, based on the ART structure, is presented. Intended for Pattern Classification, it contains a new procedure for the correct usage of the Relation Matrix, and avoids the inherent defects of the BAM and its misclassifications with appropriate action on the threshold of the neurons of the ART layers. The results clearly indicate that this method leads to a good improvement of the performance achievable in a BAM, with a 0% error rate found in a test on the well-known NIST #19 character database.
Citation:
Francisco J. López-Aligué, I. Alvarez Troncoso, I. Acevedo Sotoca, C. J. García Orellana, M. Macías Macías, H. González Velasco, "Adaptive Bam for Pattern Classification," ijcnn, vol. 5, pp.5529, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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