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Buried Tag Identification with a new RBF Classifier

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3 Author(s)
Beheim, L. ; CReSTIC, Univ. of Reims Champagne-Ardenne ; Zitouni, A. ; Belloir, F.

This article presents a new neural classifier based on an RBF network. This classifier increases relatively the recognition rate while decreasing remarkably the number of hidden layer neurons. It is very general RBF classifier, very simple, not requiring any adjustment parameter, and presenting an excellent ratio performances/neurons number. A comparative study of its performances is presented and illustrated by examples on real databases

Published in:

Signal Processing Symposium, 2006. NORSIG 2006. Proceedings of the 7th Nordic

Date of Conference:

June 2006