Abstract
We present the theory and some results of a new algorithm for Artificial Neural Nets which behaves well on complex data sets. The algorithm uses adaptive quadratic forms as discriminant functions and is very fast compared with Back-Propagation - improvements of four orders of magnitude have been obtained.
Original language | English |
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Pages (from-to) | 325-329 |
Journal | Pattern Recognition Letters |
Volume | 13 |
Issue number | May, 1992 |
DOIs | |
Publication status | Published - 1992 |