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Fast generating algorithm for a general 3-layer perceptron

URN to cite this document:
urn:nbn:de:bvb:355-epub-268044
Zollner, R. ; Schmitz, H. J. ; Wünsch, Friedrich ; Krey, Uwe
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Date of publication of this fulltext: 23 Nov 2012 14:03


Abstract

A fast iterative algorithm is proposed for the construction and the learning of a neural net achieving a classification task, with an input layer, one intermediate layer, and an output layer The network is able to learn an arbitrary training set. The algorithm does not depend on a special learning scheme (e.g., the couplings can be determined by modified Hebbian prescriptions or by more complex ...

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