Fast generating algorithm for a general
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R. Zollner; H.J. Schmitz; F. WΓΌnsch; U. Krey
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Article
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1992
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Elsevier Science
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English
β 513 KB
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