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Published in:
2006 | OriginalPaper | Chapter
A Variational Formulation for the Multilayer Perceptron
Authors : Roberto Lopez, Eugenio Oñate
Published in: Artificial Neural Networks – ICANN 2006
Publisher: Springer Berlin Heidelberg
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In this work we present a theory of the multilayer perceptron from the perspective of functional analysis and variational calculus. Within this formulation, the learning problem for the multilayer perceptron lies in terms of finding a function which is an extremal for some functional. As we will see, a variational formulation for the multilayer perceptron provides a direct method for the solution of general variational problems, in any dimension and up to any degree of accuracy. In order to validate this technique we use a multilayer perceptron to solve some classical problems in the calculus of variations.