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A three layer neural network can represent any multivariate function

Published 5 Dec 2020 in cs.LG, math.FA, and stat.ML | (2012.03016v2)

Abstract: In 1987, Hecht-Nielsen showed that any continuous multivariate function can be implemented by a certain type three-layer neural network. This result was very much discussed in neural network literature. In this paper we prove that not only continuous functions but also all discontinuous functions can be implemented by such neural networks.

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