A three layer neural network can represent any multivariate function

In 1987, Hecht-Nielsen showed that any continuous multivariate function could 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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