# NEURAL NETWORKS FOR OPTIMAL APPROXIMATION OF SMOOTH

@inproceedings{Mhaskar1996NEURALNF, title={NEURAL NETWORKS FOR OPTIMAL APPROXIMATION OF SMOOTH}, author={H. Mhaskar}, year={1996} }

We prove that neural networks with a single hidden layer are capable of providing an optimal order of approximation for functions assumed to possess a given number of derivatives, if the activation function evaluated by each principal element satisfies certain technical conditions. Under these conditions, it is also possible to construct networks that provide a geometric order of approximation for analytic target functions. The permissible activation functions include the squashing function (1… Expand

#### 7 Citations

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