• DOI:10.1016/S0893-6080(05)80131-5
Corpus ID: 206089312

Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function

@inproceedings{Leshno1993MultilayerFN,
  title={Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function},
  author={M. Leshno and Vladimir Ya. Lin and A. Pinkus and S. Schocken},
  booktitle={Neural Networks},
  year={1993}
}

M. Leshno, Vladimir Ya. Lin, +1 author S. Schocken

Published in Neural Networks 1993

Mathematics, Computer Science

Several researchers characterized the activation functions under which multilayer feedforwardnetworks can act as universal approximators. We show that all the characterizationsthat were reported thus far in the literature ark special cases of the following general result:a standard multilayer feedforward network can approximate any continuous functionto any degree of accuracy if and only if the network's activation functions are not polynomial.We also emphasize the important role of the… CONTINUE READING

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