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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14384
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| Title: | MULTILAYER FEEDFORWARD NETWORKS WITH NON-POLYNOMIAL ACTIVATION FUNCTIONS
CAN APPROXIMATE ANY FUNCTION |
| Authors: | Leshno, Moshe
Schocken, Shimon |
| Keywords: | Multilayer feedforward networks
Activation functions
role of threshold
Universal approximation capabilities
LP(μ) approximation |
| Issue Date: | Sep-1991 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-91-26 |
| Abstract: | Several researchers characterized the activation functions under which
multilayer feedforward networks can act as universal approximators. We
show that all the characterizations that were reported thus far in the
literature ark special cases of the following general result: a standard
multilayer feedforward network can approximate any continuous function
to any degree of accuracy if and only if the network's activation
functions are not polynomial. We also emphasize the important role of
the threshold, asserting that without it the last theorem doesn't hold. |
| URI: | http://hdl.handle.net/2451/14384 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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