### Abstract

The authors show that a multiple-input, single-output, single-hidden-layer feedforward network with (known) hardwired connections from input to hidden layer, monotone squashing at the hidden layer and no squashing at the output embeds as a special case a so-called Fourier network, which yields a Fourier series approximation properties of Fourier series representations. In particular, approximation to any desired accuracy of any square integrable function can be achieved by such a network, using sufficiently many hidden units. In this sense, such networks do not make avoidable mistakes.

Original language | English (US) |
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Pages | 657-664 |

Number of pages | 8 |

State | Published - Dec 1 1988 |

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### All Science Journal Classification (ASJC) codes

- Engineering(all)

### Cite this

*There exists a neural network that does not make avoidable mistakes*. 657-664.

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**There exists a neural network that does not make avoidable mistakes.** / Gallant, Andrew Ronald; White, Halbert.

Research output: Contribution to conference › Paper

TY - CONF

T1 - There exists a neural network that does not make avoidable mistakes

AU - Gallant, Andrew Ronald

AU - White, Halbert

PY - 1988/12/1

Y1 - 1988/12/1

N2 - The authors show that a multiple-input, single-output, single-hidden-layer feedforward network with (known) hardwired connections from input to hidden layer, monotone squashing at the hidden layer and no squashing at the output embeds as a special case a so-called Fourier network, which yields a Fourier series approximation properties of Fourier series representations. In particular, approximation to any desired accuracy of any square integrable function can be achieved by such a network, using sufficiently many hidden units. In this sense, such networks do not make avoidable mistakes.

AB - The authors show that a multiple-input, single-output, single-hidden-layer feedforward network with (known) hardwired connections from input to hidden layer, monotone squashing at the hidden layer and no squashing at the output embeds as a special case a so-called Fourier network, which yields a Fourier series approximation properties of Fourier series representations. In particular, approximation to any desired accuracy of any square integrable function can be achieved by such a network, using sufficiently many hidden units. In this sense, such networks do not make avoidable mistakes.

UR - http://www.scopus.com/inward/record.url?scp=0024124325&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024124325&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0024124325

SP - 657

EP - 664

ER -