Multilayer feedforward networks are universal approximators

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Summary

It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.

Type
article
Published
1989-07-01
Cited by
24,597
References
25

Keywords

Feed forward, Feedforward neural network, Computer science, Class (philosophy), Function (biology)

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