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In this paper we prove that any affine function defined on a d-simplex in Rd can be uniformly approximated by a single-layer neural network having only two neurons irrespective of d. The weights of this network are obtained in a closed analytical form, without training. This fact gives a correspondence rule that allows to transform mathematical approximants based on piecewise affine functions, into...
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