CONSTRUCTIVE APPROXIMATION BY GAUSSIAN NEURAL NETWORKS
Nahmwoo Hahm, Bum-Il Hong · Honam Mathematical Journal · 2012
In this paper, we discuss a constructive approximation by Gaussian neural networks. We show that it is possible to construct Gaussian neural networks with integer weights that approximate arbitrarily well for functions in $C_c(\mathbb{R}^s)$ . We demonstrate numerical experiments to support our theoretical results.