RBF network

Network architecture

Given certain mild conditions on the shape of the activation function, RBF networks are universal approximators on a compact subset of ${\displaystyle \mathbb {R} ^{n}}$. This means that an RBF network with enough hidden neurons can approximate any continuous function on a closed, bounded set with arbitrary precision.