Cut Languages in Rational Bases

Abstrakt

We introduce a so-called cut language which contains the representations of numbers in a rational base that are less than a given threshold. The cut languages can be used to refine the analysis of neural net models between integer and rational weights. We prove a necessary and sufficient condition when a cut language is regular, which is based on the concept of a quasi-periodic power series. For a nonnegative base and digits, we achieve a dichotomy that a cut language is either regular or non-context-free while examples of regular and non-context-free cut languages are presented. We show that any cut language with a rational threshold is context-sensitive.