A Compiler and Simulator for Partial Recursive Functions over Neural Networks

Abstract

Abstract. In [6] and [8] it was shown that Artificial Recurrent Neural Networks have the same computing power as Turing machines. A Turing machine can be programmed in a proper highlevel language -the language of partial recursive functions. In this paper we present the implementation of a compiler that directly translates high-level Turing machine programs to Artificial Recursive Neural Networks. The application contains a simulator that can be used to test the resulting networks. We also argue that these experiments provide clues to develop procedures for automatic synthesis of Neural Networks from high-level descriptions.