Neural Networks Between Integer and Rational Weights

0465639 - ÚI 2017 CZ eng V - Research Report
Šíma, Jiří
Neural Networks Between Integer and Rational Weights.
Prague: ICS CAS, 2016. 8 s. Technical Report, V-1237.
R&D Projects: GA ČR GBP202/12/G061
Institutional support: RVO:67985807
Keywords : neural networks * analog unit * rational weight * cut languages * computational power
Subject RIV: IN - Informatics, Computer Science

The analysis of the computational power of neural networks with the weight parameters between integer and rational numbers is refined. We study an intermediate model of binary-state neural networks with integer weights, corresponding to finite automata, which is extended with an extra analog unit with rational weights, as already two additional analog units allow for Turing universality. We characterize the languages that are accepted by this model in terms of so-called cut languages which are combined in a certain way by usual string operations. We employ this characterization for proving that the languages accepted by neural networks with an analog unit are context-sensitive and we present an explicit example of such non-context-free languages. In addition, we formulate a sufficient condition when these networks accept only regular languages in terms of quasi-periodicity of parameters derived from their weights.
Permanent Link: http://hdl.handle.net/11104/0264100