Proofs of strong forms of the Bovdi--Geche universality conjecture and a complex analogue

We prove two universality theorems for neural networks consisting of a single neuron. First we prove a strong form of the Bovdi--Geche universality conjecture on neurons over finite fields, where the activation function is a certain modification of the discrete logarithm, using the Weil bound on multiplicative character sums over finite fields. Then we show a generalisation of Aizenberg's universality theorem for complex binary neurons with a weight vector independent of the target function, positively answering another question in the literature. The proof of the latter uses an equidistribution theorem for the dilates of certain maps into tori.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.35645
Primary Topic
Neural Networks and Applications
Type
preprint
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preprint

Proofs of strong forms of the Bovdi--Geche universality conjecture and a complex analogue

Victor Bovdi, Ambrus Pál
arXiv (Cornell University)
Neural Networks and Applications
preprint

Proofs of strong forms of the Bovdi--Geche universality conjecture and a complex analogue

Victor Bovdi, Ambrus Pál
preprint en

Abstract

We prove two universality theorems for neural networks consisting of a single neuron. First we prove a strong form of the Bovdi--Geche universality conjecture on neurons over finite fields, where the activation function is a certain modification of the discrete logarithm, using the Weil bound on multiplicative character sums over finite fields. Then we show a generalisation of Aizenberg's universality theorem for complex binary neurons with a weight vector independent of the target function, positively answering another question in the literature. The proof of the latter uses an equidistribution theorem for the dilates of certain maps into tori.

arXiv (Cornell University)
Neural Networks and Applications
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