Implementing size-optimal discrete neural networks require analog circuitry

Valeriu Beiu

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper starts by overviewing results dealing with the approximation capabilities of neural networks, as well as bounds on the size of threshold gate circuits. Based on a constructive solution for Kolmogorov's superpositions we will show that implementing Boolean functions can be done using neurons having an identity transfer function. Because in this case the size of the network is minimised, it follows that sizeoptimal solutions for implementing Boolean functions can be obtained using analog circuitry. Conclusions and several comments on the required precision are ending the paper.

Original languageEnglish
JournalEuropean Signal Processing Conference
Volume1998-January
Publication statusPublished - 1998
Externally publishedYes
Event9th European Signal Processing Conference, EUSIPCO 1998 - Island of Rhodes, Greece
Duration: Sep 8 1998Sep 11 1998

Keywords

  • Analog circuits
  • Kolmogorov's superpositions
  • Neural networks
  • Precision
  • Size
  • Threshold gate circuits

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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