Spiking neural network Based on cusp catastrophe Theory

Damian Huderek, Szymon Szczȩsny, Raul Rato

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
6 Downloads (Pure)

Abstract

This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer cMOS technologies and the current processing mode.

Original languageEnglish
Pages (from-to)273-284
Number of pages12
JournalFoundations of Computing and Decision Sciences
Volume44
Issue number3
DOIs
Publication statusPublished - 1 Sep 2019

Keywords

  • cusp catastrophe
  • decision support system
  • spiking neuron
  • XOR problem

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