Spiking Neural Network Based on Cusp Catastrophe Theory-Reference-Cited by-同舟云学术

Spiking Neural Network Based on Cusp Catastrophe Theory

Published:2019-08-28 Issue:3 Volume:44 Page:273-284
ISSN:2300-3405
Container-title:Foundations of Computing and Decision Sciences
language:en
Short-container-title:

Author:

Huderek Damian¹,Szczęsny Szymon¹,Rato Raul²

Affiliation:

1. Institute of Computing Science , Poznań University of Technology , Poznań

2. Universidade Nova de Lisboa , 2829-516 Caparica , Portugal

Abstract

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.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/fcds-2019-0014

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