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Investigating the suitability of FPAAs for evolved hardware spiking neural networks

  • Patrick Rocke
  • , Brian McGinley
  • , John Maher
  • , Fearghal Morgan
  • , Jim Harkin

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

15 Citations (Scopus)

Abstract

This paper investigates the use of a network of cascaded Field Programmable Analogue Arrays (FPAAs) to implement an evolved, analogue, Spiking Neural Network (SNN) pole balance controller. The SNN hardware platform interfaces to a simulated pole balancing model for evaluation. Performance of the evolved analogue hardware controller is compared to that of a software-based SNN controller. The evolved hardware network displays an improved tolerance to changing environments compared with networks evolved solely in simulation. The paper goes on to discuss the suitability of low density FPAA devices for analogue-centric hardware neural network platforms. It concludes by outlining some possible directions which address the observed limitations of using FPAAs for ANNs.

Original languageEnglish
Title of host publicationEvolvable Systems
Subtitle of host publicationFrom Biology to Hardware - 8th International Conference, ICES 2008, Proceedings
PublisherSpringer-Verlag
Pages118-129
Number of pages12
ISBN (Print)3540858563, 9783540858560
DOIs
Publication statusPublished - 2008
Event8th International Conference on Evolvable Systems: From Biology to Hardware, ICES 2008 - Prague, Czech Republic
Duration: 21 Sep 200824 Sep 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5216 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Evolvable Systems: From Biology to Hardware, ICES 2008
Country/TerritoryCzech Republic
CityPrague
Period21/09/0824/09/08

Keywords

  • Analogue neural networks
  • FPAA hardware evolution
  • Spiking neural networks

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