Improving energy consumption of pattern recognition by combining processor-centric and bio-inspired considerations

Yathindu R. Hettiarachchige, Asad I. Khan, Jan Carlo Barca

Research output: Contribution to journalArticle

Abstract

This paper investigates aspects of bio-inspired models that help create more energy efficient methods in pattern recognition. A comparison between a biologically plausible pattern recognition approach and a purely computer based (algorithmic) approach yielded three main findings. Firstly, the occurrence of low-complexity parallel sub-processes within the bio-inspired approach allows higher energy efficiency by relaxing the requirement of having faster processors. Secondly, the bio-inspired approach takes advantage of numerous computationally inexpensive sub-processes that will scale better in massively parallel environments, such as neuromorphic computers, thus providing comparable speed. Finally, it is far more easier to adapt across a range of application domains than its algorithmic counterpart.

LanguageEnglish
Pages54-63
Number of pages10
JournalBiologically Inspired Cognitive Architectures
Volume23
DOIs
StatePublished - 1 Jan 2018

Keywords

  • Bio-inspired
  • Distributed pattern recognition
  • Parallelism
  • Strong AI

Cite this

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