The stochastic loss of spikes in spiking neural P systems: Design and implementation of reliable arithmetic circuits

Zihan Xu, Matteo Cavaliere, Pei An, Sarma Vrudhula, Yu Cao

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Spiking neural P systems (in short, SN P systems) have been introduced as computing devices inspired by the structure and functioning of neural cells. The presence of unreliable components in SN P systems can be considered in many different aspects. In this paper we focus on two types of unreliability: the stochastic delays of the spiking rules and the stochastic loss of spikes. We propose the implementation of elementary SN P systems with DRAM-based CMOS circuits that are able to cope with these two forms of unreliability in an efficient way. The constructed bio-inspired circuits can be used to encode basic arithmetic modules.

Original languageEnglish (US)
Pages (from-to)183-200
Number of pages18
JournalFundamenta Informaticae
Volume134
Issue number1-2
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Algebra and Number Theory
  • Information Systems
  • Computational Theory and Mathematics

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