Natural Computing

, Volume 7, Issue 4, pp 471–483 | Cite as

On the power of elementary features in spiking neural P systems

  • Marc García-Arnau
  • David Pérez
  • Alfonso Rodríguez-Patón
  • Petr Sosík
Article

Abstract

Since their first publication in 2006, spiking neural (SN) P systems have already attracted the attention of a lot of researchers. This might be owing to the fact that this abstract computing device follows basic principles known from spiking neural nets, but its implementation is discrete, using membrane computing background. Among the elementary properties which confer SN P systems their computational power one can count the unbounded fan-in (indegree) and fan-out (outdegree) of each “neuron”, synchronicity of the whole system, the possibility of delaying and/or removing spikes in neurons, the capability of evaluating arbitrary regular expressions in neurons in constant time and some others. In this paper we focus on the power of these elementary features. Particularly, we study the power of the model when some of these features are disabled. Rather surprisingly, even very restricted SN P systems keep their universal computational power. Certain important questions regarding this topic still remain open.

Keywords

P system Spiking neuron Membrane computing Normal form 

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Marc García-Arnau
    • 1
  • David Pérez
    • 1
  • Alfonso Rodríguez-Patón
    • 1
  • Petr Sosík
    • 1
    • 2
  1. 1.Departamento de Inteligencia Artificial, Facultad de InformáticaUniversidad Politécnica de Madrid – UPMBoadilla del MonteSpain
  2. 2.Institute of Computer ScienceSilesian UniversityOpavaCzech Republic

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