On Structures and Behaviors of Spiking Neural P Systems and Petri Nets

  • Francis George C. Cabarle
  • Henry N. Adorna
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7762)

Abstract

In this work we investigate further the relationship between Petri nets and Spiking Neural P (SNP) systems: we consider SNP systems that have source (no incoming synapse) and sink (no outgoing synapse) neurons, and the initial configuration of the system is where only the source neuron has only one spike. We then route the initial single spike through the system to the sink neuron, using routing constructs. This type of SNP systems are similar to Petri nets, in particular to Workflow (WF) nets. We observe structural and behavioral properties of these nets for routing a single token can be simulated by SNP systems with source and sink neurons. Certain routing types such as AND-splits and OR-joins are ‘natural’ in SNP systems, but AND-joins and especially OR-splits seem to be more complex. Our results also suggest the possibility of analysing workflows using SNP systems.

Keywords

Membrane Computing Spiking Neural P systems routing joins splits Petri nets simulations safe Petri nets ordinary Petri nets workflow nets 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Francis George C. Cabarle
    • 1
  • Henry N. Adorna
    • 1
  1. 1.Algorithms & Complexity Lab Department of Computer ScienceUniversity of the Philippines DilimanQuezon CityPhilippines

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