Asynchronous Spiking Neural P Systems with Structural Plasticity

  • Francis George C. Cabarle
  • Henry N. Adorna
  • Mario J. Pérez-Jiménez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9252)

Abstract

Spiking neural P (in short, SNP) systems are computing devices inspired by biological spiking neurons. In this work we consider SNP systems with structural plasticity (in short, SNPSP systems) working in the asynchronous (in short, asyn mode). SNPSP systems represent a class of SNP systems that have dynamic synapses, i.e. neurons can use plasticity rules to create or remove synapses. We prove that for asyn mode, bounded SNPSP systems (where any neuron produces at most one spike each step) are not universal, while unbounded SNPSP systems with weighted synapses (a weight associated with each synapse allows a neuron to produce more than one spike each step) are universal. The latter systems are similar to SNP systems with extended rules in asyn mode (known to be universal) while the former are similar to SNP systems with standard rules only in asyn mode (conjectured not to be universal). Our results thus provide support to the conjecture of the still open problem.

Keywords

Membrane computing Spiking neural P systems Structural plasticity Asynchronous systems Turing universality 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Francis George C. Cabarle
    • 1
  • Henry N. Adorna
    • 1
  • Mario J. Pérez-Jiménez
    • 2
  1. 1.Algorithms and Complexity Lab, Department of Computer ScienceUniversity of the Philippines DilimanQuezon CityPhilippines
  2. 2.Department of Computer Science and AIUniversity of SevillaSevillaSpain

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