Computing with Spiking Neural P Systems: Traces and Small Universal Systems

  • Mihai Ionescu
  • Andrei Păun
  • Gheorghe Păun
  • Mario J. Pérez-Jiménez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4287)


Recently, the idea of spiking neurons and thus of computing by spiking was incorporated into membrane computing, and so-called spiking neural P systems (abbreviated SN P systems) were introduced. Very shortly, in these systems neurons linked by synapses communicate by exchanging identical signals (spikes), with the information encoded in the distance between consecutive spikes. Several ways of using such devices for computing were considered in a series of papers, with universality results obtained in the case of computing numbers, both in the generating and the accepting mode; generating, accepting, or processing strings or infinite sequences was also proved to be of interest.

In the present paper, after a short survey of central notions and results related to spiking neural P systems (including the case when SN P systems are used as string generators), we contribute to this area with two (types of) results: (i) we produce small universal spiking neural P systems (84 neurons are sufficient in the basic definition, but this number is decreased to 49 neurons if a slight generalization of spiking rules is adopted), and (ii) we investigate the possibility of generating a language by following the trace of a designated spike in its way through the neurons.


Spike Train Output Neuron Regular Language Empty String Register Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mihai Ionescu
    • 1
  • Andrei Păun
    • 2
    • 3
  • Gheorghe Păun
    • 4
    • 5
  • Mario J. Pérez-Jiménez
    • 5
  1. 1.Research Group on Mathematical LinguisticsUniversitat Rovira i VirgiliTarragonaSpain
  2. 2.Department of Computer ScienceLouisiana Tech UniversityRustonUSA
  3. 3.Faculdad de InformatícaUniversidad Politécnica de Madrid – UPMMadridSpain
  4. 4.Institute of Mathematics of the Romanian AcademyBucharestRomania
  5. 5.Department of Computer Science and AIUniversity of SevillaSevillaSpain

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