• DocumentCode
    3611446
  • Title

    On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses

  • Author

    Tao Song ; Jinbang Xu ; Linqiang Pan

  • Author_Institution
    Coll. of Comput. & Commun. Eng., China Univ. of Pet., Qingdao, China
  • Volume
    14
  • Issue
    8
  • fYear
    2015
  • Firstpage
    960
  • Lastpage
    966
  • Abstract
    Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neurons (using extended spiking rules) or with 39 neurons (using standard spiking rules) is Turing universal. In this work, this number is improved to 6. Specifically, we construct a Turing universal spiking neural P system with rules on synapses having 6 neurons, which can generate any set of Turing computable natural numbers. As well, it is obtained that spiking neural P system with rules on synapses having less than two neurons are not Turing universal: i) such systems having one neuron can characterize the family of finite sets of natural numbers; ii) the family of sets of numbers generated by the systems having two neurons is included in the family of semi-linear sets of natural numbers.
  • Keywords
    medical computing; neurophysiology; Turing computable natural numbers; extended spiking rules; finite sets; rules-on-synapses; semilinear sets; spiking neural P systems; spiking-forgetting rules; Biological neural networks; Computational modeling; Fault diagnosis; Nanobioscience; Neurons; Registers; Standards; Bio-inspired computing; membrane computing; spiking neural P system; synapse; universality;
  • fLanguage
    English
  • Journal_Title
    NanoBioscience, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-1241
  • Type

    jour

  • DOI
    10.1109/TNB.2015.2503603
  • Filename
    7337432