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Spiking Neural P Systems with Polarizations and Rules on Synapses

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  • Suxia Jiang
  • Jihui Fan
  • Yijun Liu
  • Yanfeng Wang
  • Fei Xu

Abstract

Spiking neural P systems are a class of computation models inspired by the biological neural systems, where spikes and spiking rules are in neurons. In this work, we propose a variant of spiking neural P systems, called spiking neural P systems with polarizations and rules on synapses (PSNRS P systems), where spiking rules are placed on synapses and neurons are associated with polarizations used to control the application of such spiking rules. The computation power of PSNRS P systems is investigated. It is proven that PSNRS P systems are Turing universal, both as number generating and accepting devices. Furthermore, a universal PSNRS P system with 151 neurons for computing any Turing computable functions is given. Compared with the case of SN P systems with polarizations but without spiking rules in neurons, less number of neurons are used to construct a universal PSNRS P system.

Suggested Citation

  • Suxia Jiang & Jihui Fan & Yijun Liu & Yanfeng Wang & Fei Xu, 2020. "Spiking Neural P Systems with Polarizations and Rules on Synapses," Complexity, Hindawi, vol. 2020, pages 1-12, July.
    • Handle: RePEc:hin:complx:8742308
    DOI: 10.1155/2020/8742308
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    Cited by:

    1. Suxia Jiang & Tao Liang & Bowen Xu & Zhichao Shen & Xiaoliang Zhu & Yanfeng Wang, 2022. "Cell-like P Systems with Channel States and Synchronization Rule," Mathematics, MDPI, vol. 11(1), pages 1-14, December.

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