Sun, 04/26/2020 - 16:42 — mmartinez

Title | Dendrite P systems |

Publication Type | Journal Papers |

Year of Publication | 2020 |

Authors | Peng, H., Bao T., Luo X., Wang J., Song X., Riscos-Núñez A., & Pérez-Jiménez M. J. |

Journal Title | Neural Networks |

Volume | 127 |

Pages | 110 - 120 |

Abstract | It was recently found that dendrites are not just a passive channel. They can perform mixed computation of analog and digital signals, and therefore can be abstracted as information processors. Moreover, dendrites possess a feedback mechanism. Motivated by these computational and feedback characteristics, this article proposes a new variant of neural-like P systems, dendrite P (DeP) systems, where neurons simulate the computational function of dendrites and perform a firing–storing process instead of the storing–firing process in spiking neural P (SNP) systems. Moreover, the behavior of the neurons is characterized by dendrite rules that are abstracted by two characteristics of dendrites. Different from the usual firing rules in SNP systems, the firing of a dendrite rule is controlled by the states of the corresponding source neurons. Therefore, DeP systems can provide a collaborative control capability for neurons. We discuss the computational power of DeP systems. In particular, it is proven that DeP systems are Turing-universal number generating/accepting devices. Moreover, we construct a small universal DeP system consisting of 115 neurons for computing functions. |

Keywords | Computational power, Dendrite P systems, Neural-like P systems, P systems |

URL | http://www.sciencedirect.com/science/article/pii/S0893608020301349 |

ISSN Number | 0893-6080 |

DOI | https://doi.org/10.1016/j.neunet.2020.04.014 |