Literature DB >> 32339806

Dendrite P systems.

Hong Peng1, Tingting Bao2, Xiaohui Luo2, Jun Wang3, Xiaoxiao Song4, Agustín Riscos-Núñez5, Mario J Pérez-Jiménez5.   

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.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Keywords:  Computational power; Dendrite P systems; Neural-like P systems; P systems

Mesh:

Year:  2020        PMID: 32339806     DOI: 10.1016/j.neunet.2020.04.014

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  1 in total

1.  Turing Universality of Weighted Spiking Neural P Systems with Anti-spikes.

Authors:  Qianqian Ren; Xiyu Liu; Minghe Sun
Journal:  Comput Intell Neurosci       Date:  2020-09-17
  1 in total

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