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Dendrite P systems

delete2020-07-01
delete68
PRE
AI
H
Hong Peng
T
Tingting Bao
X
Xiaohui Luo
王军 (Jun Wang) *
X
Xiaoxiao Song
A
Agustín Riscos–Núñez
M
Mario J. Pérez-Jímenez
DOI:10.1016/j.neunet.2020.04.014delete
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Abstract

Abstract

En 中文
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. (c) 2020 Elsevier Ltd. All rights reserved.
Keywords:
P systems
Neural-like P systems
Dendrite P systems
Computational power
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Journal

Neural Networks cover
Neural Networks
IF:
6.3
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7.8K
Citations:
3.0W

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X
Xihua University
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University of Sevilla
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