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Simplified and Yet Turing Universal Spiking Neural P Systems with Communication on Request

Overview of attention for article published in International Journal of Neural Systems, August 2018
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Article details
Title
Simplified and Yet Turing Universal Spiking Neural P Systems with Communication on Request
Published in
International Journal of Neural Systems, August 2018
DOI 10.1142/s0129065718500132
Pubmed ID
Authors
Abstract

Spiking neural P systems are a class of third generation neural networks belonging to the framework of membrane computing. Spiking neural P systems with communication on request (SNQ P systems) are a type of spiking neural P system where the spikes are requested from neighboring neurons. SNQ P systems have previously been proved to be universal (computationally equivalent to Turing machines) when two types of spikes are considered. This paper studies a simplified version of SNQ P systems, i.e. SNQ P systems with one type of spike. It is proved that one type of spike is enough to guarantee the Turing universality of SNQ P systems. Theoretical results are shown in the cases of the SNQ P system used in both generating and accepting modes. Furthermore, the influence of the number of unbounded neurons (the number of spikes in a neuron is not bounded) on the computation power of SNQ P systems with one type of spike is investigated. It is found that SNQ P systems functioning as number generating devices with one type of spike and four unbounded neurons are Turing universal.

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Mendeley demographics

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The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Professor > Associate Professor 3 19%
Student > Doctoral Student 2 13%
Student > Ph. D. Student 2 13%
Researcher 2 13%
Professor 1 6%
Other 1 6%
Unknown 5 31%
Readers by discipline
Readers by discipline Count As %
Computer Science 5 31%
Arts and Humanities 1 6%
Agricultural and Biological Sciences 1 6%
Psychology 1 6%
Neuroscience 1 6%
Other 1 6%
Unknown 6 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 November 2018.
All research outputs
#20,491,286
of 23,054,359 outputs
Outputs from International Journal of Neural Systems
#223
of 256 outputs
Outputs of similar age
#291,292
of 334,358 outputs
Outputs of similar age from International Journal of Neural Systems
#10
of 10 outputs
Altmetric has tracked 23,054,359 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 256 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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