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Three small universal spiking neural P systems - Zurich Open Repository and Archive


Neary, T (2015). Three small universal spiking neural P systems. Theoretical Computer Science, 567:2-20.

Abstract

In this work we give three small spiking neural P systems. We begin by constructing a universal spiking neural P system with extended rules and only 4 neurons. This is the smallest possible number of neurons for a universal system of its kind. We prove this by showing that the set of problems solved by spiking neural P systems with 3 neurons is bounded above by NLNL, and so there exists no such universal system with 3 neurons. If we generalise the output technique we immediately find a universal spiking neural P system with extended rules that has only 3 neurons. This is also the smallest possible number of neurons for a universal system of its kind. Finally, we give a universal spiking neural P system with standard rules and only 7 neurons. In addition to giving a significant improvement in terms of reducing the number of neurons, our systems also offer an exponential improvement on the time and space overheads of the small universal spiking neural P systems of other authors.

Abstract

In this work we give three small spiking neural P systems. We begin by constructing a universal spiking neural P system with extended rules and only 4 neurons. This is the smallest possible number of neurons for a universal system of its kind. We prove this by showing that the set of problems solved by spiking neural P systems with 3 neurons is bounded above by NLNL, and so there exists no such universal system with 3 neurons. If we generalise the output technique we immediately find a universal spiking neural P system with extended rules that has only 3 neurons. This is also the smallest possible number of neurons for a universal system of its kind. Finally, we give a universal spiking neural P system with standard rules and only 7 neurons. In addition to giving a significant improvement in terms of reducing the number of neurons, our systems also offer an exponential improvement on the time and space overheads of the small universal spiking neural P systems of other authors.

Citations

2 citations in Web of Science®
2 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2015
Deposited On:22 Feb 2016 13:20
Last Modified:05 Apr 2016 20:04
Publisher:Elsevier
Number of Pages:19
ISSN:0304-3975
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.tcs.2014.09.006
Official URL:http://www.sciencedirect.com/science/article/pii/S0304397514006719

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