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On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network

Topological indices are indispensable tools for analyzing networks to understand the underlying topology of these networks. Spiking neural network architecture (SpiNNaker or TSNN) is a million-core calculating engine which aims at simulating the behavior of aggregates of up to a billion neurons in r...

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Detalles Bibliográficos
Autor principal: Cancan, Murat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589261/
https://www.ncbi.nlm.nih.gov/pubmed/31281340
http://dx.doi.org/10.1155/2019/8429120
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author Cancan, Murat
author_facet Cancan, Murat
author_sort Cancan, Murat
collection PubMed
description Topological indices are indispensable tools for analyzing networks to understand the underlying topology of these networks. Spiking neural network architecture (SpiNNaker or TSNN) is a million-core calculating engine which aims at simulating the behavior of aggregates of up to a billion neurons in real time. Tickysim is a timing-based simulator of the interchip interconnection network of the SpiNNaker architecture. Tickysim spiking neural network is considered to be highly symmetrical network classes. Classical degree-based topological properties of Tickysim spiking neural network have been recently determined. Ev-degree and ve-degree concepts are two novel degrees recently defined in graph theory. Ev-degree and ve-degree topological indices have been defined as parallel to their corresponding counterparts. In this study, we investigate the ev-degree and ve-degree topological properties of Tickysim spiking neural network. These calculations give the information about the underlying topology of Tickysim spiking neural network.
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spelling pubmed-65892612019-07-07 On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network Cancan, Murat Comput Intell Neurosci Research Article Topological indices are indispensable tools for analyzing networks to understand the underlying topology of these networks. Spiking neural network architecture (SpiNNaker or TSNN) is a million-core calculating engine which aims at simulating the behavior of aggregates of up to a billion neurons in real time. Tickysim is a timing-based simulator of the interchip interconnection network of the SpiNNaker architecture. Tickysim spiking neural network is considered to be highly symmetrical network classes. Classical degree-based topological properties of Tickysim spiking neural network have been recently determined. Ev-degree and ve-degree concepts are two novel degrees recently defined in graph theory. Ev-degree and ve-degree topological indices have been defined as parallel to their corresponding counterparts. In this study, we investigate the ev-degree and ve-degree topological properties of Tickysim spiking neural network. These calculations give the information about the underlying topology of Tickysim spiking neural network. Hindawi 2019-06-02 /pmc/articles/PMC6589261/ /pubmed/31281340 http://dx.doi.org/10.1155/2019/8429120 Text en Copyright © 2019 Murat Cancan. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Cancan, Murat
On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
title On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
title_full On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
title_fullStr On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
title_full_unstemmed On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
title_short On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
title_sort on ev-degree and ve-degree topological properties of tickysim spiking neural network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589261/
https://www.ncbi.nlm.nih.gov/pubmed/31281340
http://dx.doi.org/10.1155/2019/8429120
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