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  • 标题:On Ev-Degree and Ve-Degree Topological Properties of Tickysim Spiking Neural Network
  • 本地全文:下载
  • 作者:Murat Cancan
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2019
  • 卷号:2019
  • 页码:1-8
  • DOI:10.1155/2019/8429120
  • 出版社:Hindawi Publishing Corporation
  • 摘要: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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