Structure of a randomly grown 2-d network.

Fioralba Ajazi; George Napolitano; Tatyana Turova; Izbassar Zaurbek

doi:10.1016/j.biosystems.2015.09.002

Structure of a randomly grown 2-d network.

Fioralba Ajazi, George Napolitano, Tatyana Turova, Izbassar Zaurbek

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Abstract

We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons.

Original language	English
Pages (from-to)	105-112
Journal	BioSystems
Volume	136
Issue number	Online 14 September 2015
DOIs	https://doi.org/10.1016/j.biosystems.2015.09.002
Publication status	Published - 2015

Subject classification (UKÄ)

Bioinformatics (Computational Biology)

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10.1016/j.biosystems.2015.09.002

1 Doctoral Thesis (compilation)

Random geometric graphs and their applications in neuronal modelling
Ajazi, F., 2018 Sept, Lund: Lund University, Faculty of Science, Centre for Mathematical Sciences. 113 p.
Research output: Thesis › Doctoral Thesis (compilation)

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title = "Structure of a randomly grown 2-d network.",

abstract = "We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons.",

author = "Fioralba Ajazi and George Napolitano and Tatyana Turova and Izbassar Zaurbek",

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AU - Napolitano, George

AU - Turova, Tatyana

AU - Zaurbek, Izbassar

PY - 2015

Y1 - 2015

N2 - We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons.

AB - We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons.

U2 - 10.1016/j.biosystems.2015.09.002

DO - 10.1016/j.biosystems.2015.09.002

M3 - Article

C2 - 26375356

SN - 1872-8324

VL - 136

SP - 105

EP - 112

JO - BioSystems

JF - BioSystems

IS - Online 14 September 2015

ER -

Structure of a randomly grown 2-d network.

Abstract

Subject classification (UKÄ)

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Research output

Random geometric graphs and their applications in neuronal modelling

Cite this