Complexity matching in neural networks

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This article adopts the complexity matching principle that the maximal efficiency of communication between two complex networks is realized when both of them are at criticality, and uses this principle to establish the value of the neuronal interaction strength at which criticality occurs.

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17 p.

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Mafahim, Javad Usefie; Lambert, David; Zare, Marzieh & Grigolini, Paolo January 9, 2015.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Arts and Sciences to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 25 times . More information about this article can be viewed below.

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  • IOP Science
    Place of Publication: Bristol, United Kingdom

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Description

This article adopts the complexity matching principle that the maximal efficiency of communication between two complex networks is realized when both of them are at criticality, and uses this principle to establish the value of the neuronal interaction strength at which criticality occurs.

Physical Description

17 p.

Source

  • New Journal of Physics, 2015. Bristol, UK: IOP Science.

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Publication Information

  • Publication Title: New Journal of Physics
  • Volume: 17
  • Pages: 17

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UNT Scholarly Works

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  • January 9, 2015

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  • Oct. 6, 2016, 10:24 p.m.

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Mafahim, Javad Usefie; Lambert, David; Zare, Marzieh & Grigolini, Paolo. Complexity matching in neural networks, article, January 9, 2015; Bristol, United Kingdom. (digital.library.unt.edu/ark:/67531/metadc910325/: accessed January 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Arts and Sciences.