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Computing Shortest Paths in 2D and 3D Memristive Networks

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Handbook of Memristor Networks

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Abstract

Global optimisation problems in networks often require shortest path length computations to determine the most efficient route. The simplest and most common problem with a shortest path solution is perhaps that of a traditional labyrinth or maze with a single entrance and exit. Many techniques and algorithms have been derived to solve mazes, which often tend to be computationally demanding, especially as the size of maze and number of paths increase. In addition, they are not suitable for performing multiple shortest path computations in mazes with multiple entrance and exit points. Mazes have been proposed to be solved using memristive networks and in this paper we extend the idea to show how networks of memristive elements can be utilised to solve multiple shortest paths in a single network. We also show simulations using memristive circuit elements that demonstrate shortest path computations in both 2D and 3D networks, which could have potential applications in various fields.

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Acknowledgements

The authors wish to acknowledge the financial support of the CHIST-ERA ERAnet EPSRC EP/J00801X/1 and EP/K017829/1.

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Authors and Affiliations

  1. Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, UK

    Zhanyou Ye

  2. Systems Engineering Advancement Research Initiative (SEAri), Massachusetts Institute of Technology, 77 Massachusetts Avenue, E38-576, Cambridge, MA, 02139-4307, UK

    Shi Hong Marcus Wu

  3. Zepler Institute for Photonics and Nanoelectronics, University of Southampton, Southampton, UK

    Themistoklis Prodromakis

Authors
  1. Zhanyou Ye
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  2. Shi Hong Marcus Wu
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  3. Themistoklis Prodromakis
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Correspondence to Themistoklis Prodromakis .

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Editors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA

    Leon Chua

  2. Democritus University of Thrace, Xanthi, Greece

    Georgios Ch. Sirakoulis

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, UK

    Andrew Adamatzky

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Ye, Z., Wu, S.H.M., Prodromakis, T. (2019). Computing Shortest Paths in 2D and 3D Memristive Networks. In: Chua, L., Sirakoulis, G., Adamatzky, A. (eds) Handbook of Memristor Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-76375-0_41

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  • DOI: https://doi.org/10.1007/978-3-319-76375-0_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76374-3

  • Online ISBN: 978-3-319-76375-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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