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A Biologically Inspired Neural CPG for Sea Wave Conditions/Frequencies

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Advances in Neuro-Information Processing (ICONIP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5506))

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Abstract

This paper shows that a biology-based neural network (called a central pattern generator (CPG)) can be re-evolved for sea conditions / frequencies. The fish’s CPG operates at 1.74Hz to 5.56Hz, whereas we require performance to reach 0.05Hz to 0.35Hz (20s to 3s waves) for an alternative engineering problem. This is to enable adaptive control of wave energy devices, increasing their efficiency and power yield. To our knowledge, this is the first time a bio-inspired circuit will be integrated into the engineering domain (and for a completely different function). This provides great inspiration for utilising other neural network mechanisms for alternative tasks.

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Authors and Affiliations

  1. University of Edinburgh, King’s Buildings, Mayfield Road, Edinburgh, EH9 5JL, UK

    Leena N. Patel & Alan Murray

Authors
  1. Leena N. Patel
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  2. Alan Murray
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Editor information

Editors and Affiliations

  1. Kyushu Institute of Technology, Network Design and Research Center, 680-4 Fukuoka, 820-8502, Kawazu, Iizuka, Japan

    Mario Köppen

  2. Knowledge Engineering and Discovery Research Institute (KEDRI), School of Computing and Mathematical Sciences, Auckland University of Technology, 350 Queen Street, 10110, Auckland, New Zealand

    Nikola Kasabov

  3. Department of Electrical and Computer Engineering, Robotics Laboratory, Auckland University of Technology, 38 Princes Street, 1142, Auckland, New Zealand

    George Coghill

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© 2009 Springer-Verlag Berlin Heidelberg

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Patel, L.N., Murray, A. (2009). A Biologically Inspired Neural CPG for Sea Wave Conditions/Frequencies. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_12

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  • DOI: https://doi.org/10.1007/978-3-642-02490-0_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02489-4

  • Online ISBN: 978-3-642-02490-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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