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Artificial Neural Networks Based on Brain Circuits Behaviour and Genetic Algorithms

  • Conference paper
Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

Once the behaviour of particular brain circuits has been analyzed, we have added up some of these patterns to Artificial Neural Networks; thus a new hybrid learning method has emerged. In order to find the best solution to a given problem, this method combines the use of Genetic Algorithms with particular changes to connection weights based in the behaviour observed in the brain circuits analyzed. The design and implementation of this combination is shown in feed-forward multilayer artificial neural networks, specifically created to solve a simple problem. We also illustrate the benefits obtained with these new nets from a comparison with previous results achieved by the optimal Artificial Neural Networks used so far for solving the same problem.

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Author information

Authors and Affiliations

  1. Department of Information and Communications Technologies, University of A Coruña, 15071 Campus de Elviña, A Coruña, Spain

    Ana Porto & Alejandro Pazos

  2. Laboratorio de Electrofisiología, Instituto de Neurobiología Ramón y Cajal, CSIC, 28002, Madrid, Spain

    Alfonso Araque

Authors
  1. Ana Porto
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  2. Alejandro Pazos
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  3. Alfonso Araque
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Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Porto, A., Pazos, A., Araque, A. (2005). Artificial Neural Networks Based on Brain Circuits Behaviour and Genetic Algorithms. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_13

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  • DOI: https://doi.org/10.1007/11494669_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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