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A Linear Programming Neural Circuit Model

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ICANN 98 (ICANN 1998)

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

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Abstract

In this paper we present a neural circuit model which can solve linear programming problems. The main feature of the model is that it takes into account saturating behaviour of circuit elements in a possible realizations. The neural model can be viewed as a gradient system and its operation is based on the penalty function approach of solving linear programming tasks. In the paper the properties of the model are discussed including stability and that how to utilize the saturation in the neurons for obtaining better performance.

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References

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Author information

Authors and Affiliations

  1. High Speed Networks Laboratory Dept. of Telecommunications and Telematics, Technical University of Budapest, Budapest, Hungary

    József Bíró

  2. Traffic Analysis and Network Performance Laboratory, Ericsson, Budapest, Hungary

    Miklós Boda

Authors
  1. József Bíró
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  2. Miklós Boda
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Skövde, PO Box 408, 54128, Skövde, Sweden

    Lars Niklasson PhD , Mikael Bodén PhD  & Tom Ziemke MSc ,  & 

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© 1998 Springer-Verlag London

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Bíró, J., Boda, M. (1998). A Linear Programming Neural Circuit Model. In: Niklasson, L., Bodén, M., Ziemke, T. (eds) ICANN 98. ICANN 1998. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-1599-1_82

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  • DOI: https://doi.org/10.1007/978-1-4471-1599-1_82

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  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76263-8

  • Online ISBN: 978-1-4471-1599-1

  • eBook Packages: Springer Book Archive

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