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A programming system for implementing neural nets

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Statistical Mechanics of Neural Networks

Part of the book series: Lecture Notes in Physics ((LNP,volume 368))

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Abstract

This paper presents a programming system called NPS, for implementing neural networks, which is portable and have the ability to deal with network problems in general. The main aim of the system is to support portability and model independence by facilitating the implementation of a range of neural network models on a range of hardware. NPS is based on a specialised neural network language called NIL [Bava89]. NIL is a machine independent network specification language designed to map a spectrum of neural models onto a range of architectures. As part of the overall project, a neurocomputer architecture [Pach88] was also proposed, which is currently being implemented in CMOS.

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References

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Authors and Affiliations

  1. School of Computing and Information Technology, Thames Polytechnic, Wellington Street, SE 18, London

    A. S. Bavan

Authors
  1. A. S. Bavan
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Editor information

Luis Garrido

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© 1990 Springer-Verlag

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Bavan, A.S. (1990). A programming system for implementing neural nets. In: Garrido, L. (eds) Statistical Mechanics of Neural Networks. Lecture Notes in Physics, vol 368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3540532676_65

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  • DOI: https://doi.org/10.1007/3540532676_65

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53267-5

  • Online ISBN: 978-3-540-46808-0

  • eBook Packages: Springer Book Archive

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