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International Meeting of Young Computer Scientists

IMYCS 1990: Aspects and Prospects of Theoretical Computer Science pp 93–108Cite as

Complexity issues in discrete neurocomputing

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 464))

Abstract

An overview of the basic results in complexity theory of discrete neural computations is presented. Especially, the computational power and efficiency of single neurons, neural circuits, symmetric neural networks (Hopfield model), and of Boltzmann machines is investigated and characterized. Corresponding intractability results are mentioned as well. The evidence is presented why discrete neural networks (inclusively Boltzmann machines) are not to be expected to solve intractable problems more efficiently than other conventional models of computing.

This work was finished while the author was visiting the Department of Computer Science, University of Saarland, West Germany (Spring 1990). During this stay the research was partially supported by the ESPRIT II Basic Research Action Program of the EC under contract No. 3075 (Project Alcom).

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Authors and Affiliations

  1. VUSEI-AR, Dúbravská 3, 842 21, Bratislava, Czechoslovakia

    Juraj Wiedermann

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  1. Juraj Wiedermann
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Jürgen Dassow Jozef Kelemen

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© 1990 Springer-Verlag Berlin Heidelberg

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Wiedermann, J. (1990). Complexity issues in discrete neurocomputing. In: Dassow, J., Kelemen, J. (eds) Aspects and Prospects of Theoretical Computer Science. IMYCS 1990. Lecture Notes in Computer Science, vol 464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53414-8_32

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  • DOI: https://doi.org/10.1007/3-540-53414-8_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53414-3

  • Online ISBN: 978-3-540-46869-1

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