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The Psychological Limits of Neural Computation

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Book cover Dealing with Complexity

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

Abstract

It is known that each algorithm is Turing solvable. In the context of function computability, the Church-Turing thesis states that each intuitively computable function is Turing computable. The languages accepted by Turing machines form the recursively enumerable language family L 0 and, according to the Church-Turing thesis, L 0 is also the class of algorithmic computable sets. In spite of its generality, the Turing model can not solve any problem. Recall, for example, that the halting problem is Turing unsolvable: it is algorithmic undecidable if an arbitrary Turing machine will eventually halt when given some specified, but arbitrary, input.

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Author information

Authors and Affiliations

  1. Institute of Information Theory & Automation, Pod vodarenskou vezi 4, 182 08, Prague 8, Czech Republic

    Mirek Kárný Csc, DrSc

  2. Department of Cybernetics, University of Reading, RG6 6AY, Whiteknights, Reading, UK

    Kevin Warwick BSc, PhD, DSc, DrSc

  3. Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodarenskou vezi 2, 182 07, Prague 8, Czech Republic

    Vera Kůrková PhD

Authors
  1. Mirek Kárný Csc, DrSc
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  2. Kevin Warwick BSc, PhD, DSc, DrSc
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  3. Vera Kůrková PhD
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Editor information

Editors and Affiliations

  1. Institute of Information Theory & Automation, Pod vodarenskou vezi 4, 182 08, Prague 8, Czech Republic

    Mirek Kárný Csc, DrSc

  2. Department of Cybernetics, University of Reading, RG6 6AY, Whiteknights, Reading, UK

    Kevin Warwick BSc, PhD, DSc, DrSc

  3. Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodarenskou vezi 2, 182 07, Prague 8, Czech Republic

    Vera Kůrková PhD

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© 1998 Springer-Verlag London Limited

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Kárný, M., Warwick, K., Kůrková, V. (1998). The Psychological Limits of Neural Computation. In: Kárný, M., Warwick, K., Kůrková, V. (eds) Dealing with Complexity. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-1523-6_17

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  • DOI: https://doi.org/10.1007/978-1-4471-1523-6_17

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76160-0

  • Online ISBN: 978-1-4471-1523-6

  • eBook Packages: Springer Book Archive

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