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Fuzzy representations in neural nets

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Fuzzy Logic and Fuzzy Control (IJCAI 1991)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 833))

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Abstract

Clear, crisp, precise and unambiguous: that is how you like your concepts, if you are a serial computer. But human concepts are in general vague, fuzzy or subject to borderline cases. Anyone who deals with information via computers knows the problems arising from having to categorise objects to fit the computer's crude pigeonholes, and how inflexible this is compared to what humans do. Conversely, those of us who teach mathematics and related subjects know how hard it is to induce the brain to represent clear and precise concepts.

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Authors and Affiliations

  1. School of Mathematics, University of New South Wales, P.O. Box 1, 2033, Kensington, Australia

    James Franklin

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  1. James Franklin
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Editor information

Dimiter Driankov Peter W. Eklund Anca L. Ralescu

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© 1994 Springer-Verlag Berlin Heidelberg

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Franklin, J. (1994). Fuzzy representations in neural nets. In: Driankov, D., Eklund, P.W., Ralescu, A.L. (eds) Fuzzy Logic and Fuzzy Control. IJCAI 1991. Lecture Notes in Computer Science, vol 833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58279-7_20

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  • DOI: https://doi.org/10.1007/3-540-58279-7_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58279-3

  • Online ISBN: 978-3-540-48602-2

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