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Derivative Information from Fuzzy Models

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Applications of Fuzzy Sets Theory (WILF 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4578))

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Abstract

Universal approximation is the basis of theoretical research and practical application of fuzzy systems. The ability of fuzzy models to model static information has been successfully proven and tested, while on the other hand their limitations in simultaneously modelling dynamical information are well known. Generally, the fuzzy model is a correct zero-order representation of a process or function. However the derivative of its mathematical expression is not necessarily a derivative fuzzy model of the process or function. A perturbed fuzzy system, as a generalization of the traditional fuzzy system, is proposed. It has the ability to uniformly approximate continuous functions and their derivatives on arbitrarily compact sets to the desired degree.

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References

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Author information

Authors and Affiliations

  1. Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, Apartado 1013, 5001–801 Vila Real, Portugal

    Paulo Salgado & Fernando Gouveia

Authors
  1. Paulo Salgado
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  2. Fernando Gouveia
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Editor information

Francesco Masulli Sushmita Mitra Gabriella Pasi

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© 2007 Springer-Verlag Berlin Heidelberg

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Salgado, P., Gouveia, F. (2007). Derivative Information from Fuzzy Models. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_8

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  • DOI: https://doi.org/10.1007/978-3-540-73400-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73399-7

  • Online ISBN: 978-3-540-73400-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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