Abstract
In the present paper we construct a higher order Takagi-Sugeno fuzzy system that approximates a Mamdani fuzzy system, with arbitrary accuracy. The goal of this construction is to reduce the computational complexity of a fuzzy systems considered, also to replace a nonlinear operator by an approximate linear operator. The proposed methodology is fully constructive, so it does not require training of the Takagi-Sugeno fuzzy system. The construction combines Takagi-Sugeno systems with the classical Lagrange interpolation.
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Bede, B., Rudas, I.J. (2014). Takagi-Sugeno Approximation of a Mamdani Fuzzy System. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_28
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DOI: https://doi.org/10.1007/978-3-319-03674-8_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03673-1
Online ISBN: 978-3-319-03674-8
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