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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 5/2017

17.06.2015 | Original Article

Approximation and its implementation process of the stochastic hybrid fuzzy system

verfasst von: Guijun Wang, Xiaolin Sui, Xiaoping Li

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 5/2017

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Abstract

The stochastic Mamdani and Takagi–Sugeno fuzzy systems are firstly unified in a random environment, and the resulting stochastic hybrid fuzzy system is established according to some stochastic parameters. Secondly, A canonical representation of the stochastic process with orthogonal increments is presented by the properties of the Lebesgue–Stieltjes measure and stochastic integral, the approximation of the stochastic hybrid fuzzy system in the mean square sense is proved. Finally, an implementation process of this system is described through a simulation example, and the surface figure of the covariance function shows that the stochastic hybrid fuzzy system has excellent approximation capability.
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Metadaten
Titel
Approximation and its implementation process of the stochastic hybrid fuzzy system
verfasst von
Guijun Wang
Xiaolin Sui
Xiaoping Li
Publikationsdatum
17.06.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 5/2017
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-015-0369-y

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