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- W2159108768 abstract "A black-box model of a system is one that does not use any particular prior knowledge of the character or physics of the relationships involved. It is therefore more a question of curve-fitting than modeling. In this presentation several examples of such black-box model structures will be given. Both linear and non-linear structures are treated. Relationships between linear models, fuzzy models, neural networks and classical non-parametric models are discussed. Some reasons for the usefulness of these model types are also given. Ways to fit black box structures to measured input-output data are described, as well as the more fundamental (statistical) properties of the resulting models." @default.
- W2159108768 created "2016-06-24" @default.
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- W2159108768 date "2002-11-13" @default.
- W2159108768 modified "2023-10-10" @default.
- W2159108768 title "Black-box models from input-output measurements" @default.
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- W2159108768 doi "https://doi.org/10.1109/imtc.2001.928802" @default.
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