Black-box Models from Input-output Measurements
2001 (English)Report (Other academic)
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 will also be 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.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2001. , 11 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2362
Black-box, Signal processing, Parameter estimation
IdentifiersURN: urn:nbn:se:liu:diva-55842ISRN: LiTH-ISY-R-2362OAI: oai:DiVA.org:liu-55842DiVA: diva2:316697