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• W2012506871 abstract "The identification of a human operator's dynamic characteristics has been an important research subject for decades. Several solutions have been proposed to obtain the model of the human operator as a controller but usually the methods require separate tests to record suitable data for identification. That is, the models cannot be estimated during normal work. This paper focuses on identification of a linear or quasilinear human operator model based on normal task execution data. The performances of ARX, ARMAX and Hammerstein-Wiener models with different orders are compared in time and frequency domains." @default.
• W2012506871 created "2016-06-24" @default.
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• W2012506871 date "2010-04-01" @default.
• W2012506871 modified "2023-09-24" @default.
• W2012506871 title "Analysis of model orders in human dynamics identification using linear polynomial and Hammerstein-Wiener structures" @default.
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• W2012506871 doi "https://doi.org/10.1109/icnsc.2010.5461586" @default.
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