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- W2888719757 abstract "AIdentification of a high dimensional nonlinear nonparametric system is costly. On the other hand for many real-world problems, they are sparse in the sense that not all variables contribute or contribute significantly. If these variables that do not contribute or contribute little can be identified and removed prior to system identification, the identification problem is of lower dimension. In this paper, methods to rank variables based on the Goodness of Fits are proposed without full scale identification." @default.
- W2888719757 created "2018-08-31" @default.
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- W2888719757 date "2018-06-01" @default.
- W2888719757 modified "2023-09-23" @default.
- W2888719757 title "Ranking Variables Based on Goodness of Fits in Nonlinear Nonparametric System Identification" @default.
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- W2888719757 doi "https://doi.org/10.1109/med.2018.8442944" @default.
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